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Strange hadron collectivity in pPb and PbPb collisions
No full textThe collective behavior of
and
strange hadrons is studied by measuring the elliptic azimuthal anisotropy (v2) using the scalar-product and multiparticle correlation methods. Proton-lead (pPb) collisions at a nucleon-nucleon center-of-mass energy
= 8.16 TeV and lead-lead (PbPb) collisions at
= 5.02 TeV collected by the CMS experiment at the LHC are investigated. Nonflow effects in the pPb collisions are studied by using a subevent cumulant analysis and by excluding events where a jet with transverse momentum greater than 20 GeV is present. The strange hadron v2 values extracted in pPb collisions via the four- and six-particle correlation method are found to be nearly identical, suggesting the collective behavior. Comparisons of the pPb and PbPb results for both strange hadrons and charged particles illustrate how event-by-event flow fluctuations depend on the system size.BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA).
Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 884104, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - EOS" - be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" - 390833306, and under project number 400140256 - GRK2497; the Hungarian Academy of Sciences, the New National Excellence Program - uNKP, the NKFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the FundacAo para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF "a way of making Europe", and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B05F650021 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).Publisher versio
Near-field radiative transfer for biologically inspired structures
No full textThe field of biomimetic nanophotonics has the potential to open up unprecedented pathways for the development of sophisticated and unique devices and systems as it brings different disciplines together, including biology, physics, optics, thermal sciences, design, and nanoscale manufacturing. Given the complexity of the field, it is crucial to develop the computational tools necessary to predict the interaction between different phenomena before delving into expensive laboratory studies. In this chapter, we explore biomimetic nanophotonic systems from the standpoint of thermal and computational sciences. Particularly, we focus on near-field radiative transfer for different structures by using finite-difference time domain algorithm for the solution of problems in complex geometries. We provide the results for two case studies, one inspired by the Morpho didius butterfly and the other one from neon tetra Paracheirodon innesi fish, showing that significant spectrally selective bands can be obtained. We expect that these approaches are eventually to be adapted for new manufacturing paradigms which may be useful for the development of next-generation sensors, energy harvesting devices, and radiative cooling mechanisms
Media over QUIC: Initial testing, findings and results
No full textWith its advantages over TCP, QUIC created a new field for developing media-Aware low-latency delivery solutions. The problem space is being examined by the new Media over QUIC (moq) working group in the IETF. In this paper, we study one of the initial proposals in detail, do a gap analysis and create an open-source testbed by introducing new essential features
Meta reinforcement learning for rate adaptation
No full textAdaptive bitrate (ABR) schemes enable streaming clients to adapt to time-varying network/device conditions to achieve a stall-free viewing experience. Most ABR schemes use manually tuned heuristics or learning-based methods. Heuristics are easy to implement but do not always perform well, whereas learning-based methods generally perform well but are difficult to deploy on low-resource devices. To make the most out of both worlds, we develop Ahaggar, a learning-based scheme running on the server side that provides quality-aware bitrate guidance to streaming clients running their own heuristics. Ahaggar's novelty is the meta reinforcement learning approach taking network conditions, clients' statuses and device resolutions, and streamed content as input features to perform bitrate guidance. Ahaggar uses the new Common Media Client/Server Data (CMCD/SD) protocols to exchange the necessary metadata between the servers and clients. Experiments on an open-source system show that Ahaggar adapts to unseen conditions fast and outperforms its competitors in several viewer experience metrics.TÜBİTA
An efficient algorithm for disparity map compression based on spatial correlations and its low-cost hardware architecture
No full textThis paper proposes a low-cost disparity map compression algorithm and its hardware architecture for high resolution and high frame rate applications. The proposed algorithm uses spatial correlations between neighboring disparities and has two variants. The first variant encodes the current disparity using its left neighbor, whereas the second variant benefits from left and upper neighbors. The proposed algorithm obtains 48% and 56% savings in memory space on the average for its variants. The proposed architecture can support 1080p resolution at 60 fps on a low-cost FPGA device while consuming very low area and power
Internal migration and house prices in Australia
No full textAustralia is one of the most mobile countries in the world due to internal migration. This study provides the first evidence of the causal impact of internal migration inflow on house price changes across 237 statistical regions in Australia from 2014 to 2019. Employing a spatial correlation approach, the paper indicates that internal migration that amounts to 1% of the initial local area population is associated with a 0.52–0.71% increase in house prices in the three most populated states of Australia. Migration inflow has a significant positive effect on house price changes in metropolitan areas of Sydney and Melbourne rather than non-metropolitan regions.American Economic Association Meeting ; Australian Bureau of Statistics ; Queensland University of Technology ; Universität zu Köl
Big data–enabled sign prediction for Borsa Istanbul intraday equity prices
No full textThis paper employs a big data source, the Borsa Istanbul's “data analytics” information, to predict 5-min up, down, and steady signs drawn from closing price changes. Seven machine learning algorithms are compared with 2018 data for the entire year. Success levels for each method are reported for 26 liquid stocks in terms of macro-averaged F-measures. For the 5-min lagged data, nine equities are found to be statistically predictable. For lagged data over longer periods, equities remain predictable, decreasing gradually to zero as the markets absorb the data over time. Furthermore, economic gains for the nine equities are analyzed with algorithms where short selling is allowed or not allowed depending on these predictions. Four equities are found to yield more economic gains via machine learning–supported trading strategies than the equities' own price performances. Under the “efficient market hypothesis,” the results imply a lack of “semistrong-form efficiency.”Publisher versio
Revisiting network reconfiguration in the era of unpredictable ev charger integration
No full textAn expanded network of electric vehicle (EV) chargers is required due to the rapid uptake of EVs. The voltage profile may be disturbed by the unanticipated integration of these chargers into distribution networks, potentially resulting in system instability. There is currently no study that offers a methodology for evaluating the voltage responsiveness of various network configurations in relation to EV chargers, even though prior research has sought to improve network parameters in the face of distributed generation and network reconfiguration (NR). The problem of choosing the best network configuration remains unsolved due to this gap. In order to address this, our study analyzes a distribution network in all of its possible configurations, taking into account the possible effects of electric vehicle chargers placed in all possible locations, in the Python programming language using the Pandapower network analysis library. The results of this study will give system administrators useful information for choosing the most reliable network configuration in advance of the unpredictable integration of EV chargers into their distribution networks
Are crowdsourcing announcements signals of customer orientation? A comparison of consumer responses to product- versus communication-related campaigns
No full textPurpose: This study aims to examine consumers’ responses to crowdsourcing campaigns in the request initiation stage using the signaling theory from economics. The purpose of the research is threefold. First, it provides a comprehensive classification of various task types within crowdsourcing. Second, it conceptualizes crowdsourcing announcements as signals of customer orientation and empirically tests the differential effects of the two most common crowdsourcing task types (product- and communication-related) on customer orientation perceptions. Third, it illuminates the downstream behavioral consequences of crowdsourcing campaign announcements. Design/methodology/approach: The authors conducted secondary data analysis of 883 crowdsourcing campaigns (pilot study) to provide evidence on the differential effects of crowdsourcing task types. In addition, four laboratory experiments were conducted to test the theoretical arguments. To test the main effect of crowdsourcing task types, Study 1A (N = 252 MTurk workers) used a one-factor (product- vs communication-related crowdsourcing vs control) between-subject design, whereas Study 1B (N = 171 undergraduate students) used a 2 (task type: product- vs communication-related) by 2 (product category: restaurant vs fashion) between-subject design. Study 2 (N = 93 MTurk workers) explored the underlying mechanism using a one-factor (product- vs communication-related) between-subject design. Study 3 (N = 375 MTurk workers) investigated the boundary condition for the effect of task type with a 2 (task type: product- vs communication-related) by 3 (company credibility: low vs neutral vs high) between-subject design. Findings: The pilot study provides evidence for the conceptualized typology and the differential effects of crowdsourcing task types. Study 1A reveals that product-related crowdsourcing tends to have a more substantial impact than communication-related crowdsourcing on how customer-oriented consumers perceive a company. Study 1B validates the results of Study 1A in a different product category and population sample. Study 2 shows that the differential customer-orientation effect is mediated by the perceived cost of implementing the crowdsourcing outcome and unravels the differences in consumers’ purchase and campaign participation intentions depending on task type. Study 3 highlights that the customer-orientation effect attenuates as company credibility increases. Research limitations/implications: This research contributes to the crowdsourcing literature by categorizing the various types of crowdsourcing campaigns companies undertake and revealing the differential impact of the different types of crowdsourcing campaigns on consumers’ perceptions and behavioral intentions. In doing so, this research converges two lines of consumer research on crowdsourcing, i.e. product- and communication-related crowdsourcing. The findings add to the debate over the returns from research and development (R&D) versus advertising and extend it from marketing strategy to crowdsourcing literature. Practical implications: The findings highlight the importance of choosing specific task types for crowdsourcing and lead to practical recommendations on designing crowdsourcing campaigns to maximize their benefits to crowdsourcing brands. Originality/value: To the best of the authors’ knowledge, this is the first study that differentiates crowdsourcing task types and compares their effectiveness from a consumer perspective
Fashionably late: Differentially costly signaling of sociometric status through a subtle act of being late
No full textThis research examines how arriving late to social gatherings operates as a signal of social connectedness and desirability, leading to elevated sociometric status attributions. Drawing on costly signaling theory and the premises of sociometric status and consumption mimicry, we argue that tardiness to a gathering, as a costly and visible signal, can lead to positive inferences of sociometric status, thereby leading to mimicry. We define fashionably late as a separating equilibrium tardiness based on a signaling game and demonstrate through a series of experimental studies that people infer higher status to late- rather than on-time-arriving people. Consequently, they strive to be in the same social network with such individuals, favor their product choices, and imitate their consumption behaviors. This research contributes to the literature on the conspicuous consumption of time and to research on costly signaling by revealing the powerful influence of signaling (through late arrival to a social event) on perceptions of sociometric status