Invisible Objects Research Articles

Registered Report Stage II: Decoding the category information from evoked potentials to visible and invisible visual objects

Previous studies that use decoding methods and EEG to investigate the neural representation of the category information of visual objects focused mainly on consciously processed visual objects. It remains unclear whether the category information of unconsciously processed visual objects can be decoded and whether the decoding performance is different for consciously and unconsciously processed visual objects. The present study compared the neural decoding of the animacy category of visible and invisible visual objects via EEG and decoding methods. The results revealed that the animacy of visible visual objects could be decoded above the chance level by the P200, N300, and N400, but not by the early N/P100. However, the animacy of invisible visual objects could not be decoded above the chance level by neither early nor late ERP components. The decoding accuracy was greater for visible visual objects than that for invisible visual objects for the P200, N300 and N400. These results suggested that access to animacy category information for visual objects requires conscious processing.

Two dynamically discovered compact object candidate binary systems from LAMOST low-resolution survey

ABSTRACT We report two binary systems, LAMOST J035540 + 381550 (hereafter J035540) and LAMOST J035916 + 400732 (hereafter J035916), identified through the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-resolution survey (LRS). Each of these two systems contains an M-type star orbiting with a invisible compact object candidate. Follow-up spectroscopic observations of Palomar 200-in. telescope (P200) enhance radial velocity measurements. We use radial velocities from LAMOST and P200, as well as light curves from Zwicky Transient Facility (ZTF) to constrain orbital parameters. The masses of the visible M-type stars are estimated by fitting the MIST isochrones and spectral energy distributions. The mass functions for the unseen companions are: $0.22\pm 0.01\,{\rm M}_{\odot }$ for J035540 and $0.16\pm 0.01\, {\rm M}_{\odot }$ for J035916. With the orbital and stellar parameters derived above and assuming the orbital inclination is 90° (edge-on), we find that the minimum masses of the invisible companions exceeds that of the visible stars. The single-lined feature and the dynamical evidence suggest the presence of compact objects. J035540’s ZTF light curve, modelled with phoebe, yields a compact object mass of $0.70^{+0.12}_{-0.05}\, {\rm M}_{\odot }$. For J035916, ellipsoidal modulation analysis constrains the light-curve amplitude, yielding a compact object mass range of $0.57-0.90\, {\rm M}_{\odot }$. The mass estimates indicate that both are likely white dwarfs. These findings underscore the efficiency of optical time-domain surveys and dynamical methods in identifying faint, massive white dwarfs, along with other compact objects in binaries.

What’s in it? – schoolbags in the lives of pupils and classrooms

ABSTRACT The overarching aim of the present study is to investigate such an invisible object; namely, schoolbags and how their contents function in the lives of pupils between the privacy of the home and the societal world of schools. A sociomaterial approach is used to understand schoolbags as objects that enable certain actions and norms. The uniqueness of the study calls for a more basic approach on the analytical level, carefully investigating and describing the content of the schoolbags as well as their context seeing them as frozen moments of processes. The data material consists of photographs depicting contents of 16 German satchels, which were analysed alongside a description of exterior appearances of schoolbags and the material context of the classroom. The findings show that the function of the schoolbags exceeds their obvious transportation purposes, and that they are complex, entangled objects in the construction of “schooling” and “the pupil”.

Gravity is a Reproduced Substance Invisible Objects Arise from the Influence of Cosmic Bodies on Each Other

The sun is so vast that its invisible extension reaches the Earth and the rest of the planets, so that it overlaps with the invisible extension of the Earth, so that the two become one body, and both of them, i.e. the star and the planets, pull the other through their rotation through the invisible matter. The energy particles inherent in the quantum vacuum are affected by the same rhythm, such as the electrons inside the aforementioned wire, and thus extend for a long time in front of the sun, for example, the energies in front of it and behind it.

Visions of invisibility in optics: retrospective.

Invisibility was long thought to be exclusively the domain of science fiction and fantasy authors, but in recent years it has been the subject of extensive theoretical and experimental research. In this retrospective we look back on the evolution of invisibility in science, from the earliest hints of invisible objects in the late 19th century up to the modern concepts of cloaking, and some of the connections between them.

Oriental pied hornbills (Anthracoceros albirostris) solve invisible displacement tasks in a test of Piagetian object permanence.

Object permanence, the ability to mentally represent objects even when they are not directly accessible to the senses, is of vital importance for the survival of both human and non-human animals. The Oriental pied hornbill (Anthracoceros albirostris) is an Asian species of hornbill displaying remarkable adaptability in various environments, yet little is known about their cognitive abilities. Their breeding behaviour is unique, as the female hornbill seals herself inside a cavity before laying eggs and the male feeds her and their offspring without visual contact, strongly suggesting the presence of object permanence to some degree. In this study, six Oriental pied hornbills underwent testing for object permanence, including a series of seven standard Piagetian tasks involving visible and invisible displacements. The subjects consistently demonstrated spontaneous object permanence in all stages leading up to the invisible displacement stage. Half of the subjects achieved full stage 6 double invisible displacement Piagetian object permanence, while the other half reached stage 5 double visible displacement. Breeding behaviour and the duration of developmental stages are proposed as potential factors influencing object permanence ability in this species of hornbill.

Supramassive compact objects with neutron star and dark matter origin in the mass gap region

To this day, the nature of dark matter (DM) remains elusive despite all our efforts. This type of matter has not been directly observed, so we infer its gravitational effect. Since galaxies and supermassive objects like these are most likely to contain DM, we assume that dense objects such as neutron stars (NSs) are also likely to host DM. The NS is considered the best natural laboratory for testing theories and collecting observational data. We mainly focus on two types of DM particles, fermions and bosons, with a mass range of [0.01–1.5] GeV and repulsive interactions of about [10−4–10−1]MeV −1. Using a two-fluid model to solve the TOV equations, we find stable configurations that span hundreds of kilometers and weigh tens or even hundreds of solar masses. To visualize results, we propose the existence of a giant invisible compact DM object and the NS in the center as the core, the only visible part. Stability criteria are met for these configurations, so collapsing into a black hole is unlikely. We go further and use this work for smaller formations that exist inside the mysterious Mass Gap. We also find stable configurations of 3–4 solar masses, with NS-DM mixing capable of describing the mass gap. Regardless, the present theoretical prediction, if combined with corresponding observations, could shed light on the existence of DM and even more on its fundamental properties.

Dark Comets: Mysterious Visitors from the Unknown Deep Space

Dark comets are a serious hazard to Earth, as they could collide with Earth without warning. Thousands of these unseen comets are currently traveling near Erath. Only a few of them are identified. They are hard to detect due to their nearly invisible nature. This paper gives a concise overview of the dark comets and the risks associated with such celestial invisible objects. Additionally, we try to highlight the modern technology tools to identify and detect dark comets.

Un-settling the frontiers of food waste in the Netherlands: infrastructural stories of food waste transformation in the Hague

Transformation opens possibilities to imagine and learn other forms of being and living together; it implies change, and often exchange. This paper visibilises the infrastructural stories involved in the transformation of food waste into edible food. Conceptually, we assume there is no univocal definition of food waste. Methodologically, we resist the practice of extracting and appropriating the life (hi)stories of the people involved in these transformative initiatives who are often described as vulnerable “others.” Instead, the project highlights the stories of the infrastructures underpinning these transformative experiences. The objective is to unsettle the frontier of what counts as food waste by paying attention to the objects involved in the process of transforming it into edible food. The paper starts by positioning ourselves in the literature regarding food waste governance and infrastructural labor as transformative possibilities that support the development of personal sustainability strategies and grassroots food governance. In the second section we explain our methodological considerations to focus on the infrastructures that mediate the transformation of disposed food into edible food in The Hague. The third section presents the results and discusses the stories of two objects, a cargo bike (bakfiets) and a fridge (koelkast). We suggest these objects serve to unsettle governance practices and narratives related to food waste in the city. Paying attention to these objects’ stories is an important turn in personal sustainability research because it enables us to see that the individual is never alone, always acting with the support of often invisible objects that in this study make possible the reduction and transformation of wasted food. This serves as inspiration to imagine alternative paths for food waste governance and foster forms of collective engagement, urgently needed given the increasing precariousness of food systems and relations.

The “Cartographic Impulse” and Its Epistemic Gains in the Process of Iteratively Mapping M87’s Black Hole

After the Event Horizon Telescope Collaboration released in April 2019 the first empirical images of a black hole, an astrophysical object previously thought “unseeable,” much of the public discourse has approached these images as straightforward visual depictions of a black hole. This article challenges this view by showing that the first images of a black hole went beyond merely making an invisible cosmic object visible and that the images published in April 2019 were just the first in a series of black hole images the researchers continue producing. Drawing primarily on Sybille Krämer’s concept of the cartographic impulse, the article demonstrates that the Event Horizon Telescope images are, first and foremost, epistemic tools. These epistemic tools enable researchers to actively explore various physical aspects and dynamic properties of a black hole’s immediate environment and test theoretical predictions about it, thus making this elusive environment empirically knowable. To demonstrate this, the article analyses the mapping operations that combined automated algorithmic procedures with expert human judgment and through which these images were produced, read, and interpreted. It also examines how the different Event Horizon Telescope images relate to one another, which particular epistemic functions they fulfil in the research context, under which conditions, and with which limitations, thus tracing how these images facilitate the production of new scientific knowledge about black holes.

On the Possibilities of Constructing Theoretical Models of Invisible Objects Using the Eikonal Equation

On the Possibilities of Constructing Theoretical Models of Invisible Objects Using the Eikonal Equation

Passing the systems among levels of quantum reality

The visible reality at a given moment is a result of the modification of the quantum states of the observables of some systems from another level of quantum reality. The projection towards the new reality is done by collapsing some states described by simple wave functions or resulting from quantum superpositions. Collapses are also achieved through measurements of observables, influencing quantum phenomena, bringing some phenomena to another level of reality. These can pass from a higher level of quantum reality to another level, effectively measuring certain observables, but also through discoveries, studies, identifying the dynamics of the supply-demand balance from the "cloud" of the market's equilibrium points, the realization of new products or services, etc. That is, the still invisible objects will become visible by extracting them from the original quantum reality with the help of projectors, through collapses. The quantum state of the systems also changes through decoherence, through the interaction with the surrounding environment. In the following, some directions are suggested for the development of models for unitary treatment of objects from different levels of reality.

Dynamic Redirection for VR Haptics with a Handheld Stick.

This paper proposes a general handheld stick haptic redirection method that allows the user to experience complex shapes with haptic feedback through both tapping and extended contact, such as in contour tracing. As the user extends the stick to make contact with a virtual object, the contact point with the virtual object and the targeted contact point with the physical object are continually updated, and the virtual stick is redirected to synchronize the virtual and real contacts. Redirection is applied either just to the virtual stick, or to both the virtual stick and hand. A user study (N = 26) confirms the effectiveness of the proposed redirection method. A first experiment following a two-interval forced-choice design reveals that the offset detection thresholds are [-15cm, +15cm]. A second experiment asks participants to guess the shape of an invisible virtual object by tapping it and by tracing its contour with the handheld stick, using a real world disk as a source of passive haptic feedback. The experiment reveals that using our haptic redirection method participants can identify the invisible object with 78% accuracy.

Seeing and telling the invisible: problems of a new epistemic category in the second half of the eighteenth century

ABSTRACT The invisible object, in the eighteenth century, is not an evidence. It is the result of textual and semantic learning. Which concrete strategies are used to construct and depict objects out of sight? How do we make them a cognitive reality acceptable to a scientific community? This paper first highlights the conditions for the emergence of a field of microscopic knowledge and its epistemological consequences. Then we consider the microscopic gaze in terms of learning, situated between the act of observation as such and discursive practices. We conclude by studying a concrete case of “negotiation of the invisible” in a correspondence between Carl Linnaeus and John Ellis concerning corpuscles observed in mushroom infusions.

IVF-Net: An Infrared and Visible Data Fusion Deep Network for Traffic Object Enhancement in Intelligent Transportation Systems

Infrared and visible data fusion (IVF) aims to generate a fused output that simultaneously highlights salient thermal radiation features and preserves texture information, which can not only grasp the necessary information for traffic movement, but also highlight the invisible objects that need to be dodged in intelligent transportation system (ITS). Therefore, IVF is capable of improving the environmental perception ability for various challenging traffic situations, e.g., foggy scenarios, rainy environments, and low-light illumination. However, current available IVF algorithms cannot offer a theoretical manner to integrate a priori knowledge and the network structure into a unified model. Moreover, they always fail to handle infrared and visible data pairs with different resolutions, which is a common occurrence in real ITS scenarios. To this end, this study develops a novel model-inspired unsupervised network termed IVF-Net. Specifically, an enhanced IVF model (IVFM), which pays more attention on detailed texture information and salient objects, is first established. According to proximal gradient theory, then we map this model into a deep network with learnable feature extraction parameters, aiming to draw on the strengths of the fusion model and deep learning to better describe the IVF task. Finally, a multiple task-driven loss function is designed to train the mapped network. Unlike previous work, our IVF-Net is motivated by IVFM, each layer in which has a semantic interpretability and a clear mission, thereby leading to a significantly enhanced fusion effect. Another advantage is that it is only composed of simple convolution-based structures, which ensures its lightweight and efficiency. Experiments demonstrate that IVF-Net can have a stronger ability to capture the key traffic information and highlight the salient feature of imperceptible objects, which makes it an excellent candidate to improve the reliability of subsequent applications in ITS.

Discovery of One Neutron Star Candidate from Radial-velocity Monitoring

We report the discovery of one possible neutron star binary (P orb = 0.8666 days) by using LAMOST low-resolution spectroscopic data. The visible companion is a late A-type dwarf (T eff = 7900 ± 200 K; logg = 4.3 ± 0.2; M = 1.7 ± 0.1 M ⊙; R = 1.7 ± 0.2 R ⊙) at a distance of 1.11 ± 0.03 kpc. No double-lined feature can be seen from the Gran Telescopio Canarias/HORuS high-resolution spectra; thus the radial-velocity variation indicates an invisible object hiding in the binary. The system’s optical light curves show clear ellipsoidal variability, suggesting that the visible companion is tidal distorted. By fitting the multiband light curves with the eclipsing light-curve (ELC) code and the Wilson–Devinney (WD) code, we constrain the mass of the invisible star to be 1.1–1.3 M ⊙. Spectral disentangling shows no additional component with optical absorption spectra, supporting the idea that the system contains one compact object. No X-ray or UV emission is detected in the ROSAT archive observations. Therefore, we suspect the invisible object is more likely a neutron star rather than a white dwarf. Our finding suggests the ability of LAMOST spectroscopic survey to discover X-ray-quiescent compact objects.

A Multi-AUV Maritime Target Search Method for Moving and Invisible Objects Based on Multi-Agent Deep Reinforcement Learning.

Target search for moving and invisible objects has always been considered a challenge, as the floating objects drift with the flows. This study focuses on target search by multiple autonomous underwater vehicles (AUV) and investigates a multi-agent target search method (MATSMI) for moving and invisible objects. In the MATSMI algorithm, based on the multi-agent deep deterministic policy gradient (MADDPG) method, we add spatial and temporal information to the reinforcement learning state and set up specialized rewards in conjunction with a maritime target search scenario. Additionally, we construct a simulation environment to simulate a multi-AUV search for the floating object. The simulation results show that the MATSMI method has about 20% higher search success rate and about 70 steps shorter search time than the traditional search method. In addition, the MATSMI method converges faster than the MADDPG method. This paper provides a novel and effective method for solving the maritime target search problem.

HDRNet: High‐Dimensional Regression Network for Point Cloud Registration

AbstractAbstract‐3D point cloud registration is a crucial topic in the reverse engineering, computer vision and robotics fields. The core of this problem is to estimate a transformation matrix for aligning the source point cloud with a target point cloud. Several learning‐based methods have achieved a high performance. However, they are challenged with both partial overlap point clouds and multiscale point clouds, since they use the singular value decomposition (SVD) to find the rotation matrix without fully considering the scale information. Furthermore, previous networks cannot effectively handle the point clouds having large initial rotation angles, which is a common practical case. To address these problems, this paper presents a learning‐based point cloud registration network, namely HDRNet, which consists of four stages: local feature extraction, correspondence matrix estimation, feature embedding and fusion and parametric regression. HDRNet is robust to noise and large rotation angles, and can effectively handle the partial overlap and multi‐scale point clouds registration. The proposed model is trained on the ModelNet40 dataset, and compared with ICP, SICP, FGR and recent learning‐based methods (PCRNet, IDAM, RGMNet and GMCNet) under several settings, including its performance on moving to invisible objects, with higher success rates. To verify the effectiveness and generality of our model, we also further tested our model on the Stanford 3D scanning repository.

Optical spatial filtering with plasmonic directional image sensors.

Photonics provides a promising approach for image processing by spatial filtering, with the advantage of faster speeds and lower power consumption compared to electronic digital solutions. However, traditional optical spatial filters suffer from bulky form factors that limit their portability. Here we present a new approach based on pixel arrays of plasmonic directional image sensors, designed to selectively detect light incident along a small, geometrically tunable set of directions. The resulting imaging systems can function as optical spatial filters without any external filtering elements, leading to extreme size miniaturization. Furthermore, they offer the distinct capability to perform multiple filtering operations at the same time, through the use of sensor arrays partitioned into blocks of adjacent pixels with different angular responses. To establish the image processing capabilities of these devices, we present a rigorous theoretical model of their filter transfer function under both coherent and incoherent illumination. Next, we use the measured angle-resolved responsivity of prototype devices to demonstrate two examples of relevant functionalities: (1) the visualization of otherwise invisible phase objects and (2) spatial differentiation with incoherent light. These results are significant for a multitude of imaging applications ranging from microscopy in biomedicine to object recognition for computer vision.

The Secret Life of Energy in Refugee Camps: Invisible Objects, Technologies, and Energy Systems in Humanitarianism

AbstractWithin humanitarian systems and refugee spaces, energy technologies are often invisible and unrecognized. Beyond basic UN and emergency interventions to supply solar lanterns, lie vibrant systems of connection underpinning refugee electricity and cooking access: a world of energy needs and provision exist within refugee camps in East Africa. The article frames energy within forced migration debates on technology: contributing to the social anthropology and migration studies literature by exploring the material culture of energy in humanitarian contexts. The article argues that some forms of energy are highly visible—for example, solar lanterns and cookstoves—while others remain invisible. Certain objects are in danger of becoming fetishized by the humanitarian system while others are neglected and ignored. Analysis for this article reveals the invisibility of energy as a marginalized topic, highlights the methodological challenges of revealing the energy needs of displaced people, and explores institutional ignorance on the importance of energy.