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What is the relationship between policy positions taken in campaigns and those proposed in bargaining when the final policy outcome depends on other political actors? Why do candidates sometimes advocate policies in their campaigns that are unlikely or impossible to pass given the preferences of other actors in the government? We analyze a model in which candidates make non-binding policy platform announcements and then bargain with a Veto player over the final policy if they take office. In the model, a candidate has private information that is related to the policy preferences of a key citizen group and engages in bargaining with a Veto player who is responsive to this information. When the citizen's group sometimes interprets campaign promises naively, elections are more likely to allow information revelation. Furthermore, in this case, politicians overpromise: the politician's platform is outside of the range of feasible bargaining outcomes. [ABSTRACT FROM AUTHOR]

Orbital angular momentums (OAMs) greatly enhance the channel capacity in free-space optical communication. However, demodulation of superposed OAM to recognize them separately is always difficult, especially upon multiplexing more OAMs. In this work, we report a directly recognition of multiplexed fractional OAM modes, without separating them, at a resolution of 0.1 with high accuracy, using a multi-task deep learning (MTDL) model, which has not been reported before. Namely, two-mode, four-mode, and eight-mode superposed OAM beams, experimentally generated with a hologram carrying both phase and amplitude information, are well recognized by the suitable MTDL model. Two applications in information transmission are presented: the first is for 256-ary OAM shift keying via multiplexed fractional OAMs; the second is for OAM division multiplexed information transmission in an eightfold speed. The encouraging results will expand the capacity in future free-space optical communication. [ABSTRACT FROM AUTHOR]

We propose a new model of gradual consumer search based on simulated beliefs in which consumers are selective about the product attributes they inspect. The search literature has relied on parsimonious models to recover consumer fundamentals and characterize market outcomes. We investigate simple online search patterns that suggest that the dualistic view of fixed sample versus sequential search modes is the likely result of coarse data combined with methodological convenience. In contrast with these paradigms, we find that consumers are selective about the product attributes they inspect, that they revisit items to acquire additional information, and that they often convert without collecting all available data about the selected alternatives. Our substantive motivation is the problem of providing information to consumers in a market with differentiated products. We propose a new model of gradual consumer search based on simulated beliefs and "in-tandem" decision tree and likelihood computation that allows us to characterize the full search problem in contexts with moderate numbers of alternatives. We find that the seller's incentives to engage in search design activities tend to match the consumers' incentives. History: Tat Chan served as the senior editor. Funding: This work was funded by Fundação para a Ciência e a Tecnologia [Grants UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab - PINFRA/22209/2016], POR Lisboa and POR Norte [Social Sciences DataLab, PINFRA/22209/2016]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mksc.2022.0177. [ABSTRACT FROM AUTHOR]

Modern information theory pioneered by Shannon provides the mathematical foundation of information transmission and compression. However, the physical (and especially the energetic) nature of the information has been elusive. While the processing of information incurs inevitable energy dissipation, it is possible for communication systems to harness information to perform useful work. In this article, we prove that the thermodynamic cost (that is, the entropy production of the communication system) is at least equal to the information transmitted. Based on this result, a model of a communication heat engine is proposed, which can extract work from the heat bath by utilizing the transmission of information. The communication heat engine integrates the manipulation of both energy and information so that both information and power may be transmitted in parallel. The information transmission rate and the information power of the communication heat engine are derived from a pure thermodynamics argument. We find that the information power of the communication heat engine can be increased by increasing the number of communication channels, but the absolute energy efficiency of the heat engine first increases and then decreases after the number of channels of the system exceeds a threshold. The proposed model and definitions provide a new way to think of a classical communication system from a thermodynamic perspective. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research explores the application of neutrosophy to understand and address the inherent complexity in the oral transmission of knowledge in family agriculture. It leverages its ability to handle contradictions and ambiguities, facilitating a richer analysis of agricultural practices and social interactions. Orality, as the primary form of communication in these communities, is essential for the transmission of agricultural and cultural knowledge. This research highlights how orality acts as a vehicle for the preservation of collective identity and the transmission of ancestral knowledge. The study used Fuzzy Cognitive Maps (FCM) to describe the causal relationships between different variables of interest. Fieldwork was conducted between October 2023 and January 2024, using semi-structured interviews to capture the oral narrative of the farmers in Apagua. The analysis of the FCM showed that the components of cultural preservation and knowledge transmission are the most influential. This study demonstrated that neutrosophy is an effective tool for analyzing the complex dynamics of oral knowledge transmission in family agriculture. The conclusions underline the interdependence between knowledge transmission, social relationships, adaptation to changes, and cultural preservation. [ABSTRACT FROM AUTHOR]

Covert channel is a method to hide information in public communication channels for covert transmission, aiming at ensuring data transmission security and making third parties unaware of the covert communication process. However, with the continuous progress of traffic analysis technology, traditional network covert channels can no longer guarantee their security. Blockchain, as an emerging technology that combines cryptography, consensus algorithms, and P2P networks, has characteristics such as decentralization, traceability, anonymity, immutability, and security, making it an ideal platform for constructing covert channels. This paper first introduces blockchain technology, elaborates on the development process of covert channels, researches and summarizes the existing classification methods of covert channels. Then it summarizes the general model of blockchain covert channel on the basis of traditional network covert channel and divides the process of constructing covert channel into two main stages: information transmission and information extraction. Next, starting from the six-layer architecture of blockchain, the blockchain covert channels are analyzed in depth and the blockchain covert channels are divided into six categories according to different levels and subdivided based on the structure and mechanism of each layer, which can help better understand the construction process of blockchain covert channels and explore potential covert channels. Finally, this paper discusses the limitations of blockchain technology for covert channels and proposes future research directions.

Children actively and selectively transmit information to others based on the type of information and the context during learning. Four‐ to 7‐year‐old children preferentially transmit generalizable information in teaching‐like contexts. Although 2‐year‐old children are able to distinguish between generalizable and non‐generalizable information, it is not known whether they likewise transmit generalizable information selectively. We designed a behavioral study to address this question. Two‐year‐old children were presented with three novel boxes, identical except for their color. In each box, one of two equally salient actions led to a generalizable outcome (e.g., playing a [different] tune in each box), whereas the other led to a non‐generalizable outcome (e.g., turning on a light, vibrating the box, or making a noise). In the discovery phase, children had a chance to discover the functions of each box presented one‐by‐one. Then, in the exploration phase, they were given the opportunity to independently explore all three boxes presented together. Finally, in the transmission phase, an ignorant recipient entered the room and asked the child to show them how these toys work. We measured whether children preferentially transmitted either generalizable or non‐generalizable information when they were asked to demonstrate the function of the toys to a naïve adult. We found that children did not display any preference for transmitting generalizable information. These findings are discussed with respect to toddlers' selectivity in transmitting information but also the development of sensitivity to information generalizability. Research Highlight: Young children transmit information to others and do so with some degree of selectivity to a variety of factors.Generalizability is an important factor affecting information transmission, and older children tend to associate generalizable information with teaching‐like interactions.We tested whether toddlers selectively transmitted it to others over non‐generalizable information.We found that toddlers do not show a preference to transmit generalizable over non‐generalizable information. [ABSTRACT FROM AUTHOR]

Information transmission plays a crucial role across various fields, including physics, engineering, biology, and society. The efficiency of this transmission is quantified by mutual information and its associated information capacity. While studies in closed systems have yielded significant progress, understanding the impact of non-equilibrium effects on open systems remains a challenge. These effects, characterized by the exchange of energy, information, and materials with the external environment, can influence both mutual information and information capacity. Here, we delve into this challenge by exploring non-equilibrium effects using the memoryless channel model, a cornerstone of information channel coding theories and methodology development. Our findings reveal that mutual information exhibits a convex relationship with non-equilibriumness, quantified by the non-equilibrium strength in transmission probabilities. Notably, channel information capacity is enhanced by non-equilibrium effects. Furthermore, we demonstrate that non-equilibrium thermodynamic cost, characterized by the entropy production rate, can actually improve both mutual information and information channel capacity, leading to a boost in overall information transmission efficiency. Our numerical results support our conclusions. [ABSTRACT FROM AUTHOR]

We study here say-buy/whisper-sell behavior wherein analysts issue optimistic recommendations to attract retail investors while providing more accurate information to fund managers in private, sometimes resulting in fund managers selling the recommended stocks. We test whether fund managers return the favor using their votes for analysts in a Chinese "star analyst" competition. Managers are more likely to vote for analysts who exhibit greater "say-buy/whisper-sell" behavior toward these managers. This suggests that analysts reduce the accuracy of their public recommendations, thereby maintaining the value of their private advice to funds. Our findings help explain several empirical puzzles about analyst public recommendations. [ABSTRACT FROM AUTHOR]

Acquisition announcements coincide with upward value revisions for the target firms' technology peers, which are not due to economic relations based on product market, supply chain, or geographical location. Such a phenomenon is robust across subsample periods, not specific to merger or technology waves, and not related to product-market structure and the unique innovation features of certain technology-intensive industries. Firms experience more dramatic value revisions when they have deeper technology overlaps with their targets, are more dependent on technology, or when a transaction features higher premium or greater technology overlap between the acquirer and target. Our mechanism analysis provides evidence that is primarily consistent with the acquisition-probability hypothesis whereby acquisition announcements elevate expected technology synergies and merger prospects for peers and partially in line with the enhanced-investment hypothesis that peers' revaluations correlate with increased technology investments. We do not find any evidence in line with the competition-balance hypothesis that attributes peers' value revisions to the change in industrial competition intensity. Overall, our results demonstrate that acquisition announcements disseminate novel information about the value of technology that is of common interest among firms with close technologies. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4890. [ABSTRACT FROM AUTHOR]

Structured light can be encoded to carry information for free‐space optical communications with an extended degree of freedom to increase the capacity, however, the accuracy issue along with capacity increase is one of the biggest challenges that prevent practical applications. To achieve high accuracy with high capacity by a simple method, they propose the spatial nonlinear conversion of structured light into a communication network, especially, realizing an ultra‐high‐accuracy point‐to‐multipoint (PtoMP) information transmission link. A series of coherently superposed spatial modes and their spatial nonlinear conversion states are used as information carriers to replace the prior orbital angular momentum beams and greatly expand channel capacity within quite low spatial mode order. Through the spatial nonlinear conversion of simple dual‐mode superposition and a very basic neural network for machine learning‐based recognition, as high as 99.5% accuracy for more than 500 modes is obtained. By a combination of diffuse reflection screens and multiple CCDs, the large observation angle PtoMP information transmission is also proved to be feasible. This work paves the way for practical large‐scale multi‐party information networks using structured light. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Real‐time telemedicine detection can solve the problem of the shortage of public medical resources caused by the coming aging society. However, the development of such an integrated monitoring system is hampered by the need for high‐performance sensors and the strict‐requirement of long‐distance signal transmission and reproduction. Here, a bionic crack‐spring fiber sensor (CSFS) inspired by spider leg and cirrus whiskers for stretchable and weavable electronics is reported. Trans‐scale conductive percolation networks of multilayer graphene around the surface of outer spring‐like Polyethylene terephthalate (PET) fibers and printing Ag enable a high sensitivity of 28475.6 and broad sensing range over 250%. The electromechanical changes in different stretching stages are simulated by Comsol to explain the response mechanism. The CSFS is incorporated into the fabric and realized the human‐machine interactions (HMIs) for robot control. Furthermore, the 5G Narrowband Internet of Things (NB‐IoT) system is developed for human healthcare data collection, transmission, and reproduction together with the integration of the CSFS, illustrating the huge potential of the approach in human–machine communication interfaces and intelligent telemedicine rehabilitation and diagnosis monitoring. [ABSTRACT FROM AUTHOR]

How do migrant social networks matter for performance in the job? We examine this by constructing a nationality-based network of foreign newcomers when they first begin to play in the PGA TOUR and examine the impact of this initial social network on newcomers' probability of surviving (i.e., keeping their license) at the end of their inaugural PGA TOUR season. We find that the migrant social network matters among the non-elite group of players in the second tier of the PGA TOUR, but not among the elite group of players in the first tier of the PGA TOUR. For the second-tier tour players, we find that density of connections within a nationality cluster has a sizable positive effect on newcomers' probability of surviving, but no evidence that the centrality of a nationality cluster in the overall PGA TOUR network has an impact on survival. [ABSTRACT FROM AUTHOR]

Organic single crystals quickly emerge as dense yet light and nearly defect‐free media for emissive elements. Integration of functionalities and control over the emissive properties is currently being explored for a wide range of these materials to benchmark their performance against organic emissive materials diluted in powders or films. Here, we report mechanically flexible emissive chiral organic crystals capable of an unprecedented combination of fast, reversible, and low‐fatigue responses. UV‐excited single crystals of both enantiomers of the material, 4‐chloro‐2‐(((1‐phenylidene)imino)methyl)phenol, exhibit a drastic yet reversible change in the emission color from green to orange‐yellow within a second and can be cycled at least 2000 times. The photoresponse was found to depend strongly on the excitation intensity and temperature. Combining chirality, mechanical compliance, rapid emission switching, multiple responses, and writability by UV light, this material provides a unique and versatile platform for developing organic crystal‐based materials for on‐demand signal transfer, information storage, and cryptography. [ABSTRACT FROM AUTHOR]

Population density is a fundamental ecological feature influencing the opportunity for social encounters between individuals. Hence, density can impact various population processes such as social transmission. While the density dependence of disease spread has been studied extensively, we know little about how variation in density influences information transmission. If high densities lead to more social connections, information may spread more rapidly. Here, we experimentally manipulated local population density in great tits, Parus major , and investigated the effects on individuals' acquisition of information on novel food patches. We manipulated density by assigning individuals to either a high- or low-density treatment using automated bird feeders in the wild. We first show how our approach successfully led to changes in local population density. Next, we examine how the manipulation changed the local and individual social environment. At the local level, high-density locations resulted on average in denser and more clustered social networks compared to low-density locations. At the individual level, birds assigned to the high-density treatment had on average more social connections and more central network positions than birds in the low-density treatment. However, despite the effect on network structure, we found no evidence that the density manipulation influenced an individuals' likelihood, or speed, of locating novel food patches. Birds in the low-density treatment still spent a large proportion of time foraging at the high-density location. Thus, the manipulation did not lead to a strict segregation between birds of the different treatments, which may be one explanation for the absence of an effect on patch discovery. • We experimentally manipulated population density in wild great tits. • We examined effects of the manipulation on the discovery of food patches. • Higher densities led to denser and more clustered social networks. • Birds in the high-density treatment had more social connections. • We found no evidence for effects on the likelihood and speed of patch discovery. [ABSTRACT FROM AUTHOR]

Information cascades have been used to explain a variety of collective behaviours in nonhuman animals, including mate selection, antipredator responses and social foraging. A taxonomically widespread phenomenon, information cascades occur in many group-living animals from ant colonies to schools of fish and social mammals. Here we review the animal behaviour literature for examples of information cascades. We found that the literature on information cascades in animals is limited by inconsistent terminology that fails to adequately describe the differences between cascade types. We propose a classification framework, adapted from behavioural economics, to describe information cascades in behavioural ecology. Our framework consists of three types of information cascades derived from individual level fitness outcomes (adaptive, maladaptive or neutral) and a further two cascade types based on the transmission mechanism of cascading social information (signals or cues). We use a selection of past studies to illustrate the diversity of information cascades and we apply our framework to real world examples. We also discuss four mechanisms used by group-living animals to minimize the spread of maladaptive information cascades and propose avenues for future research. • Information cascades drive collective behaviours in a diverse suite of animal taxa. • Information cascades may be adaptive, selectively neutral or maladaptive. • Cascades are classified by their selective outcome and mode of transmission. • Group-living animals employ several mechanisms to minimize maladaptive cascades. [ABSTRACT FROM AUTHOR]

Information warfare requires more attention as competing interests get escalated by the spread of information on various Internet-based social media platforms in recent times. In this work, we construct and analyze a mathematical model with a system of ordinary differential equations to consider how two interacting pieces of information, where the first one is incomplete and misleading while the second one is corrective of the first, evolve with time in an online population. The counter and correctional information is the rejoinder. Human psychological and sociological attributes like disbelief in the rejoinder and increased tendency to keep spreading the misleading information even after knowing the correct one are factored into our model. We find that in correcting a misleading piece of information that is already spreading within a population, the rejoinder has to be released early enough within a certain time range. The findings can help us appreciate the impact of misinformation on the society and promote information literacy at optimal cost. [ABSTRACT FROM AUTHOR]

Accurately classifying degraded images is a challenging task that relies on domain expertise to devise effective image processing techniques for various levels of degradation. Genetic Programming (GP) has been proven to be an excellent approach for solving image classification tasks. However, the program structures designed in current GP-based methods are not effective in classifying images with quality degradation. During the iterative process of GP algorithms, the high similarity between individuals often results in convergence to local optima, hindering the discovery of the best solutions. Moreover, the varied degrees of image quality degradation often lead to overfitting in the solutions derived by GP. Therefore, this research introduces an innovative program structure, distinct from the traditional program structure, which automates the creation of new features by transmitting information learned across multiple nodes, thus improving GP individual ability in constructing discriminative features. An accompanying evolution strategy addresses high similarity among GP individuals by retaining promising ones, thereby refining the algorithm's development of more effective GP solutions. To counter the potential overfitting issue of the best GP individual, a multi-generational individual ensemble strategy is proposed, focusing on constructing an ensemble GP individual with an enhanced generalization capability. The new method evaluates performance in original, blurry, low contrast, noisy, and occlusion scenarios for six different types of datasets. It compares with a multitude of effective methods. The results show that the new method achieves better classification performance on degraded images compared with the comparative methods. [ABSTRACT FROM AUTHOR]

Abstract Real‐time telemedicine detection can solve the problem of the shortage of public medical resources caused by the coming aging society. However, the development of such an integrated monitoring system is hampered by the need for high‐performance sensors and the strict‐requirement of long‐distance signal transmission and reproduction. Here, a bionic crack‐spring fiber sensor (CSFS) inspired by spider leg and cirrus whiskers for stretchable and weavable electronics is reported. Trans‐scale conductive percolation networks of multilayer graphene around the surface of outer spring‐like Polyethylene terephthalate (PET) fibers and printing Ag enable a high sensitivity of 28475.6 and broad sensing range over 250%. The electromechanical changes in different stretching stages are simulated by Comsol to explain the response mechanism. The CSFS is incorporated into the fabric and realized the human‐machine interactions (HMIs) for robot control. Furthermore, the 5G Narrowband Internet of Things (NB‐IoT) system is developed for human healthcare data collection, transmission, and reproduction together with the integration of the CSFS, illustrating the huge potential of the approach in human–machine communication interfaces and intelligent telemedicine rehabilitation and diagnosis monitoring.

The ability to overcome the negative effects, induced by obstacles and turbulent atmosphere, is a core challenge of long-distance information transmission, and it is of great significance in free-space optical communication. The spatial-coherence structure, that characterizes partially coherent fields, provides a new degree of freedom for carrying information. However, due to the influence of the complex transmission environment, the spatial-coherence structure is severely damaged during the propagation path, which undoubtedly limits its ability to transmit information. Here, we realize the robust far-field orbital angular momentum (OAM) transmission and detection by modulating the spatial-coherence structure of a partially coherent vortex beam with the help of the cross-phase. The cross-phase enables the OAM information, quantified by the topological charge, hidden in the spatial-coherence structure can be stably transmitted to the far field and can resist the influence of obstructions and turbulence within the communication link. This is due to the self-reconstruction property of the spatial-coherence structure embedded with the cross-phase. We demonstrate experimentally that the topological charge information can be recognized well by measuring the spatial-coherence structure in the far field, exhibiting a set of distinct and separated dark rings even under amplitude and phase perturbations. Our findings open a door for robust optical signal transmission through the complex environment and may find application in optical communication through a turbulent atmosphere.

The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these considerations, a simple model for molecular communication entailing the diffusion of signaling molecules from transmitter to receiver is elucidated. The channel capacity C (maximal rate of information transmission) and an optimistic heuristic estimate of the actual information transmission rate ℐ are derived for this communication system; the two quantities, especially the latter, are demonstrated to be broadly consistent with laboratory experiments and more sophisticated theoretical models. The channel capacity exhibits a potentially weak dependence on environmental parameters, whereas the actual information transmission rate may scale with the intercellular distance d as ℐ ∝ d−4 and could vary substantially across settings. These two variables are roughly calculated for diverse astrobiological environments, ranging from Earth's upper oceans (C ∼ 3.1 × 10 bits/s; ℐ ∼ 4.7 × 10−2 bits/s) and deep sea hydrothermal vents (C ∼ 4.2 × 10 bits/s; ℐ ∼ 1.2 × 10−1 bits/s) to the hydrocarbon lakes and seas of Titan (C ∼ 3.8 × 10 bits/s; ℐ ∼ 2.6 × 10−1 bits/s). [ABSTRACT FROM AUTHOR]

Polyaniline (PANI) can achieve reversible optical modulation in visible and infrared (IR) bands under the action of voltage. However, PANI‐based electrochromic devices cannot cope with the dual detection of visible and IR light to realize the transmission of information due to the linkage restriction between the spectral modulation in the visible and IR region. Here, IR low‐absorptive inorganic pigments as colorants and IR high‐transparent polymer as a binder are utilized to prepare colored films with high transparency. A camouflage layer against visible light detection is constructed on the surface of IR electrochromic devices, and the information transmission is realized in the IR band by controlling the thermal radiation characteristics. Furthermore, thermochromic microcapsules (TMs) that change color under external thermal stimuli are introduced to fabricate a thermochromic and IR transparent functional layer, which is attached to the surface of IR electrochromic devices and endows the devices with separate spectral modulation ability in the visible and IR region. Multicolored displays are fabricated by arraying various devices. Moreover, visual patterns are prepared on the surface of IR electrochromic devices by dispensing technology. This configuration endows the device with a promising potential for anti‐counterfeiting, optical security, and related applications. [ABSTRACT FROM AUTHOR]

As a large and complex network with uneven spatial distribution, IoT is widely used in many optical network service industries. However, in the actual use process, it is easy to generate node congestion, resulting in more loaded nodes due to excessive energy consumption, resulting in information transmission link breakage, information loss and other situations. An optimization approach for information transmission of Internet of things nodes based on a fuzzy hierarchical neural network method was presented in order to address the issue of long laser transmission times caused by network congestion brought on by various types of IoT nodes. The key evaluation factors were screened out using the fuzzy analytic hierarchy method, and the comprehensive selection system of information transmission was constructed. Combining with the principle of fuzzy neural network, a comprehensive judgement model for the information transmission of IoT communication nodes based on fuzzy neural network was established, and its accuracy was tested. Based on the fuzzy hierarchical algorithm and the nonlinear mapping ability, this method develops an optimized mathematical model that complies with the requirements of information transmission optimization in the Internet of Things and enhances the global optimization capability and convergence efficiency. Through simulation and analysis of the findings, we found that the suggested method performs better than the particle swarm optimization (PSO) algorithm in terms of network energy consumption, transmission latency, packet loss rate, and other metrics. connectivity and reliability. In terms of network energy consumption, transmission delay and packet loss rate, the proposed algorithm is 35.8, 27.9 and 31.6% lower than PSO algorithm, respectively. The mathematical model realizes the comprehensive judgement and the optimal network path that routes the engineering requirements is obtained through multi-generation evolution. Simulation results show that this method can effectively reduce transmission probability error rate, network congestion and transmission time. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cancer is one of the leading causes of death worldwide. Benefiting from technological advances, new approaches for treatment are being proposed, studied and tested. High intensity focused ultrasounds (HIFU) is one of them. To further improve the performance of such a system, using integrated driver to ultrasound transducers is one step forward. To reach this goal, several design challenges must be overcome: the driver design must be compatible with complementry metal oxide semiconductor (CMOS) technology; it also must be compatible with magnetic resonance imaging (MRI) equipment used for treatment monitoring; and it should be immune to the floating ground necessary for AC-switch implementation for some specific implementation. In this article, a new AC-switch driver used within a HIFU system for a resonant circuit autotuning is proposed. A capacitive isolation is chosen so that the designed driver is compatible with both CMOS technology and MRI. It is designed in a CMOS HV 0.35 μm. The simulation results have shown that with just a 10 ns delay, or 1% of the control signal cycle, this system may run with a floating ground that can reach 180 Vpp with respect to the main ground, leading to a relative inaccuracy of 0.065% of the resonance frequency of the tank circuit. The design is well balanced so that it minimizes the carrier frequency, power consumption, and created signal latency. By using the proposed active biasing circuit, the system's power usage is further cut in half while still maintaining a floating ground voltage of 160 Vpp, which is sufficient for our needs. [ABSTRACT FROM AUTHOR]

To design an online real-time transmission tool of irst-person perspective information. This information transmission tool is designed to help medical staff monitor the patient's condition changes and respond quickly, ensuring the patient's life safety. (本研究设计一种第一视角信息在线实时传输工具, 旨在方便医务人员第一时间监测到患者的病情变化趋势并迅速做出反应, 保障患者的生命安全。)

Being the important composition, the efficiency of information transmission system affects directly degree of system operational task. Aiming at the characteristics of warship information transmission efficiency evaluation multiple requirements and complex system organization application, the paper applies the method combining technique quantification model and restriction factors. Rounding single link, multiple links and marshalling operations information transmission requirements, the system structure of information transmission efficiency evaluation based on operational task is established, which can offer efficient supplication for warship communication command.

Volatility spillover informs whether the information in one market impacts the information in another. This paper examines whether oil market volatility spills over to the equity markets of selected SAARC countries. The study uses data from February 2013 to September 2019 to obtain updated evidence about the transmission of global oil price volatility to the equity markets of the SAARC member countries. The bivariate EGARCH model is used to test for volatility transmission from the oil market to the stock market. It is found that oil price shocks do not significantly impact equity market volatility, except in Bangladesh. Policymakers can use these findings when making policy decisions.

Modern information theory pioneered by Shannon provides the mathematical foundation of information transmission and compression. However, the physical (and especially the energetic) nature of the information has been elusive. While the processing of information incurs inevitable energy dissipation, it is possible for communication systems to harness information to perform useful work. In this article, we prove that the thermodynamic cost (that is, the entropy production of the communication system) is at least equal to the information transmitted. Based on this result, a model of a communication heat engine is proposed, which can extract work from the heat bath by utilizing the transmission of information. The communication heat engine integrates the manipulation of both energy and information so that both information and power may be transmitted in parallel. The information transmission rate and the information power of the communication heat engine are derived from a pure thermodynamics argument. We find that the information power of the communication heat engine can be increased by increasing the number of communication channels, but the absolute energy efficiency of the heat engine first increases and then decreases after the number of channels of the system exceeds a threshold. The proposed model and definitions provide a new way to think of a classical communication system from a thermodynamic perspective.

Information transmission plays a crucial role across various fields, including physics, engineering, biology, and society. The efficiency of this transmission is quantified by mutual information and its associated information capacity. While studies in closed systems have yielded significant progress, understanding the impact of non-equilibrium effects on open systems remains a challenge. These effects, characterized by the exchange of energy, information, and materials with the external environment, can influence both mutual information and information capacity. Here, we delve into this challenge by exploring non-equilibrium effects using the memoryless channel model, a cornerstone of information channel coding theories and methodology development. Our findings reveal that mutual information exhibits a convex relationship with non-equilibriumness, quantified by the non-equilibrium strength in transmission probabilities. Notably, channel information capacity is enhanced by non-equilibrium effects. Furthermore, we demonstrate that non-equilibrium thermodynamic cost, characterized by the entropy production rate, can actually improve both mutual information and information channel capacity, leading to a boost in overall information transmission efficiency. Our numerical results support our conclusions.

Decades of research seek to understand how people form perceptions of risk by modeling either individual-level psychological processes or broader social and organizational mechanisms. Yet, little formal theoretical work has focused on the interaction of these 2 sets of factors. In this paper, I contribute to closing this gap by modifying a psychologically rich individual model of probabilistic reasoning to account for the transmission and collective emergence of risk perceptions. Using data from 357 individuals, I present experimental evidence in support of my main building assumptions and demonstrate the empirical validity of my model. Incorporating these results into an agent-based setting, I simulate over 1.5 billion social interactions to analyze the emergence of risk perceptions within organizations under different information frictions (i.e., limits on the availability and precision of social information). My results show that by focusing on information quality (rather than availability), groups and organizations can more effectively boost the accuracy of their emergent risk perceptions. This work offers researchers a formal framework to analyze the relationship between psychological and organizational factors in shaping risk perceptions.

The entry into and uptake of information in social groups is critical for behavioral adaptation by long-lived species in rapidly changing environments. We exposed five groups of wild vervet monkeys to a novel food to investigate the innovation of processing and consuming it. We report that immigrant males innovated in two groups, and an infant innovated in one group. In two other groups, immigrant males imported the innovation from their previous groups. We compared uptake between groups with respect to the initial innovator to examine the extent to which dispersing males could introduce an innovation into groups. Uptake of the novel food was faster in groups where immigrant males ate first rather than the infants. Younger individuals were more likely overall, and faster, to subsequently acquire the novel food. We also investigated the role of muzzle contact behavior in information seeking around the novel food. Muzzle contacts decreased in frequency over repeated exposures to the novel food. Muzzle contacts were initiated the most by naïve individuals, high rankers, and juveniles; and were targeted most towards knowledgeable individuals and high rankers, and the least towards infants. We highlight the potential importance of dispersers in rapidly exploiting novel resources among populations.

Using the method of, this study constructs a tail risk predictor of the international commodity market to forecast US stock volatility. The in-sample results show that tail risk contains significant interpretive ability for stock volatility. Being of our interest, the tail risk predictor can successfully predict the US stock volatility from both statistical and economic viewpoints. The results of controlling 12 popular macroeconomic variables suggest that tail risk contains incremental information for stock volatility. To further confirm our findings, we examine the forecasting performance of the tail risk predictor for 12 industrial portfolios. [ABSTRACT FROM AUTHOR]

Being the important composition, the efficiency of information transmission system affects directly degree of system operational task. Aiming at the characteristics of warship information transmission efficiency evaluation multiple requirements and complex system organization application, the paper applies the method combining technique quantification model and restriction factors. Rounding single link, multiple links and marshalling operations information transmission requirements, the system structure of information transmission efficiency evaluation based on operational task is established, which can offer efficient supplication for warship communication command. [ABSTRACT FROM AUTHOR]

This study matches the digital financial inclusion index with micro panel data from the China Household Finance Survey (CHFS) in 2015, 2017, and 2019, and explores the impact of digital finance on the return rate of entrepreneurship. The results show that the effect is positive—entrepreneurial households in prefectures with higher digital finance obtain higher return rates—and remarkably reliable to a battery of endogeneity and robustness tests. Mechanism analysis indicates that the positive effect of digital finance on the return rate of entrepreneurship is achieved mainly through facilitating external financing and reducing financial transaction costs. Further research finds that the spillover effect of digital finance has obvious Internet bias: the "digital dividend" only extends to the advantaged classes who have access to the Internet—non-rural and migrating rural entrepreneurs, but for non-migrating rural entrepreneurs generally facing digital exclusion, digital finance has little effect on their return rate. The empirical evidence presented in this study has important policy implications for accelerating the digital finance process, promoting high-quality entrepreneurship development, and boosting digital poverty groups to break stratum solidification. [ABSTRACT FROM AUTHOR]

Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼ 10 24 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance. [ABSTRACT FROM AUTHOR]

Visual perception in natural environments depends on the ability to focus on salient stimuli while ignoring distractions. This kind of selective visual attention is associated with gamma activity in the visual cortex. While the nucleus reticularis thalami (nRT) has been implicated in selective attention, its role in modulating gamma activity in the visual cortex remains unknown. Here, we show that somatostatin- (SST) but not parvalbumin-expressing (PV) neurons in the visual sector of the nRT preferentially project to the dorsal lateral geniculate nucleus (dLGN), and modulate visual information transmission and gamma activity in primary visual cortex (V1). These findings pinpoint the SST neurons in nRT as powerful modulators of the visual information encoding accuracy in V1 and represent a novel circuit through which the nRT can influence representation of visual information.

Accurately classifying degraded images is a challenging task that relies on domain expertise to devise effective image processing techniques for various levels of degradation. Genetic Programming (GP) has been proven to be an excellent approach for solving image classification tasks. However, the program structures designed in current GP-based methods are not effective in classifying images with quality degradation. During the iterative process of GP algorithms, the high similarity between individuals often results in convergence to local optima, hindering the discovery of the best solutions. Moreover, the varied degrees of image quality degradation often lead to overfitting in the solutions derived by GP. Therefore, this research introduces an innovative program structure, distinct from the traditional program structure, which automates the creation of new features by transmitting information learned across multiple nodes, thus improving GP individual ability in constructing discriminative features. An accompanying evolution strategy addresses high similarity among GP individuals by retaining promising ones, thereby refining the algorithm’s development of more effective GP solutions. To counter the potential overfitting issue of the best GP individual, a multi-generational individual ensemble strategy is proposed, focusing on constructing an ensemble GP individual with an enhanced generalization capability. The new method evaluates performance in original, blurry, low contrast, noisy, and occlusion scenarios for six different types of datasets. It compares with a multitude of effective methods. The results show that the new method achieves better classification performance on degraded images compared with the comparative methods.