Coherent Response Research Articles

Shifting official development assistance during COVID-19: earmarking, donor concentration and loans

ContextIn contrast to bilateral aid, aid disbursed from multilateral institutions increased significantly at the onset of the COVID-19 pandemic. Yet, at a time when a coherent and effective multilateral response...

Easy and effective! Data augmentation for knowledge-aware dialogue generation via multi-perspective sentences interaction

In recent years, knowledge-based dialogue generation has garnered significant attention due to its capacity to produce informative and coherent responses through the integration of external knowledge into models. However, obtaining high-quality knowledge that aligns with the dialogue content poses a considerable challenge, necessitating substantial time and resources. To tackle the issue of limited dialogue data, a majority of research endeavors concentrate on data augmentation to augment the volume of training data. Regrettably, these methods overlook knowledge augmentation, leading to a restricted diversity in input data and yielding enhancements solely in specific metrics. Real-world conversations exhibit a spectrum of characteristics, including repetitions, reversals, and interruptions, demanding a heightened level of data diversity. In this study, we introduce a straightforward yet effective data augmentation technique known as Multi-perspective Sentence Interaction to bolster the connections among sentences from varied viewpoints. Through an examination of target responses from multiple dialogue perspectives, we enhance our comprehension of the relationships between dialogue sentences, thereby facilitating the expansion of knowledge-based dialogue data. Through experiments conducted on various knowledge-based dialogue datasets and utilizing different models, our findings illustrate a notable enhancement in the quality of model generation facilitated by our method. Specifically, we observed a 3.5% enhancement in reply accuracy and a 0.1506 increase in diversity (DIST-2). Moreover, there was a substantial improvement in knowledge selection accuracy by 19.04% and a reduction in model perplexity by 31.48%.

Optimization of the pipe diameters and the dynamic operation of a district heating network using a robust initialization strategy

District heating networks (DHN) are systems offering a substantial solution for the decarbonization of heat production. As these systems involve significant costs, the development of digital tools for their optimization becomes a necessity. In the literature, there is a lack of studies optimizing the sizing of the DHN while considering a dynamic operation of the system with a detailed physics. In this work, we developed a Non-Linear Programming (NLP) optimization used in a case study of a DHN where the pipe sizing and the operation are optimized with a precise modeling of the distribution network. The method of Orthogonal Collocation on Finite Elements (OCFE) was employed to discretize the partial differential equation (PDE) governing the temperature evolution in the pipes. In addition, the pressure drops were modeled using the Darcy–Weisbach equation. Three optimization criteria were used: investment cost of the pipes, operational cost, and the global cost. The optimization provided the pipe diameters that best fit each optimization criterion. Furthermore, several initializations were tested to verify if the obtained optimum was a confidence optimum and if the resolution was robust. Finally, the optimization provided a coherent response to the variation in the cost of heat production.

Personality testing of large language models: limited temporal stability, but highlighted prosociality.

As large language models (LLMs) continue to gain popularity due to their human-like traits and the intimacy they offer to users, their societal impact inevitably expands. This leads to the rising necessity for comprehensive studies to fully understand LLMs and reveal their potential opportunities, drawbacks and overall societal impact. With that in mind, this research conducted an extensive investigation into seven LLMs, aiming to assess the temporal stability and inter-rater agreement on their responses on personality instruments in two time points. In addition, LLMs' personality profile was analysed and compared with human normative data. The findings revealed varying levels of inter-rater agreement in the LLMs' responses over a short time, with some LLMs showing higher agreement (e.g. Llama3 and GPT-4o) compared with others (e.g. GPT-4 and Gemini). Furthermore, agreement depended on used instruments as well as on domain or trait. This implies the variable robustness in LLMs' ability to reliably simulate stable personality characteristics. In the case of scales which showed at least fair agreement, LLMs displayed mostly a socially desirable profile in both agentic and communal domains, as well as a prosocial personality profile reflected in higher agreeableness and conscientiousness and lower Machiavellianism. Exhibiting temporal stability and coherent responses on personality traits is crucial for AI systems due to their societal impact and AI safety concerns.

Laser-induced modification of an excited-state vibrational wave packet in neutral H2 observed in a pump-control scheme

We observe and modify a molecular vibrational wave packet in an electronically excited state of the neutral hydrogen molecule. In an extreme-ultraviolet (XUV) time-domain absorption spectroscopy experiment, we launch a vibrational wave packet in the DΠu13pπ state of H2 and track its time evolution via the coherent dipole response. The reconstructed time-dependent dipole from experimentally measured XUV absorption spectra provides access to the revival of the vibrational wave packet, which we control via an intense near-infrared (NIR) pulse. Tuning the intensity of the NIR pulse, we observe the revival of the wave packet to be significantly modified, which is supported by the results of a multilevel simulation as well as an analytical model based on state-specific phase shifts. The NIR field is applied only 7 fs after the creation of the wave packet but influences its evolution up to at least its first revival at 270 fs. This experimental approach for nonlocal-in-time laser modification of quantum dynamics in a pump-control scheme enabled by molecular self-probing is generally applicable to a large range of molecules and materials as it only requires the observation of absorption spectra. Published by the American Physical Society 2024

Real‐Time Detection of Coherent Vibrational Dynamics in TiN Films

AbstractTitanium nitride (TiN) has recently gained considerable interest because of its remarkable plasmonic properties and for its strong electron–phonon (e–ph) coupling, leading to extremely fast (<100 fs) electron‐lattice cooling. Here, the generation of coherent phonons in TiN films is reported, along with their real‐time detection by means of broadband transient reflection spectroscopy with sub‐15‐fs temporal resolution. The measurements show damped oscillations, superimposed to excited state electronic decay. A coherent vibrational mode is revealed, with ≈10 THz frequency ascribed to defect‐activated normal modes, consistent with spontaneous Raman scattering data, and a dephasing time of ≈250 fs. Two π‐phase flips are also observed located at photon energies corresponding to interband optical transitions (at 3.2 and 2.5 eV), ascribed to selective coupling of the vibrational mode to these transitions; the energy modulation induced by the vibrational coherence is evaluated. It is shown that the displacive excitation of coherent phonons model describes the coherent response in terms of temporal behavior and of spectral amplitude profile. Overall, a comprehensive and detailed analysis of coherent phonons in TiN films, so far undected, is provided and relevant information on TiN photo‐physical properties, potentially useful for its applications, is given.

Brain encoding of naturalistic, continuous, and unpredictable tactile events.

Studies employing EEG to measure somatosensory responses have been typically optimized to compute event-related potentials in response to discrete events (ERPs). However, tactile interactions involve continuous processing of non-stationary inputs that change in location, duration, and intensity. To fill this gap, this study aims to demonstrate the possibility of measuring the neural tracking of continuous and unpredictable tactile information. Twenty-seven young adults (females = 15) were continuously and passively stimulated with a random series of gentle brushes on single fingers of each hand, which were covered from view. Thus, tactile stimulations were unique for each participant, and stimulated fingers. An encoding model measured the degree of synchronization between brain activity and continuous tactile input, generating a temporal response function (TRF). Brain topographies associated with the encoding of each finger stimulation showed a contralateral response at central sensors starting at 50 ms and peaking at about 140 ms of lag, followed by a bilateral response at about 240 ms. A series of analyses highlighted that reliable tactile TRF emerged after just 3 minutes of stimulation. Strikingly, topographical patterns of the TRF allowed discriminating digit lateralization across hands and digit representation within each hand. Our results demonstrated for the first time the possibility of using EEG to measure the neural tracking of a naturalistic, continuous, and unpredictable stimulation in the somatosensory domain. Crucially, this approach allows the study of brain activity following individualized, idiosyncratic tactile events to the fingers.Significant Statement This study expands the current research conducted on neural tracking, opening the exploration of idiosyncratic tactile events and overcoming constraints of laboratory tasks that typically rely on discrete events. We validated a protocol for the ecological investigations of continuous, slow, tactile processing of the hands. The employed approach enriches the possible use of the EEG to characterize somatosensory neural representations of tactile events. Findings unravel coherent neural responses to continuous and naturalistic touch, with sensitivity for digit lateralization and representation.

Slow light in loop-coupled multimode optomechanical system

We theoretically propose a loop-coupled multimode optomechanical system (OMS) with a single-mode cavity, a two-level system (TLS), and a mechanical resonator, which are coupled to each other. With controlled coupling parameters, the loop-coupled multimode OMS can flexibly transform into different OMSs (e.g. cavity OMSs, cavity quantum electrodynamic systems). By simultaneously driving the single-mode cavity using pump and probe fields, we investigate the coherent optical response and transmission spectra for the transparent window and absorption dips. Additionally, the transparent window and absorption dips that induce coherent light propagation were demonstrated. Our findings demonstrate that the transparent window and absorption dips can generate slow (fast) light, and that the control of coupling parameters can modulate optical fields in different OMSs. With further weaving of these coupling parameters, the loop-coupled multimode OMS can be a quantum information processing platform for chip-scale applications.

(Digital Presentation) Cooperative Quantum Dynamics of Excitons in Colloidal Quantum Dots for Novel Optoelectronic Applications

Colloidal semiconductor quantum dots (QDs) are excellent materials for combining photonics and nanoscience. They have been extensively studied to understand the photophysics of quantum confined excitons and to develop efficient optoelectronic devices such as QD solar cells and light-emitting diodes. The photophysical processes of QD devices are governed by a large number of QDs constructing the devices. Therefore, cooperative quantum dynamics of QDs, i.e., synchronous responses of QD ensembles, have a great potential for boosting optoelectronic device performances.Before the use of cooperative quantum dynamics in QD devices, the understanding of quantum dynamics of excitons, i.e., coherent properties of multiexcitons, is required to draw out quantum cooperativity from QD ensembles. In order to elucidate coherent dynamics of multiexcitons during resonant laser-pulse excitation, we performed a quantum interference spectroscopy of QD responses. We found that multiexcitons generate the high-frequency coherent oscillations with integer multiples of the exciton resonance frequency, which is called harmonic quantum coherence, and that the coherent responses govern the microscopic processes in the resonant multiphoton absorption [1-3]. Furthermore, it was demonstrated that the coherent responses were detectable as photocurrent signals in thin films of QD ensembles [4]. These developments build up an essential base of quantum cooperativities emerging in optoelectronics.Here, we report recent investigations of cooperative quantum dynamics in QDs. In optoelectronic devices, electronic couplings between QDs are expected to generate a new type of quantum cooperativities. To generate electronic coupling, we fabricated closely packed PbS QDs by using a ligand exchange method. We found that nonlinear photocurrent signals are strongly enhanced in the QD solids. The comparison analysis of different ligands clarified that the enhancement ratio increases monotonically with the decrease of the inter-QD distance [5]. This means that the signal enhancement originates from the electronic coupling and cooperative behavior of QDs. These findings show that the cooperative quantum dynamics provide a new route to advanced optoelectronic technology such as nonlinear amplifiers.Part of this work was supported by JSPS KAKENHI (JP19H05465, JP22H01990, and JP23K17877), JST PRESTO (JPMJPR23H3), and JST CREST (JPMJCR21B4).

Mice integrate conspecific and contextual information in forming social episodic-like memories under spontaneous recognition task conditions

The ability to remember unique past events (episodic memory) may be an evolutionarily conserved function, with accumulating evidence of episodic-(like) memory processing in rodents. In humans, it likely contributes to successful complex social networking. Rodents, arguably the most used laboratory models, are also rather social animals. However, many behavioural paradigms are devoid of sociality, and commonly-used social spontaneous recognition tasks (SRTs) are open to non-episodic strategies based upon familiarity. We address this gap by developing new SRT variants. Here, in object-in-context SRTs, we asked if context could be specified by the presence/absence of either a conspecific (experiment 1) or an additional local object (experiment 2). We show that mice readily used the conspecific as contextual information to distinguish unique episodes in memory. In contrast, no coherent behavioural response emerged when an additional object was used as a potential context specifier. Further, in a new social conspecific-in-context SRT (experiment 3) where environment-based change was the context specifier, mice preferably explored a more recently-seen familiar conspecific associated with contextual mismatch, over a less recently-seen familiar conspecific presented in the same context. The results argue that, in incidental SRT conditions, mice readily incorporate conspecific cue information into episodic-like memory. Thus, the tasks offer different ways to assess and further understand the mechanisms at work in social episodic-like memory processing.

Aportes del pensamiento crítico latinoamericano contemporáneo para el abordaje de las migraciones internacionales como una problemática mundial de la actualidad

The article examines the significant contribution of contemporary Latin American critical thinking to the understanding of international migrations as a current global issue. It emphasizes the need to approach the migratory phenomenon in a transdisciplinary manner, while analyzing the marked disparities present in the world and the lack of coherent responses in a globally interconnected context driven more by the interests of capital than by human needs. The article highlights the importance of incorporating the perspective of the "other" in a comprehensive approach to migrations, emphasizing the crucial consideration of human rights as an integral component of migration policies. Furthermore, it posits the thesis that the current treatment and management of international migrations have failed, being approached from a securitist model and from the perspective of the nation-state, where preeminence lies in migration control and economic interests. Conversely, it emphasizes the need to address this complex issue from an integral perspective, within the framework of North-South asymmetrical relations, acknowledging that forced migration is one of the manifestations of a civilizational crisis that humanity is undergoing. This theoretical approach is made viable through the foundations of contemporary critical theory and Latin American philosophy, providing a contextualized perspective for understanding the complexity of migratory dynamics.

Incoherent phenomena in anisotropic periodic structures: from modeling to experimental demonstration.

The periodic structures are widely studied in numerous optical applications and there is a number of good tools for numerical modeling of such a structures (for example rigorous coupled-wave analysis, finite-difference time-domain, finite element method etc.). However, when it comes to the modeling of incoherent effects in many cases of practical interest, the current methods are not rigorous enough or depend on computationally demanding averaging of coherent response. In this paper, we present a novel approach to modeling of incoherent effects in structures with lateral periodicity based on scattering matrix formalism, as a way to describe optical response of a structure, and on application of incoherent wave summation in the form of infinite geometric series and generalized Mueller matrix calculus. This method can be combined with any of the existing coherent methods of modeling periodic structures and it offers significantly faster computational performance than partially coherent/incoherent methods based on averaging. It is compared with other methods for modeling of incoherent effects and also with experimental spectroscopic data. This method is then used to explain phenomena emerging from the complex interaction between diffraction grating and thick substrate.

Analisis Ketersediaan dan Kebutuhan Air Sub DAS Rupit Menggunakan Remote Sensing dan GIS

The water balance of a river basin is crucial for estimating water availability to meet current and future domestic and economic water demand and supply. Parameters such as rainfall, temperature, evapotranspiration, deficit, and surplus soil water content determine the water availability of a river basin (DAS), influenced by factors like land use, soil type, seasonal variations, and other environmental factors. This research aims to estimate the water balance of the Rupit sub-watershed using the FJ Mock model. The Sentinel 1 image of the area was processed to produce a land use map. GIS modeling generated maps of rainfall, land use, soil, slope, morphometry catchment, excess moisture, evapotranspiration, and surface run-off. The analysis reveals that the highest rainfall and evapotranspiration occur in January, while other months average around 56 - 66 mm per month. Excess water during the wet months (November-March) leads to flooding, damaging infrastructure such as residential buildings, roads, and bridges. Conversely, April-October experiences water shortages. The annual weighted watershed deficit is 46.6 mm, with almost no surplus detected. Rainfall run-off simulations demonstrate significant and coherent watershed responses to rainfall patterns. Due to low rainfall and soil moisture levels from preceding months, March exhibits the highest discharge at 15.35 m3/s, with a run-off coefficient of 0.863.

Everything you wanted to know about ChatGPT: Components, capabilities, applications, and opportunities

AbstractConversational Artificial Intelligence (AI) and Natural Language Processing have advanced significantly with the creation of a Generative Pre‐trained Transformer (ChatGPT) by OpenAI. ChatGPT uses deep learning techniques like transformer architecture and self‐attention mechanisms to replicate human speech and provide coherent and appropriate replies to the situation. The model mainly depends on the patterns discovered in the training data, which might result in incorrect or illogical conclusions. In the context of open‐domain chats, we investigate the components, capabilities constraints, and potential applications of ChatGPT along with future opportunities. We begin by describing the components of ChatGPT followed by a definition of chatbots. We present a new taxonomy to classify them. Our taxonomy includes rule‐based chatbots, retrieval‐based chatbots, generative chatbots, and hybrid chatbots. Next, we describe the capabilities and constraints of ChatGPT. Finally, we present potential applications of ChatGPT and future research opportunities. The results showed that ChatGPT, a transformer‐based chatbot model, utilizes encoders to produce coherent responses.

All-Oxide Metasurfaces Formed by Synchronized Local Ionic Gating.

Ionic gating of oxide thin films has emerged as a novel way of manipulating the properties of thin films. Most studies are carried out on single devices with a three-terminal configuration,but, by exploring the electrokinetics during the ionic gating, such a configuration with initially insulating films leads to a highly non-uniform gating response of individual devices within large arrays of the devices. It is shown that such an issue can be circumvented by the formation of a uniform charge potential by the use of a thin conducting underlayer. This synchronized local ionic gating allows for the simultaneous manipulation of the electrical, magnetic, and/or optical properties of large arrays of devices. Designer metasurfaces formed in this way from SrCoO2.5 thin films display an anomalous optical reflection of light that relies on the uniform and coherent response of all the devices. Beyond oxides, almost any material whose properties can be controlled by the addition or removal of ions via gating can form novel metasurfaces using this technique. These findings provide insights into the electrokinetics of ionic gating and a wide range of applications using synchronized local ionic gating.

Intent Recognition and slot filling for ecommerce chatbot

With the continuous evolution of natural language processing (NLP), conversational agents have become pivotal in enhancing user engagement and satisfaction in the e-commerce domain. This paper presents a comprehensive study and implementation of intent recognition and slot filling techniques tailored for an e-commerce chatbot. Leveraging a dataset of 8,000 samples, we employed a Convolutional Neural Network (CNN) combined with Long Short-Term Memory (LSTM) networks for intent recognition, achieving an accuracy of 87%. For slot filling, we utilized the Bidirectional Encoder Representations from Transformers (BERT) model, also attaining an accuracy of 87%. The chatbot seamlessly integrates with an e-commerce database, using OpenAI's GPT-3 to generate natural language responses from query results. Our system demonstrates significant advancements in processing user queries, generating precise database queries, and providing coherent and relevant responses, thereby enhancing the overall user experience. This work aims to equip researchers and practitioners with insights into the methodologies and challenges in developing sophisticated e-commerce chatbots, fostering further innovation in this field. Key Words: Intent Recognition, Slot Filling, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional Encoder Representations from Transformers (BERT), GPT-3, Natural Language Understanding (NLU), Chatbot

Microheterogeneity in the Kinetics and Sex-Specific Response to Type I IFN.

The response to type I IFNs involves the rapid induction of prototypical IFN signature genes (ISGs). It is not known whether the tightly controlled ISG expression observed at the cell population level correctly represents the coherent responses of individual cells or whether it masks some heterogeneity in gene modules and/or responding cells. We performed a time-resolved single-cell analysis of the first 3 h after invivo IFN stimulation in macrophages and CD4+ T and B lymphocytes from mice. All ISGs were generally induced in concert, with no clear cluster of faster- or slower-responding ISGs. Response kinetics differed between cell types: mostly homogeneous for macrophages, but with far more kinetic diversity among B and T lymphocytes, which included a distinct subset of nonresponsive cells. Velocity analysis confirmed the differences between macrophages in which the response progressed throughout the full 3 h, versus B and T lymphocytes in which it was rapidly curtailed by negative feedback and revealed differences in transcription rates between the lineages. In all cell types, female cells responded faster than their male counterparts. The ISG response thus seems to proceed as a homogeneous gene block, but with kinetics that vary between immune cell types and with sex differences that might underlie differential outcomes of viral infections.

Multiple optomechanically induced transparency generated slow light in an array of optomechanical system

We present an array of optomechanical systems which consist of an optical cavity and three nanomechanical resonators. Introducing Jaynes-Cumming (J-C) coupling in the nearest neighbor resonator allows for the formation of optomechanical systems with arrays of N nanomechanical resonators. Using a strong pump field and a weak probe field to drive the optical cavity simultaneously, we investigated the coherent optical response and the probe transmission spectrum manifested as multiple optomechanically induced transparency. We illustrate the impact of probe-cavity detuning, J-C coupling strength, and the number of nanomechanical resonators on the transparent window. In particular, we analyze nanomechanical resonators and find that increasing their number results in multiple transparent windows and slow light at different frequencies. We also find that the slow light effect can be enhanced by increasing the number of nanomechanical resonators with odd numbers at resonance. These findings imply that the arrays of optomechanical system can be used for multichannel optical communications and multichannel quantum information processing.

Ultrafast Raman thermometry in driven YBa2Cu3O6.48

Signatures of photoinduced superconductivity have been reported in cuprate materials subjected to a coherent phonon drive. A “cold” superfluid was extracted from the transient Terahertz conductivity and was seen to coexist with “hot” uncondensed quasiparticles, a hallmark of a driven-dissipative system of which the interplay between coherent and incoherent responses is not well understood. Here, time resolved spontaneous Raman scattering was used to probe the lattice temperature in the photoinduced superconducting state of YBa2Cu3O6.48. An increase in lattice temperature of up to 140 K was observed by measuring the time dependent Raman scattering intensity of an undriven “spectator” phonon mode. This value is consistent with the estimated increase in quasiparticle temperature measured under the same excitation conditions. These temperature changes provide quantitative information on the nature of the driven state and its decay, and may suggest a strategy to optimize this effect. Published by the American Physical Society 2024

Systemic cellular migration: The forces driving the directed locomotion movement of cells.

Directional motility is an essential property of cells. Despite its enormous relevance in many fundamental physiological and pathological processes, how cells control their locomotion movements remains an unresolved question. Here, we have addressed the systemic processes driving the directed locomotion of cells. Specifically, we have performed an exhaustive study analyzing the trajectories of 700 individual cells belonging to three different species (Amoeba proteus, Metamoeba leningradensis, and Amoeba borokensis) in four different scenarios: in absence of stimuli, under an electric field (galvanotaxis), in a chemotactic gradient (chemotaxis), and under simultaneous galvanotactic and chemotactic stimuli. All movements were analyzed using advanced quantitative tools. The results show that the trajectories are mainly characterized by coherent integrative responses that operate at the global cellular scale. These systemic migratory movements depend on the cooperative nonlinear interaction of most, if not all, molecular components of cells.