Sep 2026· journal of Health Research and Development· 0 citations· 26 references
TL;DR
The findings of the present study indicated that potential complications such as delayed union, nonunion, and osteomyelitis in the intramedullary nailing method are approximately comparable to those of the external fixator method.
Abstract
Background: Various statistics have reported the prevalence of nonunion following intramedullary nailing to be between 0.9% and 1.1%. Femoral shaft fractures typically should achieve union within three to six months after intramedullary nailing. This study aimed to determine the prevalence of nonunion in patients with femoral shaft fractures treated with intramedullary nailing at Fatemi Hospital, Ardabil. Methods: This descriptive-analytical study was conducted on 70 patients who presented to the orthopedic clinic of Fatemi Hospital, Ardabil, with a diagnosis of femoral shaft fracture and underwent intramedullary nailing surgery in 2023 (1402 Persian calendar). Using anteroposterior femoral radiographs, patients were categorized into one of five groups (0 to 4) according to the Winquist-Hansen classification. Additionally, data on fracture type and fracture line, as well as demographic variables including age and sex, were collected. Data were analyzed using SPSS 22 software with descriptive statistics, chi-square test, Fisher's exact test, and independent t-test. The significance level was set at 0.05. Results: In the present study, 70 patients with femoral shaft fractures with a mean age of 36.06 ± 13.5 years who underwent IM nailing surgery at Fatemi Hospital, Ardabil, participated. The prevalence of nonunion complication in femoral shaft fracture patients was 18.6%. A significant relationship was observed between fracture grade and nonunion complication. Conclusion: The findings of the present study indicated that potential complications such as delayed union, nonunion, and osteomyelitis in the intramedullary nailing method are approximately comparable to those of the external fixator method. On the other hand, the duration of hospitalization, time to union, and other complications were lower in the intramedullary nailing method.
LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into the software supply chain. We make four contributions to this problem. First, we show that prior evaluation methodologies systematically inflate hallucination rates by misclassifying standard-library modules as hallucinations in some languages. For Python, the overestimation reaches 9.4 percentage points. Second, we evaluate seven inference-time defenses for mitigating package hallucinations, including five guided decoding strategies (Greedy, Contrastive, DoLa, Nudging, and Active Layer-Contrastive Decoding), an iterative self-refinement approach (Self-Refine), and a Retrieval-Augmented Generation (RAG)-based defense.. Across eight models spanning five families and four programming languages (Python, JavaScript, Ruby, Rust), RAG reduces the package hallucination rate (PHR) in 18 of 32 model--language configurations. Third, we introduce Package Utility (PU) to assess whether defenses preserve valid and task-relevant recommendations. Among strategies evaluated, Greedy decoding provides the strongest average mitigation--utility trade-off. Fourth, we stress-test all strategies under adversarial prompts seeded with fabricated package names and find that PHR surges by up to 45 percentage points relative to standard prompts, with Ruby consistently the most vulnerable language (80.9--95.2\%). Under adversarial conditions, RAG and Self-Refine outperform all decoding-only strategies, indicating that robust defense requires either external grounding or iterative self-verification when prompts are actively hostile. Our results recast package hallucination as both a measurement problem and a decoding-time control problem, and they demonstrate that the choice of defense must be matched to the threat model and recommendation utility.
Albérick Euraste Djiré, Iyiola E. Olatunji, Melissa Tessa et al.· 1 citation
MAGE explains how externalized knowledge, bounded action, independent evaluation, and retained human authority can compose into a governed engineering environment, and proposes tests of when that environment turns commodity intelligence into durable engineering progress.
James C. Davis, Kelechi G. Kalu, Huiyun Peng et al.· 1 citation
An audit-and-placebo protocol is proposed that separates verifier artifacts, interaction scaffolding, and grounded feedback credit in evaluations of self-evolving test generators in evaluations of self-evolving test generators.
Yunhao Liang, Chengguang Gan, Ruixuan Ying et al.· 0 citations
This study presents a landslide susceptibility assessment using multiple parameters by integrating remote sensing, GIS, and field observations in the Jammu and Kashmir region. Eight contributing variables were selected for landslide susceptibility analysis: Land Use and Land Cover (LULC), proximity to roads, streams, slope gradient, slope orientation (aspect), geology, geomorphology, and elevation. In addition, an extensive landslide inventory consisting of 669 landslide events was developed using the Field Landslide Inventory Mapping (FLIM) application, LISS-IV satellite data, and field observations, covering an area of 42,950.43 km². Landslide susceptibility mapping (LSM) was carried out using the Analytical Hierarchy Process (AHP) approach and validated with MaxEnt software and field-generated landslide data. The resulting landslide susceptibility map was classified into five categories: very high, high, medium, low, and very low susceptibility zones. Based on the AHP approach, these zones cover 3.65% (1,569.0483 km²), 24.43% (10,492.8912 km²), 51.56% (22,147.2369 km²), 18.81% (8,079.2199 km²), and 1.54% (662.0301 km²) of the study area, respectively. The weighted overlay and MaxEnt models proved effective for landslide vulnerability mapping, with MaxEnt achieving AUC values of 0.82 for training data and 0.807 for testing data, indicating good predictive performance. Field validation further showed that 87% of landslides occurred within high and very high susceptibility zones. The Jackknife test identified road proximity, slope, and stream proximity as the most significant independent variables influencing landslide occurrence. The generated landslide susceptibility map provides important insights for reducing landslide risk and serves as a valuable tool for infrastructure planning, community development, and disaster management in the region.
A. S. Jasrotia, Amit Sharma, I. C. Das et al.· Scientific Reports· 0 citations
This prototype MRG image translocation software was helpful to 69% of patients with binocular diplopia, but limited by large angle strabismus because of the limited instrument field of view.
Edsel B Ing, Kevin Sha, Sarosh Dandoti et al.· Journal of neuro-ophthalmolo...· 0 citations
A diagnostic support system based on a unified web platform that classifies patients according to the risks of developing three diseases based on regularly collected clinical or audio data using classical supervised learning algorithms is presented.
Vedamurthy D R, Dr. Anup Ritti, A. Bibi et al.· International Journal for Re...· 0 citations
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