Optimal topology control for grounding protection sensor networks in shipboard electrical systems.

Intelligent monitoring of environmental information in ships is an important prerequisite for reducing and avoiding accidents and is of great importance for safety at sea. The use of a ship environmental monitoring system based on wireless sensor networks has the unique advantages of low cost, stability, and reliability, allowing real-time monitoring of many environmental factors in ships. This article proposes an optimal topology control to maximize collected data satisfaction and reduce energy consumption and transmission latency. First, the cluster head selection method is obtained by initializing the wireless sensor network with a fuzzy clustering algorithm, then the amount of collection data is obtained by a sub-gradient descent algorithm, and a sensor association scheme based on ant colony optimization is proposed to solve the knapsack problem. Finally, simulation results show that the proposed algorithm in this article can effectively reduce the energy consumption and transmission delay of the wireless sensor network while ensuring the monitoring of the grounding protection in the electrical system of the offshore ship.

Ground by Status.

What is the explanatory role of 'status-truths' such as essence-truths, necessity-truths and law-truths? A plausible principle, suggested by various authors, is Ground by Status, according to which status truths ground their prejacents. For instance, if it is essential to a that p, then this grounds the fact that p. But Ground by Status faces a forceful objection: it is inconsistent with widely accepted principles regarding the logic of grounding (Glazier in Philos Stud 174(11):2871-2889, 2017a, Synthese 174(198):1409-1424, 2017b; Kappes in Synthese 199(1-2):2575-2595, 2020, Philos Stud 178(4):1267-1284, 2021). I defend Ground by Status against this objection.

A framework for risk matrix design: A case of MASS navigation risk.

Risk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework for developing a risk matrix based on fuzzy Analytic Hierarchy Process (AHP) is proposed. In this framework, a linear function is defined where the risk index is treated as a response variable, while the probability and consequence indices are explanatory variables, with weights of these two indices representing their importance on given risk level. This significance is assessed by experts and quantified using AHP in interval type 2 fuzzy environment. A continuous risk diagram is then created and converted into a risk matrix that can be improved. To verify the feasibility of the proposed framework, a risk matrix is designed in the context of MASS grounding. The results show that the proposed approach is feasible. Our discussion results can provide new insights for the design of risk matrices and promote the management of MASS navigational risks.

Aristotelian universals, strong immanence, and construction.

The Aristotelian view of universals, according to which each universal generically depends for its existence on its instantiations, has recently come under attack by a series of ground-theoretic arguments. The last such arguments, presented by Raven, promises to offer several significant improvements over its predecessors, such as avoiding commitment to the transitivity of ground and offering new reasons for the metaphysical priority of universals over their instantiations. In this paper, we argue that Raven's argument does not effectively avoid said commitment and that Raven's new reasons fail. Moreover, we present a novel ground-theoretic interpretation of the Aristotelian view, referred to as strong immanence, and introduce a new argument against the Aristotelian view, intended to sidestep any commitment to the transitivity of ground.

Review on Soil Corrosion and Protection of Grounding Grids.

The corrosion of grounding grid materials in soil is a prominent factor in power and electrical equipment failure. This paper aims to delve into the corrosion characteristics of grounding grid materials and the corresponding methods of safeguarding against this phenomenon. Firstly, the influencing factors of the soil environment on the corrosion of the grounding grid are introduced, including soil physicochemical properties, microorganisms, and stray currents. Then, the corrosion behavior and durability of common grounding grid materials such as copper, carbon steel, and galvanized steel are discussed in detail and compared comprehensively. In addition, commonly used protective measures in China and outside China, including anti-corrosion coatings, electrochemical protection, and other technologies are introduced. Finally, it summarizes the current research progress and potential future directions of this field of study.

Grounding spatial relations in text-only language models.

This paper shows that text-only Language Models (LM) can learn to ground spatial relations like left of or below if they are provided with explicit location information of objects and they are properly trained to leverage those locations. We perform experiments on a verbalized version of the Visual Spatial Reasoning (VSR) dataset, where images are coupled with textual statements which contain real or fake spatial relations between two objects of the image. We verbalize the images using an off-the-shelf object detector, adding location tokens to every object label to represent their bounding boxes in textual form. Given the small size of VSR, we do not observe any improvement when using locations, but pretraining the LM over a synthetic dataset automatically derived by us improves results significantly when using location tokens. We thus show that locations allow LMs to ground spatial relations, with our text-only LMs outperforming Vision-and-Language Models and setting the new state-of-the-art for the VSR dataset. Our analysis show that our text-only LMs can generalize beyond the relations seen in the synthetic dataset to some extent, learning also more useful information than that encoded in the spatial rules we used to create the synthetic dataset itself.

Language with vision: A study on grounded word and sentence embeddings.

Grounding language in vision is an active field of research seeking to construct cognitively plausible word and sentence representations by incorporating perceptual knowledge from vision into text-based representations. Despite many attempts at language grounding, achieving an optimal equilibrium between textual representations of the language and our embodied experiences remains an open field. Some common concerns are the following. Is visual grounding advantageous for abstract words, or is its effectiveness restricted to concrete words? What is the optimal way of bridging the gap between text and vision? To what extent is perceptual knowledge from images advantageous for acquiring high-quality embeddings? Leveraging the current advances in machine learning and natural language processing, the present study addresses these questions by proposing a simple yet very effective computational grounding model for pre-trained word embeddings. Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora. By applying a learned alignment, we are able to indirectly ground unseen words including abstract words. A series of evaluations on a range of behavioral datasets shows that visual grounding is beneficial not only for concrete words but also for abstract words, lending support to the indirect theory of abstract concepts. Moreover, our approach offers advantages for contextualized embeddings, such as those generated by BERT (Devlin et al, 2018), but only when trained on corpora of modest, cognitively plausible sizes. Code and grounded embeddings for English are available at ( https://github.com/Hazel1994/Visually_Grounded_Word_Embeddings_2 ).

An Eco-evolutionary Model on Surviving Lysogeny Through Grounding and Accumulation of Prophages.

Temperate phages integrate into the bacterial genomes propagating along with the bacterial genomes. Multiple phage elements, representing diverse prophages, are present in most bacterial genomes. The evolutionary events and the ecological dynamics underlying the accumulation of prophage elements in bacterial genomes have yet to be understood. Here, we show that the local wastewater had 7% of lysogens (hosting mitomycin C-inducible prophages), and they showed resistance to superinfection by their corresponding lysates. Genomic analysis of four lysogens and four non-lysogens revealed the presence of multiple prophages (belonging to Myoviridae and Siphoviridae) in both lysogens and non-lysogens. For large-scale comparison, 2180 Escherichia coli genomes isolated from various sources across the globe and 523 genomes specifically isolated from diverse wastewaters were analyzed. A total of 15,279 prophages were predicted among 2180 E. coli genomes and 2802 prophages among 523 global wastewater isolates, with a mean of ~ 5 prophages per genome. These observations indicate that most putative prophages are relics of past bacteria-phage conflicts; they are "grounded" prophages that cannot excise from the bacterial genome. Prophage distribution analysis based on the sequence homology suggested the random distribution of E. coli prophages within and between E. coli clades. The independent occurrence pattern of these prophages indicates extensive horizontal transfers across the genomes. We modeled the eco-evolutionary dynamics to reconstruct the events that could have resulted in the prophage accumulation accounting for infection, superinfection immunity, and grounding. In bacteria-phage conflicts, the bacteria win by grounding the prophage, which could confer superinfection immunity.

Trauma-Informed Care in Medical Imaging and Radiation Therapy to Reduce Retraumatization.

PURPOSE: To provide an overview of trauma-informed care, including the neurobiology of trauma, interventions to reduce retraumatizing patients who have experienced trauma, and implications of trauma-informed care in medical imaging and radiation therapy. METHODS: A comprehensive search of electronic databases related to the purpose of this project resulted in the collection of 12 peer-reviewed journal articles. Two conference papers, 1 behavioral science textbook, 1 trauma neurobiology textbook, 1 professional conference presentation, and 1 governmental report also were reviewed to complement the journal articles. A thematic analysis was performed to identify commonalities among the selected sources. RESULTS: Four themes identified in the literature included definitions of trauma-informed care, neurobiology of trauma, pillars of trauma-informed care for intervention, and implications in medical imaging and radiation therapy. DISCUSSION: A trauma-informed health care professional realizes the prevalence of trauma, recognizes the signs and symptoms of trauma, responds by integrating knowledge about trauma into practice, and actively resists retraumatizing the patient (ie, avoids creating an environment that inadvertently reminds patients of their traumatic experiences and causes them to experience emotional and biological stress). The pillars of trauma-informed care include safety, trustworthiness or transparency, peer support, collaboration, empowerment, and responsiveness or cultural considerations. Delivery of health care often involves assessment and interventions in locations on the patient's body where trauma has previously occurred, increasing the probability of retraumatization and manifestation of signs and symptoms of trauma. Radiologic technologists and radiation therapists should be trauma-informed when they are interacting with and caring for patients to reduce retraumatization. A hypothetical case study also is presented to show how radiologic technologists can use the pillars of trauma-informed care in the clinic. CONCLUSION: Because many aspects of care, including routine care in medical imaging and radiation therapy, can be an unintentional reminder of a traumatic experience, health care professionals should be trauma-informed when they are interacting with and caring for patients.

Transmission Line Voltage Measurement Utilizing a Calibrated Suspension Grounding Voltage Sensor.

The accurate voltage measurement of distribution networks is of great significance in power dispatching and fault diagnosis. Voltage sensors based on the spatial electric field effect do not require grounding, which provides the possibility for the distributed measurement of transmission line voltages. However, the divider ratio of suspension grounding voltage sensors is affected by the height between the sensor and the ground, as well as the distance between the sensor and the telegraph pole. In this paper, a self-calibration method based on internal capacitance transformation is proposed to realize the on-line calibration of suspension grounding voltage sensors. The calibration is accomplished by switching different parameters in the conditioning circuit, and the calibration process does not require power failure or known input excitation. In addition, the impact of electric fields in the other two phases of three-phase transmission lines on measurement through simulation research is quantified in this paper. In order to reduce the impact of interference electric fields, an equipotential shielding structure is designed. The circuit topology and probe prototype have been developed and testing has been conducted in laboratory conditions; the experimental results show that the maximum relative error of voltage amplitude is 1.65%, and the phase relative error is 0.94%. The measurement accuracy is not limited by the height to ground or the distance to the telegraph pole. In addition, in the application of an equipotential shielding probe, the maximum deviation of measured voltage is 0.7% with and without interference electric fields.

Simulation and Experimentation of a Grounding Network Detection Scheme Based on a Low-Frequency Electromagnetic Method.

The grounding network is a significant component of substations, and the corrosion of its ground resistance is predominantly detected using the electromagnetic method. However, the application of electromagnetic methods for detecting corrosion within earthing networks has received relatively limited attention in research. Currently, the prevailing method utilizes electromagnetic techniques to identify the breakage points within the given earthing network. In this study, we propose a corrosion detection method for grounding networks based on the low-frequency electromagnetic method, which measures the resistance value between individual nodes of the network. Specifically, an excitation source signal of a predetermined frequency was transmitted to the measurement segment of the grounding network, which facilitated the direct measurement of the strength of the induced magnetic field above the center of the measuring conductor. The recorded electromagnetic data were subsequently uploaded to the host computer for data processing, and the computer interface was constructed based on a LABVIEW design. By leveraging the relationship between the induced electric potential, current strength, excitation source strength, and additional voltage detection devices, the resistance of the conductor under examination could be determined. Furthermore, the proposed method was tested under suitable conditions, and it demonstrated favorable results. Thus, the proposed method can serve as a foundation for developing electromagnetic testing instruments tailored to the investigated grounding network.

Learning to reason over scene graphs: a case study of finetuning GPT-2 into a robot language model for grounded task planning.

Long-horizon task planning is essential for the development of intelligent assistive and service robots. In this work, we investigate the applicability of a smaller class of large language models (LLMs), specifically GPT-2, in robotic task planning by learning to decompose tasks into subgoal specifications for a planner to execute sequentially. Our method grounds the input of the LLM on the domain that is represented as a scene graph, enabling it to translate human requests into executable robot plans, thereby learning to reason over long-horizon tasks, as encountered in the ALFRED benchmark. We compare our approach with classical planning and baseline methods to examine the applicability and generalizability of LLM-based planners. Our findings suggest that the knowledge stored in an LLM can be effectively grounded to perform long-horizon task planning, demonstrating the promising potential for the future application of neuro-symbolic planning methods in robotics.

Research on Channel Characteristics and Electrode Electrical Performance of Earth Current Field Information Transmission Technology.

Starting from the need for emergency rescue information transmission in tunnel engineering accidents, this article focuses on researching and solving the technical problems of information transmission between rescue personnel and trapped personnel after tunnel engineering collapse accidents, before and during the rescue process. The research objects are the information transmission channel and grounding electrode in the earth current field information transmission technology, and the electromagnetic characteristics of the earth medium and the electrical performance of the grounding electrode are studied and analyzed using the electromagnetic simulation software Maxwell based on finite element algorithm, establish a three-dimensional model based on the transmission of current field information of the ground electrode, analyze the effects of the electrode array, electrode depth, and radius on impedance. Research has shown that the impedance of the earth is related to the resistivity of the medium and is not a human-controllable factor. To reduce the contact impedance of an electric dipole antenna, one should start with the contact impedance of the earth electrode. The impedance of the transmitting end is an important factor affecting the efficiency of information transmission; parallel connection of multiple grounding electrodes, increasing the depth of grounding electrode penetration into the soil layer, and increasing the radius between grounding electrode pairs are all effective methods to reduce the contact impedance of electric dipole antennas, thereby improving information transmission capacity. To achieve wireless information transmission through the stratum, by appropriately selecting the operating frequency of electromagnetic waves, a certain distance of signal transmission can be achieved.

Learning artificial number symbols with ordinal and magnitude information.

The question of how numerical symbols gain semantic meaning is a key focus of mathematical cognition research. Some have suggested that symbols gain meaning from magnitude information, by being mapped onto the approximate number system, whereas others have suggested symbols gain meaning from their ordinal relations to other symbols. Here we used an artificial symbol learning paradigm to investigate the effects of magnitude and ordinal information on number symbol learning. Across two experiments, we found that after either magnitude or ordinal training, adults successfully learned novel symbols and were able to infer their ordinal and magnitude meanings. Furthermore, adults were able to make relatively accurate judgements about, and map between, the novel symbols and non-symbolic quantities (dot arrays). Although both ordinal and magnitude training was sufficient to attach meaning to the symbols, we found beneficial effects on the ability to learn and make numerical judgements about novel symbols when combining small amounts of magnitude information for a symbol subset with ordinal information about the whole set. These results suggest that a combination of magnitude and ordinal information is a plausible account of the symbol learning process.

The Iconicity Ring Hypothesis Bridges the Gap Between Symbol Grounding and Linguistic Relativity.

Kemmerer captured the drastic change in theories of word meaning representations, contrasting the view that word meaning representations are amodal and universal, with the view that they are grounded and language-specific. However, he does not address how language can be simultaneously grounded and language-specific. Here, we approach this question from the perspective of language acquisition and evolution. We argue that adding a new element-iconicity-is critically beneficial and offer the iconicity ring hypothesis, which explains how language-specific, secondary iconicity might emerge from biologically grounded and universally shared iconicity in the course of language acquisition and evolution.

A Multi-Frequency Omnidirectional Antenna Based on a Ring-Shaped Structure.

A multi-frequency microstrip antenna loaded with a ring-like structure has been proposed. The radiating patch on the antenna surface consists of three split-ring resonator structures, and the ground plate consists of a bottom metal strip and three ring-shaped metals with regular cuts to form a defective ground structure. The proposed antenna works in six different frequency bands covering 1.10, 1.33, 1.63, 1.97, 2.08, and 2.69 GHz and works entirely when connected to 5G NR (FR1, 0.45-3 GHz), 4GLTE (1.6265-1.6605 GHz), Personal Communication System (1.85-1.99 GHz), Universal Mobile Telecommunications System (1.92-2.176 GHz), WiMAX (2.5-2.69 GHz), and other communications frequency bands. Moreover, such antennas also have stable omnidirectional radiation properties across different operating frequency bands. This antenna meets the needs of portable multi-frequency mobile devices and provides a theoretical approach for the development of multi-frequency antennas.

Tackling SNR at low-field: a review of hardware approaches for point-of-care systems.

OBJECTIVE: To review the major hardware components of low-field point-of-care MRI systems which affect the overall sensitivity. METHODS: Designs for the following components are reviewed and analyzed: magnet, RF coils, transmit/receive switches, preamplifiers, data acquisition system, and methods for grounding and mitigating electromagnetic interference. RESULTS: High homogeneity magnets can be produced in a variety of different designs including C- and H-shaped as well as Halbach arrays. Using Litz wire for RF coil designs enables unloaded Q values of ~ 400 to be reached, with body loss representing about 35% of the total system resistance. There are a number of different schemes to tackle issues arising from the low coil bandwidth with respect to the imaging bandwidth. Finally, the effects of good RF shielding, proper electrical grounding, and effective electromagnetic interference reduction can lead to substantial increases in image signal-to-noise ratio. DISCUSSION: There are many different magnet and RF coil designs in the literature, and to enable meaningful comparisons and optimizations to be performed it would be very helpful to determine a standardized set of sensitivity measures, irrespective of design.

Rethinking symbolic and visual context in Referring Expression Generation.

Situational context is crucial for linguistic reference to visible objects, since the same description can refer unambiguously to an object in one context but be ambiguous or misleading in others. This also applies to Referring Expression Generation (REG), where the production of identifying descriptions is always dependent on a given context. Research in REG has long represented visual domains through symbolic information about objects and their properties, to determine identifying sets of target features during content determination. In recent years, research in visual REG has turned to neural modeling and recasted the REG task as an inherently multimodal problem, looking at more natural settings such as generating descriptions for objects in photographs. Characterizing the precise ways in which context influences generation is challenging in both paradigms, as context is notoriously lacking precise definitions and categorization. In multimodal settings, however, these problems are further exacerbated by the increased complexity and low-level representation of perceptual inputs. The main goal of this article is to provide a systematic review of the types and functions of visual context across various approaches to REG so far and to argue for integrating and extending different perspectives on visual context that currently co-exist in research on REG. By analyzing the ways in which symbolic REG integrates context in rule-based approaches, we derive a set of categories of contextual integration, including the distinction between positive and negative semantic forces exerted by context during reference generation. Using this as a framework, we show that so far existing work in visual REG has considered only some of the ways in which visual context can facilitate end-to-end reference generation. Connecting with preceding research in related areas, as possible directions for future research, we highlight some additional ways in which contextual integration can be incorporated into REG and other multimodal generation tasks.

Understanding Social Robots: Attribution of Intentional Agency to Artificial and Biological Bodies.

Much research in robotic artificial intelligence (AI) and Artificial Life has focused on autonomous agents as an embodied and situated approach to AI. Such systems are commonly viewed as overcoming many of the philosophical problems associated with traditional computationalist AI and cognitive science, such as the grounding problem (Harnad) or the lack of intentionality (Searle), because they have the physical and sensorimotor grounding that traditional AI was argued to lack. Robot lawn mowers and self-driving cars, for example, more or less reliably avoid obstacles, approach charging stations, and so on-and therefore might be considered to have some form of artificial intentionality or intentional directedness. It should be noted, though, that the fact that robots share physical environments with people does not necessarily mean that they are situated in the same perceptual and social world as humans. For people encountering socially interactive systems, such as social robots or automated vehicles, this poses the nontrivial challenge to interpret them as intentional agents to understand and anticipate their behavior but also to keep in mind that the intentionality of artificial bodies is fundamentally different from their natural counterparts. This requires, on one hand, a "suspension of disbelief " but, on the other hand, also a capacity for the "suspension of belief." This dual nature of (attributed) artificial intentionality has been addressed only rather superficially in embodied AI and social robotics research. It is therefore argued that Bourgine and Varela's notion of Artificial Life as the practice of autonomous systems needs to be complemented with a practice of socially interactive autonomous systems, guided by a better understanding of the differences between artificial and biological bodies and their implications in the context of social interactions between people and technology.