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We quantify how user mobile Internet usage relates to unique characteristics of the mobile Internet. In particular, we focus on examining how the mobile-phone-based content generation behavior of users relates to content usage behavior. The key objective is to analyze whether there is a positive or negative interdependence between the two activities. We use a unique panel data set that consists of individual-level mobile Internet usage data that encompass individual multimedia content generation and usage behavior. We combine this knowledge with data on user calling patterns, such as duration, frequency, and locations from where calls are placed, to construct their social network and to compute their geographical mobility. We build an individual-level simultaneous equation panel data model that controls for the different sources of endogeneity of the social network. We find that there is a negative and statistically significant temporal interdependence between content generation and usage. This finding implies that an increase in content usage in the previous period has a negative impact on content generation in the current period and vice versa. The marginal effect of this interdependence is stronger on content usage (up to 8.7%) than on content generation (up to 4.3%). The extent of geographical mobility of users has a positive effect on their mobile Internet activities. Users more frequently engage in content usage compared to content generation when they are traveling. In addition, the variance of user mobility has a stronger impact on their mobile Internet activities than does the mean. We also find that the social network has a strong positive effect on user behavior in the mobile Internet. These analyses unpack the mechanisms that stimulate user behavior on the mobile Internet. Implications for shaping user mobile Internet usage behavior are discussed. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors.

The content created by the users of social networking sites has reached such high levels of quality and variety that it is comparable to that produced by professional agencies. Therefore, understanding what types of content users generate and the underlying motivational factors is vital to the success of the sites. The extant research on content generation has primarily focused on the amount of content and on how to encourage participation in content creation, and less attention has been paid to the content itself and how social relations affect the types of content that users upload. This study aims to empirically document the relationship between social ties and the similarities between the types of content that people create online. We collected a large data set from the photo-hosting website Flickr detailing the users' social relations over time in conjunction with their photo-uploading behavior. We found that around the time of the formation of a social tie, members of dyads began to upload more similar photos than they did before that time. After a social tie was formed, this similarity evolved in different ways in different subgroups of dyads. Whereas the similarity between photos uploaded by dyads experiencing notably different popularity levels on the site continued to grow, the dyads of users with similar levels of popularity gradually began to upload less similar photos. In cultural production, individuals appear to present themselves as unique; this feature is more salient when the social contacts are similar in popularity status. Photo-shooting behaviors have been found to exhibit the same patterns. Furthermore, we show that the most divergent uploading behavior is observed when a high-popularity user initiates a tie with a user with lower popularity. We use social psychological motivations to explain these results.

Mind uploading—the transference of mind from a biological brain to a computer—offers the alluring possibility of immortality. This paper provides a novel challenge to mind uploading, focusing on the distinction between abstract objects and concrete individuals. Uploads are abstract objects, while currently, persons are concrete individuals. This presents a dilemma: if the mind is concrete, uploading it to a computer is impossible. Alternatively, if mind uploading is feasible, the resulting abstract upload cannot be numerically identical to the original person. Furthermore, by differentiating survival from persistence, this paper argues that concrete persons might survive as abstract uploads, but only in a highly restricted sense, without preserving their numerical identity. Despite these philosophical hurdles, practical reasons for considering mind uploading as life nears its end still need to be acknowledged.

Retrieval-augmented generation (RAG) adds a simple but powerful feature to chatbots, the ability to upload files just-in-time. Chatbots are trained on large quantities of public data. The ability to upload files just-in-time makes it possible to reduce hallucinations by filling in gaps in the knowledge base that go beyond the public training data such as private data and recent events. For example, in a customer service scenario, with RAG, we can upload your private bill and then the bot can discuss questions about your bill as opposed to generic FAQ questions about bills in general. This tutorial will show how to upload files and generate responses to prompts; see https://github.com/kwchurch/RAG for multiple solutions based on tools from OpenAI, LangChain, HuggingFace transformers and VecML.

As a genre, science fiction has long played with the idea of all-powerful virtual beings and explored notions of transcendence through technological advancements. It has also been at the forefront of exploring our anxieties and hopes regarding new technologies and the ethical and moral consequences of scientific advancement, raising deeply philosophical and theological concerns about an age-old question, namely: what makes us distinct as human beings and what lies beyond our own existence? This article aims to provide an overview of recent themes that have emerged in science fiction film and television, especially with regard to extending our lives beyond their natural biological age. As the article will outline, these ideas generally appear in notions of cyborgization or mind uploading into cyberspace. Both indicate a deeply human desire to avoid death, and the films and shows discussed in this article offer a range of different ideas on this. As we will see, the final case study, the Amazon Prime television show Upload (2020–), brings both of these elements together, touching on a broad range of ideas about cyber-spirituality along the way. The article concludes that although many shows raise interesting questions about the ethical challenges inherent in transhumanist fantasies of mind uploading, they ultimately remain ambiguous in their critique of the dream of digital immortality.

Extracellular vesicles (EVs) secreted by cancer cells play a crucial role in tumor progression by facilitating communication within the tumor microenvironment. These EVs carry molecular payloads that promote cancer cell survival, invasion, and metastasis. Recently, EVs have garnered significant interest as potential drug and gene delivery systems in cancer therapy. Glucose oxidase (GOX) was uploaded into EVs derived from adenocarcinomic human alveolar basal epithelial cells (A549) and further used as a potent starving agent in pristine A549 cells. In uploading studies, various loading methods such as incubation with and without saponin, freeze-thaw cycles, sonication, and different electroporation setups were tested. The electroporation technique exhibited the highest efficiency in loading GOX into EVs while maintaining EV integrity. GOX-loaded A549-derived EVs demonstrated significant cytotoxic effects on pristine A549 cells, suggesting that the EVs could effectively deliver enzymatic cargo to target cancer cells. The results highlight the potential of A549-derived EVs as \"Trojan-horse-like\" carriers for enzymatic cargo, offering a novel approach for targeting and disrupting metabolic pathways in lung cancer cells. This study presents EVs as promising vehicles for targeted delivery of therapeutic agents in cancer treatment.

An ontology of information belies our common intuitions about reality today and animates and governs both explicit scholarly study in philosophy and the sciences as well as the ideologies that are growing out of them. Transhumanism is one such technoscientific ideology that holds to a very specific ontology of information which need not be the only one on offer. This article argues that the transhumanist ontology of information exhibits gnostic and docetic religious overtones in it and that it devalues physical existence. At the same time, despite claiming a rejection of supernature, hypothetical transhumanist practices (such as mind‐uploading) posit the infosphere as a kind of supernatural realm that is often set in opposition to the natural world. This article presents a critique of transhumanist conceptions of information and offers an alternative ontology of information that more adequately accounts for the distinction between the natural and supernatural as well as the integrity of the physical world.

Underwater wireless sensor networks (UWSNs) have become a popular research topic due to the challenges of underwater communication. The existing mechanisms for collecting data from UWSNs focus on reducing the data redundancy and communication energy consumption, while ignoring the problem of energy-saving transmission after compression. In order to improve the efficiency of data collection, we propose a data uploading decision-making strategy based on the high similarity of the collected data and the energy consumption of the high similarity data compression. This decision-making strategy efficiently optimizes the energy consumption of the networks. By analyzing the data similarity, the quality of network communication, and uploading energy consumption, the decision-making strategy provides an energy-efficient data upload strategy for underwater nodes, which reduces the energy consumption in various network settings. The simulation results show that compared with several existing data compression and uploading methods, the proposed data upload methods has better energy saving effect in different network scenarios.

Driven by emerging technologies such as edge computing and Internet of Things (IoT), recent years have witnessed the increasing growth of data processing in a distributed way. Federated Learning (FL), a novel decentralized learning paradigm that can unify massive devices to train a global model without compromising privacy, is drawing much attention from both academics and industries. However, the performance dropping of FL running in a heterogeneous and asynchronous environment hinders its wide applications, such as in autonomous driving and assistive healthcare. Motivated by this, we propose a novel mechanism, called Fed2A: Federated learning mechanism in Asynchronous and Adaptive Modes. Fed2A supports FL by (1) allowing clients and the collaborator to work separately and asynchronously, (2) uploading shallow and deep layers of deep neural networks (DNNs) adaptively, and (3) aggregating local parameters by weighing on the freshness of information and representational consistency of model layers jointly. Moreover, the effectiveness and efficiency of Fed2A are also analyzed based on three standard datasets, i.e., FMNIST, CIFAR-10, and GermanTS. Compared with the best performance among three baselines, i.e., FedAvg, FedProx, and FedAsync, Fed2A can reduce the communication cost by over 77%, as well as improve model accuracy and learning speed by over 19% and 76%, respectively.

Aiming at the problem of large deformation and failure of the surrounding rock of the mining roadway in the nearly vertical and extra‐thick coal seam group under the action of dynamic pressure, the deformation and failure mechanism of the mining roadway were analyzed based on the actual engineering conditions. Using the methods of in situ stress testing, physical composition analysis, and numerical simulation, the deformation and failure laws of the surrounding rock in the mining tunnel are expounded. The results show that the special geological structure and the bending and prying action of the middle rock column put the coal and rock mass in a high stress state, and the dynamic pressure disturbance aggravated the instability of the jointed and fractured surrounding rock in this high stress state. Using the method of transient electromagnetic testing, prevention and control measures such as deep hole pressure relief blasting and optimized mining sequence were determined, which effectively reduced the stress of the surrounding rock and weakened the impact of dynamic pressure on the stability of the tunnel’s surrounding rock. Field measurement and numerical simulation results show that the constant resistance large deformation active coupling support technology effectively improves the joint bearing capacity of the support structure and surrounding rock, and the deformation and damage of the surrounding rock in the tunnel are effectively prevented. Different engineering conditions have different damage characteristics of tunnel surrounding rocks, and specific problems should be analyzed in the prevention and control process. Although this result has achieved good application results in this project, it still has certain limitations. Some technical parameters are only applicable to this project or to situations with similar nearly vertical strata.