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This corpus comprises a diverse collection of authentic dialogues extracted from clinical encounters and from AI-generated interactions. Encompassing a wide array of scenarios, it offers a comprehensive snapshot of human communication within medical contexts and the evolving capabilities of AI. By intertwining genuine exchanges with those produced by AI models, the corpus facilitates a deeper understanding of communication dynamics and the progression of AI technology in simulating human interactions.

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Autistic people typically need methodical support as they explore and interact with their immediate surroundings and the objects associated with them, emphasising the importance of spatial knowledge and cognitive skills in improving and understanding their surroundings. The objective of this research paper is to present a conceptual and technical framework that could be of significant assistance in developing spatial ability and cognitive skills in autistic people.

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The PID is collected by small unmanned aerial vehicles equipped with LiDAR.

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We investigated the effect of CW radiation at 0.6 THz on pathological protein aggregates in the form of amyloid fibrils, i.e. ordered protein complexes linked to neurodegenerative diseases such as Parkinson's and Frontotemporal Dementia. To monitor the effect of THz irradiation we exploited mid-infrared (mid-IR) vibrational spectroscopy in the amide-I band range, whose lineshape is known to depend on the protein conformation and on how proteins arrange into ordered supramolecular complexes such as fibrils.

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This study analyzes the spending of Brazilian municipalities on health using an approach based on computational intelligence. The study was characterized by a quantitative and documentary database, and 117 municipalities with an average population between 2004 and 2019 of more than 100,000 inhabitants were analyzed. The data was obtained from the Brazilian Finance database (Finbra) (National Treasury Secretariat) and processed and adjusted for inflation. The main technique used was cluster analysis via R software, version 3.3.3.

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A dataset comprising a total of 21 individuals has been meticulously compiled, with 9 individuals identified as exhibiting Major Depressive Disorder (MDD) based on the outcomes derived from the PHQ-9 Questionnaire. The remaining 12 individuals in the dataset are classified as non-MDD. 

The dataset encompasses diverse sensor data, including temperature measurements, SpO2 readings, pulse rates, and accelerometer data. It is important to note that all data points were collected within a controlled environment, ensuring reliability and consistency throughout the dataset.

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Smart grids are nowadays featured by distributed energy resources, both renewables, traditional sources and storage systems. Generally, these components are characterized by different control technologies that interact with the generators through smart inverters. This exposes them to a variety of cyber threats. In this context, there is a need to develop datasets of attacks on these systems, in order to evaluate the risks and allow researchers to develop proper monitoring algorithms.

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A specially designed waist-worn device with accelerometer, gyroscope, and pressure sensor was utilized to collect information about 18 ADLs and 16 fall types. The falls protocol has been performed in our lab to replicate realistic situations that typically affect workers and older people. In contrast to other datasets that are accessible to the public, we included a new task in the falls, syncope, since it has a high mortality rate among the elderly and is linked to falls. As such, we must take it into account and include it in our fall detection system.

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We downloaded the dataset of Hindi Poems from the Website, contains around 2500 poems the downloaded dataset link is: link In the initial phase of our data preprocessing pipeline, we collected text data from a diverse set of HTML files, totaling 2500 documents. These files, constituting a substantial corpus, were meticulously curated for subsequent analysis. To facilitate further investigation, we amalgamated all the extracted text into a consolidated text file, a crucial step in preparing the data for subsequent processing.

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Molecular communication is a paradigm inspired by biological systems, where chemical signals encode and transmit information. MoSK (Molecule Shift Keying) is proposed as a modulation technique that utilizes different signaling molecules to encode digital information. MoSK mimics natural molecular communication by leveraging the diversity of signaling molecules and their specific roles. Experimental testbeds have been developed using microfluidic systems, droplet-based platforms, and biological cells to validate MoSK.

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