The purpose of this report is to describe the case and management of an unexplained vitreous haemorrhage that occurred after repeated roller-coaster riding. The authors inadvertently demonstrate the ...value of observation over immediate surgery in certain situations and review the literature on vitreoretinal and other ocular complications after roller-coaster riding. A 26-year-old male presented 12 h after riding high-velocity roller-coasters with a left vitreous haemorrhage. A hazy view of the retina and B-scan revealed a bullous area of superior-temporal retinal lifting. A diagnosis of a presumed macula-on retinal detachment was made and the patient was listed for a pars plana vitrectomy retinal detachment repair. An abnormal clotting result, which was subsequently found out to be erroneous, ultimately delayed the procedure. During this delay the vision and retinal view improved to an extent whereby the diagnosis of a retinoschisis with an intraretinal cyst was made and surgery was avoided. The patient regained 6/6 vision, without the need to undergo surgery. Historically the management of an unexplained vitreous haemorrhage was observation with serial B-scans. The current evidence and practice for treating unexplained vitreous haemorrhage have since moved towards early surgical intervention. The authors highlight that despite the current trend, a place remains for conservative management for selected cases.
The purpose of this report is to describe an unusual presentation of vitreous hemorrhage (VH) in a patient with an immunosuppressive condition.
Retrospective case report.
A 72-year-old woman with ...known T-cell prolymphocytic leukemia treated with a course of alemtuzumab presented to our department with a VH in her left eye after a fall. An initial diagnosis of hemorrhagic posterior vitreous detachment was made. However, as the VH was resolving, she was found to have underlying vitritis, occlusive vasculitis, and a pale optic nerve head. Vitreous biopsy confirmed cytomegalovirus retinitis. Despite treatment with intravenous foscarnet and oral valganciclovir, her vision continued to remain poor because of the severe damage from the retinal vasculitis and residual VH.
As indications for immunosuppression increase, the incidence of cytomegalovirus retinitis in non-HIV-immunosuppressed patients is expected to rise. Therefore, in this subgroup of patients, we should be aware of any underlying retinitis especially in cases with an unusual presentation of VH.
With the AI revolution in place, the trend for building automated systems to support professionals in different domains such as the open source software systems, healthcare systems, banking systems, ...transportation systems and many others have become increasingly prominent. A crucial requirement in the automation of support tools for such systems is the early identification of named entities, which serves as a foundation for developing specialized functionalities. However, due to the specific nature of each domain, different technical terminologies and specialized languages, expert annotation of available data becomes expensive and challenging. In light of these challenges, this paper proposes a novel named entity recognition (NER) technique specifically tailored for the open-source software systems. Our approach aims to address the scarcity of annotated software data by employing a comprehensive two-step distantly supervised annotation process. This process strategically leverages language heuristics, unique lookup tables, external knowledge sources, and an active learning approach. By harnessing these powerful techniques, we not only enhance model performance but also effectively mitigate the limitations associated with cost and the scarcity of expert annotators. It is noteworthy that our model significantly outperforms the state-of-the-art LLMs by a substantial margin. We also show the effectiveness of NER in the downstream task of relation extraction.
Ensuring the safe alignment of large language models (LLMs) with human values is critical as they become integral to applications like translation and question answering. Current alignment methods ...struggle with dynamic user intentions and complex objectives, making models vulnerable to generating harmful content. We propose Safety Arithmetic, a training-free framework enhancing LLM safety across different scenarios: Base models, Supervised fine-tuned models (SFT), and Edited models. Safety Arithmetic involves Harm Direction Removal to avoid harmful content and Safety Alignment to promote safe responses. Additionally, we present NoIntentEdit, a dataset highlighting edit instances that could compromise model safety if used unintentionally. Our experiments show that Safety Arithmetic significantly improves safety measures, reduces over-safety, and maintains model utility, outperforming existing methods in ensuring safe content generation.
In the rapidly advancing field of artificial intelligence, the concept of Red-Teaming or Jailbreaking large language models (LLMs) has emerged as a crucial area of study. This approach is especially ...significant in terms of assessing and enhancing the safety and robustness of these models. This paper investigates the intricate consequences of such modifications through model editing, uncovering a complex relationship between enhancing model accuracy and preserving its ethical integrity. Our in-depth analysis reveals a striking paradox: while injecting accurate information is crucial for model reliability, it can paradoxically destabilize the model's foundational framework, resulting in unpredictable and potentially unsafe behaviors. Additionally, we propose a benchmark dataset NicheHazardQA to investigate this unsafe behavior both within the same and cross topical domain. This aspect of our research sheds light on how the edits, impact the model's safety metrics and guardrails. Our findings show that model editing serves as a cost-effective tool for topical red-teaming by methodically applying targeted edits and evaluating the resultant model behavior.
Hybrid functional verification and debug systems which combine high execution speed of logic emulators and full observability and controllability of software simulators are widely used, but suffer ...from scalability problem since software simulators cannot handle large and complex System-on-chip (SoC) designs efficiently, restricting their application to only relatively small designs. This paper presents a completely scalable hybrid verification and debug system based on dynamically reconfigurable co-simulation. Unlike existing systems, it allows one or more component logic blocks of a SoC to run on simulator for debugging while rest of the design still runs on emulator. The full design under test (DUT) is run on emulator at near hardware speed for long test sequences, and on error detection one or more logic blocks are transparently switched over to simulation for debugging, initializing the system as a piecewise co-simulator. Logic blocks can be flexibly relocated between simulator and emulator dynamically, without going through time consuming design recompilation phase, allowing designers to quickly debug functional issues. Application of the system to verification of real complex designs shows the effectiveness of our approach.
Community Question Answering (CQA) platforms steadily gain popularity as they provide users with fast responses to their queries. The swiftness of these responses is contingent on a mixture of ...query-specific and user-related elements. This paper scrutinizes these contributing factors within the context of six highly popular CQA platforms, identified through their standout answering speed. Our investigation reveals a correlation between the time taken to yield the first response to a question and several variables: the metadata, the formulation of the questions, and the level of interaction among users. Additionally, by employing conventional machine learning models to analyze these metadata and patterns of user interaction, we endeavor to predict which queries will receive their initial responses promptly.
Quantitative Comparison of Path Planning Algorithms in Simulated Environment Shekhar, Shashi; Vaishnav, Ram; Kumari, Ankita ...
2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA),
2024-March-15
Conference Proceeding
Path planning algorithms play a pivotal role in autonomous navigation systems across various domains, from robotics to self-driving vehicles. This research undertakes an extensive quantitative ...analysis, comparing various notable path planning algorithms in a simulated setting. The evaluated algorithms includes D*, A*, Dijkstra, and Rapidly Exploring Random Tree (RRT). We assess and contrast these algorithms using various metrics related to accuracy. The simulation environment in Matlab is designed to mimic real-world scenarios, incorporates obstacles. Performance metrics such as path length, travel time, and battery consumption in finding optimal paths are systematically measured and analyzed for each algorithm under identical condition. Through rigorous experimentation and statistical analysis, this research identifies the strengths and weaknesses of each algorithm in handling different environmental complexities. Results demonstrates that A* path planning method performs better than the other methods.
PDF
