Three-dimensional (3D) modelling is an efficient technique for preserving visual archaeological legacy by offering chronological evidence of architectural alterations. This research used a mixed-methods approach to explore the Itakhola Mound Temple, particularly its five phases, as a notable archaeological site in the Lalmai-Mainamati Hill region of the Cumilla district, Bangladesh. All the available evidence and field observations suggest that the highest reconstruction phase is situated above the other four phases. Consequently, only the fifth phase is observable, as opposed to the others. To render all phases visibly, the solid 3D model has been generated utilizing several software tools, for example, Autodesk AutoCAD, 3D Studio Max, and Adobe Photoshop. These elucidated the chronological architectural modifications of the temple and the likely reasons for these alterations. This research elucidates the rationale for choosing solid modelling over photogrammetry or laser scanning methods, as well as the alterations in measurement over several phases. This study emphasizes the significance of virtual preservation, specifically concerning temple architecture only, rather than environmental elements. This demonstrates that 3D solid modelling functions as a sustainable digital approach for the virtual preservation and representation of archaeological monuments, thereby aiding future investigations and conservation efforts.
Collective effects, such as superradiance and subradiance are central to emerging quantum technologies -- from sensing to energy storage -- and play an important role in light-harvesting. These effects enhance or suppress rates of dynamic processes (absorption, emission, and transfer) due to the formation of symmetric or antisymmetric collective states. However, collective effects in different contexts -- absorption, emission, and transfer -- have often been defined disparately, especially across different communities, leading to results that are not immediately transferable between different contexts. Here, we describe all three types of collective effects using a common Dicke framework that resolves the apparent discrepancies between different approaches. It allows us to generalise previously known collective effects involving spins into new ones involving aggregates of harmonic oscillators or other degrees of freedom. It also explains how collective effects can be engineered to be robust against both disorder and noise, paving the way for more resilient quantum devices.
Collisions of protons with lead nuclei (pPb), such as those measured by the LHCb experiment, provide a unique environment to study the surprising emergence of collective, fluid-like phenomena in small systems. A key signature of this hydrodynamic behavior is the predicted formation of a toroidal vorticity structure. In this work, I use two-particle femtoscopic correlations of non-identical hadrons, specifically proton-pion ($pπ^+$) pairs, as a novel probe for this phenomenon. Previous works indicate that the collective flow of the system is consistent with the formation of a vortex ring created by the passage of the proton through the lead nucleus, which modifies the collective flow profile. I establish that the resulting emission asymmetry between protons and pions, driven by their mass difference and differential response to the vortical flow, is directly linked to the initial vorticity and can be measured using femtoscopy. This method therefore presents a new, sensitive observable for characterizing the rotational dynamics of the matter created in small collision systems.
Resumo Este texto apresenta uma revisão de literatura, explorando os impactos do chatbot ChatGPT no contexto educacional. A questão norteadora deste estudo é: quais são as potencialidades e limitações da aplicação da Inteligência Artificial (ChatGPT) na Educação? Para responder a essa questão, foi realizada uma busca sistemática em bases de dados por artigos recentes sobre ChatGPT e Educação, tendo sido selecionados 10 estudos a partir de critérios como relevância e qualidade. Os resultados e a discussão evidenciaram o potencial do ChatGPT como uma valiosa ferramenta complementar na geração automatizada de conteúdos e avaliações personalizadas. No entanto, revelaram também limitações cruciais, como lógica falha, respostas imprecisas e enviesamento. Questões éticas, como o estímulo ao plágio e a inibição da criatividade dos alunos, são preocupações latentes que exigem estratégias pedagógicas cuidadosas. Conclui-se que ainda há muito a ser investigado antes de uma integração segura e eficaz do ChatGPT na prática educacional.
Museums. Collectors and collecting, Bibliography. Library science. Information resources
Collecting traffic data is crucial for transportation systems and urban planning, and is often more desirable through easy-to-deploy but power-constrained devices, due to the unavailability or high cost of power and network infrastructure. The limited power means an inevitable trade-off between data collection duration and accuracy/resolution. We introduce a novel learning-based framework that strategically decides observation timings for battery-powered devices and reconstructs the full data stream from sparsely sampled observations, resulting in minimal performance loss and a significantly prolonged system lifetime. Our framework comprises a predictor, a controller, and an estimator. The predictor utilizes historical data to forecast future trends within a fixed time horizon. The controller uses the forecasts to determine the next optimal timing for data collection. Finally, the estimator reconstructs the complete data profile from the sampled observations. We evaluate the performance of the proposed method on PeMS data by an RNN (Recurrent Neural Network) predictor and estimator, and a DRQN (Deep Recurrent Q-Network) controller, and compare it against the baseline that uses Kalman filter and uniform sampling. The results indicate that our method outperforms the baseline, primarily due to the inclusion of more representative data points in the profile, resulting in an overall 10\% improvement in estimation accuracy. Source code will be publicly available.
Mahdi Chegnizadeh, Marco Scigliuzzo, Amir Youssefi
et al.
Collective phenomena arise from interactions within complex systems, leading to behaviors absent in individual components. Observing quantum collective phenomena with macroscopic mechanical oscillators has been impeded by the stringent requirement that oscillators be identical. Here, we demonstrate the quantum regime for collective motion of $N=6$ mechanical oscillators, a hexamer, in a superconducting circuit optomechanical platform. By increasing the optomechanical couplings, the system transitions from individual to collective motion, characterized by a $\sqrt{N}$ enhancement of cavity-collective mode coupling, akin to super-radiance of atomic ensembles. Using sideband cooling, we prepare the collective mode in the quantum ground state and measure its quantum sideband asymmetry, with zero-point motion distributed across distant oscillators. This regime of optomechanics opens avenues for studying multi-partite entanglement, with potential advances in quantum metrology.
We investigate research challenges and opportunities for visualization in motion during outdoor physical activities via an initial corpus of real-world recordings that pair egocentric video, biometrics, and think-aloud observations. With the increasing use of tracking and recording devices, such as smartwatches and head-mounted displays, more and more data are available in real-time about a person's activity and the context of the activity. However, not all data will be relevant all the time. Instead, athletes have information needs that change throughout their activity depending on the context and their performance. To address this challenge, we describe the collection of a diverse corpus of information needs paired with contextualizing audio, video, and sensor data. Next, we propose a first set of research challenges and design considerations that explore the difficulties of visualizing those real data needs in-context and demonstrate a prototype tool for browsing, aggregating, and analyzing this information. Our ultimate goal is to understand and support embedding visualizations into outdoor contexts with changing environments and varying data needs.
We investigate collective spin excitations of graphene electrons with short-ranged interactions and subject to the external Zeeman magnetic field. We find that in addition to the familiar Silin spin wave, a collective spin-flip excitation that reduces to the uniform precession when the wave's momentum approaches zero, the magnetized graphene supports another collective mode visible in the transverse spin susceptibility: a collective spin-current mode. Unlike the Silin wave, this mode is not dictated by the spin-rotational symmetry but rather owns its existence to the pseudo-spin structure of the graphene lattice. We find the new collective excitation to become sharply defined in a finite interval of wave's momenta, the range of which is determined by the interaction and the magnetization.
Human societies are organized and developed through collective cooperative behaviors, in which interactions between individuals are governed by the underlying social connections. It is well known that, based on the information in their environment, individuals can form collective cooperation by strategically imitating superior behaviors and changing unfavorable surroundings in self-organizing ways. However, facing the tough situation that some humans and social bots keep spreading misinformation, we still lack the systematic investigation on the impact of such proliferation of misinformation on the evolution of social cooperation. Here we study this problem by virtue of classical evolutionary game theory. We find that misinformation generally impedes the emergence of collective cooperation compared to scenarios with completely true information, although the level of cooperation is slightly higher when the benefits provided by cooperators are reduced below a proven threshold. We further show that this possible advantage shrinks as social connections become denser, suggesting that misinformation is more detrimental to the formation of collective cooperation when 'social viscosity' is low. Our results uncover the quantitative effect of misinformation on the social cooperative behavior in the complex networked society, and pave the way for designing possible interventions to improve collective cooperation.
Abstract: As part of the innovation process, clinical research generates valuable data to assess technological solutions in healthcare, linking scientific research and knowledge transfer to provide beneficial innovations for society. However, the generated clinical data do not appear to be adequately available to the scientific community and society. The present study seeks to analyze the effectiveness of databases of clinical records as a source of relevant information for scientific research. We conducted a comparative analysis of 27 correlations of clinical trials between three different technologies and their scientific articles by consulting two information sources. Making connections between the data from these sources proved to be challenging. In addition, a considerable time lag (40 months on average) was observed between the end of the study and the publication of the results. Among the completed studies, 56% had not published their results in any of the channels studied. In addition to the paucity of reported results, the poor publication record of clinical trials is further evident in the lack of information on these studies in scientific publications. Thus, databases of clinical records are a potential source of information and may come to represent a central tool in the search for new technological solutions in healthcare.
Museums. Collectors and collecting, Bibliography. Library science. Information resources
The book presents itself as a manual on women’s clothing in Northern Europe through the years 1360-1415, and is aimed at reenactors. The time frame - 1360-1415 - means that we are in the beginning of the Late Medieval period as defined by English and northern European historians (normally set to 1300-1500). The geographical setting is Northern Europe, here defined as: “from Germany til (sic) central Sweden, and from the Baltic region to the Norwegian West coast.”
One of the challenges in quantum information science is to control open quantum systems with a large number of qubits. An important aspect of many-body systems is the emergence of collective phenomena. One collective noise model is an open atomic system in an electromagnetic environment. This model was considered by Dicke in the 50's Dicke. In this paper, we study the entropic decay in Dicke's model and other related collective noise models. Specifically, we develop a general framework to estimate the spectral gap and modified logarithmic Sobolev constant of these collective noise models. In addition, we study the necessary mixing conditions a general Dicke's model must satisfy in order to have a unique equilibrium state. The combination of representation theory and entropy estimates could be a guideline to study more general collective noise models.
Federico Tartarini, Mario Frei, Stefano Schiavon
et al.
Collecting feedback from people in indoor and outdoor environments is traditionally challenging and complex in a reliable, longitudinal, and non-intrusive way. This paper introduces Cozie Apple, an open-source mobile and smartwatch application for iOS devices. This platform allows people to complete a watch-based micro-survey and provide real-time feedback about environmental conditions via their Apple Watch. It leverages the inbuilt sensors of a smartwatch to collect physiological (e.g., heart rate, activity) and environmental (sound level) data. This paper outlines data collected from 48 research participants who used the platform to report perceptions of urban-scale environmental comfort (noise and thermal) and contextual factors such as who they were with and what activity they were doing. The results of 2,400 micro-surveys across various urban settings are illustrated in this paper showing the variability of noise-related distractions, thermal comfort, and associated context. The results show people experience at least a little noise distraction 58% of the time, with people talking being the most common reason (46%). This effort is novel due to its focus on spatial and temporal scalability and collection of noise, distraction, and associated contextual information. These data set the stage for larger deployments, deeper analysis, and more helpful prediction models toward better understanding the occupants' needs and perceptions. These innovations could result in real-time control signals to building systems or nudges for people to change their behavior.
Consider an urn filled with balls, each labeled with one of several possible collective decisions. Now, let a random voter draw two balls from the urn and pick her more preferred as the collective decision. Relabel the losing ball with the collective decision, put both balls back into the urn, and repeat. Once in a while, relabel a randomly drawn ball with a random collective decision. We prove that the empirical distribution of collective decisions produced by this process approximates a maximal lottery, a celebrated probabilistic voting rule proposed by Peter C. Fishburn (Rev. Econ. Stud., 51(4), 1984). In fact, the probability that the collective decision in round $n$ is made according to a maximal lottery increases exponentially in $n$. The proposed procedure is more flexible than traditional voting rules and bears strong similarities to natural processes studied in biology, physics, and chemistry as well as algorithms proposed in machine learning.
In decentralised autonomous systems it is the interactions between individual agents which govern the collective behaviours of the system. These local-level interactions are themselves often governed by an underlying network structure. These networks are particularly important for collective learning and decision-making whereby agents must gather evidence from their environment and propagate this information to other agents in the system. Models for collective behaviours may often rely upon the assumption of total connectivity between agents to provide effective information sharing within the system, but this assumption may be ill-advised. In this paper we investigate the impact that the underlying network has on performance in the context of collective learning. Through simulations we study small-world networks with varying levels of connectivity and randomness and conclude that totally-connected networks result in higher average error when compared to networks with less connectivity. Furthermore, we show that networks of high regularity outperform networks with increasing levels of random connectivity.
Este estudo assenta de modo exclusivo na importante fonte documental que são as Memórias Paroquiais que resultaram do inquérito ordenado em 1758 pelo Marquês de Pombal. Procedeu-se ao levantamento e transcrição paleográfica de todos os registos referentes a hospitais, Misericórdias e outros estabelecimentos assistenciais, contidos nos depoimentos respeitantes às 4073 Freguesias do país, sendo encontrados os pretendidos registos em 398 Freguesias, com indicação de localização de hospitais e/ou Misericórdias e/ou Albergarias ou outros estabelecimentos de assistência. Na maior parte dos casos os mesmos possuem informações adicionais, que se revelaram do maior interesse para este estudo, não só em termos panorâmicos, mas proporcionando estudos parcelares em âmbitos diversos da mesma temática.
Arts in general, Museums. Collectors and collecting