Major self-mutilation leading to complete amputation of the hand during an acute psychotic episode

Traumatic amputations involving the upper limb can be a catastrophic injury with significant short and long-term consequences for patients. Upper limb injuries can have a profound impact of patient\u27s quality of life and have a large impact in the patient\u27s ability to perform activities of daily living (ADLs). A rare cause of traumatic amputations is major self-mutilation. Major self-mutilation is usually a devastating complication of severe mental health issues, with most people who inflict major self-mutilation having a psychotic disorder. We present a case of a self-inflicted traumatic hand amputation associated with an acute psychotic episode. The case shows the difficult decision that has to be made whether to perform a replantation or not. It also discusses gaining consent in a psychotic patient. The case highlights how timely communication between different medical specialists and sites can lead to good outcomes for patients

Influence of Size Classifications on the Structural and Solid-State Characterization of Cellulose Materials

Influence of size classification on the properties of cellulose materials has been a subject of neglect over the years. Researchers had the opinion that there exist no significant difference between the characteristics of bulk particulate materials and sizes of their constituents. However, it has been affirmed that increase in crystallinity index, increases the strength properties of cellulose materials. Therefore, there is need to establish the influence of size classification as it affects the properties of cellulose materials. This study focused on the influence of size classifications on the structural and solid State characterization of cellulose obtained from wood dust. The structure of the cellulose composed principally of crystalline cellulose (I and II) and amorphous cellulose. The crystallinity and the inter-planar spacing revealed different structural properties for the two size classifications. The elemental composition consists of Carbon (C), Oxygen (O), Sodium (Na) and Chlorine (Cl) with Carbon having the highest percentage. The surface morphology of the isolated cellulose appears fiber -like for the size classifications examined. The isolated cellulose exhibits good mechanical and solid state properties with promising applications in device utilization. Within the limit of the research, size classification is noted to influence the characteristics of the cellulose materials

Insights into the Diaporthe/Phomopsis complex infecting soybeans in the United States

Diaporthe/Phomopsis species are pathogens on a wide range of hosts including soybeans (Glycine max L.), and responsible for several diseases, some of which are of economic importance. Under favorable environmental conditions, these diseases can result in in significant yield losses (Backman et al. 1985). For example, yield losses from Stem canker in the Midwest have ranged from minor to in excess of 50% (Hartman et al. 1999). Four Diaporthe species have been reported pathogenic on soybean – Diaporthe sojae, the causal agent of pod and stem blight; Diaporthe caulivora and Diaporthe aspalathi, causal agents of Northern and Southern stem cankers, respectively; and Diaporthe longicolla, causing seed decay (Hartman et al. 1999)

The Imitation Game: Detecting Human and AI-Generated Texts in the Era of Large Language Models

The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become a significant task. This paper presents a comparative study, introducing a novel dataset of human-written and LLM-generated texts in different genres: essays, stories, poetry, and Python code. We employ several machine learning models to classify the texts. Results demonstrate the efficacy of these models in discerning between human and AI-generated text, despite the dataset's limited sample size. However, the task becomes more challenging when classifying GPT-generated text, particularly in story writing. The results indicate that the models exhibit superior performance in binary classification tasks, such as distinguishing human-generated text from a specific LLM, compared to the more complex multiclass tasks that involve discerning among human-generated and multiple LLMs. Our findings provide insightful implications for AI text detection while our dataset paves the way for future research in this evolving area

The 3rd International Workshop on Internet of Ubiquitous and Pervasive Things IUPT'2013 Preface

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The Province of Maine from the Best Authorities

The Province of Maine, from the best Authorities by Samuel Lewis, 1794. W. Barker, sculp. [Scale of] American Miles 69 1/2 to a Degree. Engraved for Carey\u27s American Edition of Guthrie\u27s Geography improved. Black and white, foldout map of northern Massachusetts showing the New Hampshire border and identifies the Line between the United States and the British Possessions by Treaty 1785 including Quebec and Nova Scotia. Map size: 36 x 24 cm. Scale 1:1,520,640. Engraved by W. Barker. Map is in stable condition but shows folds and creases.https://digitalcommons.library.umaine.edu/mainebicentennial/1014/thumbnail.jp

From the Internet of Things to the web of things-enabling by sensing as-A service

© 2016 IEEE. Sensing as a Service (SenaaS) is emerging as a prominent element in the middleware linking together the Internet of Things (IoT) and the Web of Things (WoT) layers of future ubiquitous systems. An architecture framework is discussed in this paper whereby things are abstracted into services via embedded sensors which expose a thing as a service. The architecture acts as a blueprint to guide software architects realizing WoT applications. Web-enabled things are eventually appended into Web platforms such as Social Web platforms to drive data and services that are exposed by these things to interact with both other things and people, in order to materialize further the future social Web of Things. Research directions are discussed to illustrate the integration of SenaaS into the proposed WoT architectural framework

Suitability of Blockchain for Collaborative Intrusion Detection Systems

© 2020 IEEE. Cyber-security is indispensable as malicious incidents are ubiquitous on the Internet. Intrusion Detection Systems have an important role in detecting and thwarting cyber-attacks. However, it is more effective in a centralized system but not in peer-to-peer networks which makes it subject to central point failure, especially in collaborated intrusion detection systems. The novel blockchain technology assures a fully distributed security system through its powerful features of transparency, immutability, decentralization, and provenance. Therefore, in this paper, we investigate and demonstrate several methods of collaborative intrusion detection with blockchain to analyze the suitability and security of blockchain for collaborative intrusion detection systems. We also studied the difference between the existing means of the integration of intrusion detection systems with blockchain and categorized the major vulnerabilities of blockchain with their potential losses and current enhancements for mitigation