Regional surname affinity: a spatial network approach

OBJECTIVE We investigate surname affinities among areas of modern‐day China, by constructing a spatial network, and making community detection. It reports a geographical genealogy of the Chinese population that is result of population origins, historical migrations, and societal evolutions. MATERIALS AND METHODS We acquire data from the census records supplied by China's National Citizen Identity Information System, including the surname and regional information of 1.28 billion registered Chinese citizens. We propose a multilayer minimum spanning tree (MMST) to construct a spatial network based on the matrix of isonymic distances, which is often used to characterize the dissimilarity of surname structure among areas. We use the fast unfolding algorithm to detect network communities. RESULTS We obtain a 10‐layer MMST network of 362 prefecture nodes and 3,610 edges derived from the matrix of the Euclidean distances among these areas. These prefectures are divided into eight groups in the spatial network via community detection. We measure the partition by comparing the inter‐distances and intra‐distances of the communities and obtain meaningful regional ethnicity classification. DISCUSSION The visualization of the resulting communities on the map indicates that the prefectures in the same community are usually geographically adjacent. The formation of this partition is influenced by geographical factors, historic migrations, trade and economic factors, as well as isolation of culture and language. The MMST algorithm proves to be effective in geo‐genealogy and ethnicity classification for it retains essential information about surname affinity and highlights the geographical consanguinity of the population.National Natural Science Foundation of China, Grant/Award Numbers: 61773069, 71731002; National Social Science Foundation of China, Grant/Award Number: 14BSH024; Foundation of China of China Scholarships Council, Grant/Award Numbers: 201606045048, 201706040188, 201706040015; DOE, Grant/Award Number: DE-AC07-05Id14517; DTRA, Grant/Award Number: HDTRA1-14-1-0017; NSF, Grant/Award Numbers: CHE-1213217, CMMI-1125290, PHY-1505000 (61773069 - National Natural Science Foundation of China; 71731002 - National Natural Science Foundation of China; 14BSH024 - National Social Science Foundation of China; 201606045048 - Foundation of China of China Scholarships Council; 201706040188 - Foundation of China of China Scholarships Council; 201706040015 - Foundation of China of China Scholarships Council; DE-AC07-05Id14517 - DOE; HDTRA1-14-1-0017 - DTRA; CHE-1213217 - NSF; CMMI-1125290 - NSF; PHY-1505000 - NSF)Published versio

Excitonic effects in nonlinear optical responses: Exciton-state formalism and first-principles calculations

Nonlinear optical (NLO) responses have garnered tremendous interest for decades due to their fundamental and technological interests. The theory and calculations of NLO responses including electron-hole interactions, which is especially crucial for reduced-dimensional materials, however, remain underdeveloped. Here, we develop an ab initio approach to calculate second-order nonlinear responses (such as second harmonic generation (SHG) and shift current) with excitonic effects in an exciton-state basis, going beyond the independent-particle approximation. We compute SHG in monolayer h-BN and MoS2 employing exciton states from GW-Bethe-Salpeter equation (GW-BSE) calculations and show both materials exhibit huge excitonic enhancement. The physical origin of the enhancement is directly understood through the coupling amplitudes among exciton states, assisted with diagrammatic representations. Our method provides an accurate and ab initio description of second-order NLO responses, capturing self-energy and electron-hole interaction effects.Comment: 14 pages, 3 figures; Minor revisio

Adaptive business intelligence in healthcare - A platform for optimising surgeries

Adaptive Business Intelligence (ABI) combines predictive with prospective analytics in order to give support to the decision making process. Surgery scheduling in hospital operating rooms is a high complex task due to huge volume of surgeries and the variety of combinations and constraints. This type of activity is critical and is often associated to constant delays and significant rescheduling. The main task of this work is to provide an ABI based platform capable of estimating the time of the surgeries and then optimising the scheduling (minimizing the waste of resources). Combining operational data with analytical tools this platform is able to present complex and competitive information to streamline surgery scheduling. A case study was explored using data from a portuguese hospital. The best achieved relative absolute error attained was 6.22%. The paper also shows that the approach can be used in more general applications.This work has been supported by FCT –Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/201

Network of Econophysicists: a weighted network to investigate the development of Econophysics

The development of Econophysics is studied from the perspective of scientific communication networks. Papers in Econophysics published from 1992 to 2003 are collected. Then a weighted and directed network of scientific communication, including collaboration, citation and personal discussion, is constructed. Its static geometrical properties, including degree distribution, weight distribution, weight per degree, and betweenness centrality, give a nice overall description of the research works. The way we introduced here to measure the weight of connections can be used as a general one to construct weighted network.Comment: 6 pages, 7 figure

Chiral Kondo Lattice in Doped MoTe2_2/WSe2_2 Bilayers

We theoretically study the interplay between magnetism and a heavy Fermi liquid in the AB stacked transition metal dichalcogenide bilayer system MoTe$_2$/WSe$_2$ in the regime in which the Mo layer supports localized magnetic moments coupled by interlayer electron tunnelling to a weakly correlated band of itinerant electrons in the W layer. We show that the interlayer electron transfer leads to a chiral Kondo exchange, with consequences including a strong dependence of the Kondo temperature on carrier concentration, a topological hybridization gap and an anomalous Hall effect. The theoretical model exhibits two phases, a small Fermi surface magnet and a large Fermi surface heavy Fermi liquid; the transition between them is first order. A low-energy theory is developed for the the transport properties of the two states. Implications of our results for present and future experiments on MoTe$_2$/WSe$_2$ bilayer heterostructures are discussed.Comment: (7+9) pages, (4+6) figure

Determining the optimal range of coupling coefficient to suppress decline in WPTs efficiency due to increased resistance with temperature rise

The continuous operation of the wireless power transfer system (WPTS) under high-frequency switching activity might cause a temperature rise in various system\u27s components. That temperature rise might increase the resistance of the primary and secondary coils, which will lead to a significant decline in the system\u27s efficiency. To address this problem at the design stage, we investigate the optimal range of the coupling coefficient that suppresses the efficiency drop due to the increasing resistance of the WPTS components. The proposed optimal range of the coupling coefficient can also ensure the output power requirements of the WPTS. Using four different WPTSs, the determination method for the optimal range of coupling coefficients under different system operational frequencies was developed and implemented. A 3-kW resonant experimental prototype WPTS was designed and built to validate the proposed coupling coefficients experimentally. The experimental results show that the optimized coupling range successfully suppressed the efficiency decline resulting from the increasing resistance caused by temperature rise

Time Course of Dichoptic Masking in Normals and Suppression in Amblyopes

Purpose: To better understand the relationship between dichoptic masking in normal vision and suppression in amblyopia we address three questions: First, what is the time course of dichoptic masking in normals and amblyopes? Second, is interocular suppression low-pass or band-pass in its spatial dependence? And third, in the above two regards, is dichoptic masking in normals different from amblyopic suppression? Methods: We measured the dependence of dichoptic masking in normal controls and amblyopes on the temporal duration of presentation under three conditions; monocular (the nontested eye—i.e., dominant eye of normals or nonamblyopic eye of amblyopes, being patched), dichoptic-luminance (the nontested eye seeing a mean luminance—i.e., a DC component) and dichoptic-contrast (the nontested eye seeing high-contrast visual noise). The subject had to detect a letter in the other eye, the contrast of which was varied. Results: We found that threshold elevation relative to the patched condition occurred in both normals and amblyopes when the nontested eye saw either 1/f or band-pass filtered noise, but not just mean luminance (i.e., there was no masking from the DC component that corresponds to a channel responsive to a spatial frequency of 0 cyc/deg); longer presentation of the target (corresponding to lower temporal frequencies) produced greater threshold elevation. Conclusions: Dichoptic masking exhibits similar properties in both subject groups, being low-pass temporally and band-pass spatially, so that masking was greatest at the longest presentation durations and was not greatly affected by mean luminance in the nontested eye

CARLA-Loc: Synthetic SLAM Dataset with Full-stack Sensor Setup in Challenging Weather and Dynamic Environments

The robustness of SLAM algorithms in challenging environmental conditions is crucial for autonomous driving, but the impact of these conditions are unknown while given the difficulty of arbitrarily changing the relevant environmental parameters of the same environment in the real world. Therefore, we propose CARLA-Loc, a synthetic dataset of challenging and dynamic environments built on CARLA simulator. We integrate multiple sensors into the dataset with strict calibration, synchronization and precise timestamping. 7 maps and 42 sequences are posed in our dataset with different dynamic levels and weather conditions. Objects in both stereo images and point clouds are well-segmented with their class labels. We evaluate 5 visual-based and 4 LiDAR-based approaches on varies sequences and analyze the effect of challenging environmental factors on the localization accuracy, showing the applicability of proposed dataset for validating SLAM algorithms