79 research outputs found
A natural deduction system for bundled branching time logic
No full textWe introduce a natural deduction system for the until-free subsystem of the branching time logic Although we work with labelled formulas, our system differs conceptually from the usual labelled deduction systems because we have no relational formulas. Moreover, no deduction rule embodies semantic features such as properties of accessibility relation or similar algebraic properties. We provide a suitable semantics for our system and prove that it is sound and weakly complete with respect to such semantics
A two-dimensional metric temporal logic
No full textWe introduce a two-dimensional metric (interval) temporal logic whose inter- nal and external time flows are dense linear orderings. We provide a suitable semantics and a sequent calculus with axioms for equality and extralogical axioms. Then we prove completeness and a semantic partial cut-elimination theorem down to formulas of a certain type
Tumors of the Chest Wall
No full textPrimary tumors of the chest wall are uncommon.
Chest wall tumors, whether malignant or benign,are classified as primary or secondary (metastatic).The most common benign tumors are osteochondromas and chondromas. The most common malignant chest wall tumors are sarcomas.
Most primary tumors originate in the bones or muscles of the chest wall, though they can also arise from nerves and vessels. Less than half
of malignant chest wall tumors are primary. Secondary tumors originate elsewhere in the body and spread (metastasize) to the chest wall.
The most frequent secondary tumors of the chest wall spread from primary breast and lung cancer. In fact, they can either locally extend to the chest wall, or metastasize to it. Furthermore, other tumors that are not unfrequently spread to the pleura include those originating from ovary, kidney, uterus, head and neck, and testis.
Therefore, almost all secondary tumors are malignant. Most chest wall tumors found in children are primary, while most found in adults are
secondary . It is often difficult to make an accurate presurgical diagnosis and differentiate benign from malignant tumors. Most patients with primary chest wall tumor receive surgical biopsy or radical surgical resection
A closer look to the sgoldstino interpretation of the diphoton excess
No full textAbstract: We revisit the sgoldstino interpretation of the diphoton excess in the context of gauge mediation. While the bound on the gluino mass might seem to make the sgoldstino contribution to the diphoton excess unobservable, we show that the interpretation is viable in a thin, near critical region of the parameter space. This regime gives rise to drastic departures from the standard gauge mediation picture. While the fermion messengers lie in the (10-100) TeV range, some scalar messengers are significantly lighter and are responsible for the sgoldstino production and decay. Their effective coupling to the sgoldstino is correspondingly enhanced, and a non-perturbative regime is triggered when light and heavy messenger masses differ by a factor ≳ 4π. We also comment on the possible role of an R-axion and on the possibility to decouple the sfermions in this context. © 2016, The Author(s)
An Assessment of ChatGPT’s Responses to Common Patient Questions About Lung Cancer Surgery: A Preliminary Clinical Evaluation of Accuracy and Relevance
No full textBackground: Chatbots based on artificial intelligence (AI) and machine learning are rapidly growing in popularity. Patients may use these technologies to ask questions regarding surgical interventions, preoperative assessments, and postoperative outcomes. The aim of this study was to determine whether ChatGPT could appropriately answer some of the most frequently asked questions posed by patients about lung cancer surgery. Methods: Sixteen frequently asked questions about lung cancer surgery were asked to the chatbot in one conversation, without follow-up questions or repetition of the same questions. Each answer was evaluated for appropriateness and accuracy using an evidence-based approach by a panel of specialists with relevant clinical experience. The responses were assessed using a four-point Likert scale (i.e., “strongly agree, satisfactory”, “agree, requires minimal clarification”, “disagree, requires moderate clarification”, and “strongly disagree, requires substantial clarification”). Results: All answers provided by the chatbot were judged to be satisfactory, evidence-based, and generally unbiased overall, seldomly requiring minimal clarification. Moreover, information was delivered in a language deemed easy-to-read and comprehensible to most patients. Conclusions: ChatGPT could effectively provide evidence-based answers to the most commonly asked questions about lung cancer surgery. The chatbot presented information in a language considered understandable by most patients. Therefore, this resource may be a valuable adjunctive tool for preoperative patient education
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