Freeway Traffic Incident Detection from Cameras: A Semi-Supervised Learning Approach

Early detection of incidents is a key step to reduce incident related congestion. State Department of Transportation (DoTs) usually install a large number of Close Circuit Television (CCTV) cameras in freeways for traffic surveillance. In this study, we used semi-supervised techniques to detect traffic incident trajectories from the cameras. Vehicle trajectories are identified from the cameras using state-of-the-art deep learning based You Look Only Once (YOLOv3) classifier and Simple Online Realtime Tracking (SORT) is used for vehicle tracking. Our proposed approach for trajectory classification is based on semi-supervised parameter estimation using maximum-likelihood (ML) estimation. The ML based Contrastive Pessimistic Likelihood Estimation (CPLE) attempts to identify incident trajectories from the normal trajectories. We compared the performance of CPLE algorithm to traditional semi-supervised techniques Self Learning and Label Spreading, and also to the classification based on the corresponding supervised algorithm. Results show that approximately 14% improvement in trajectory classification can be achieved using the proposed approach

The role of matrix metalloproteinase-9 and its inhibitor TIMP-1 in burn injury: a systematic review

Matrix metalloproteinase-9 (MMP-9) and its endogenous inhibitor, tissue inhibitor of metalloproteinase-1 (TIMP-1), are key mediators of acute inflammation and regulators of the wound healing process. The aim of this systematic review was to determine the local and systemic involvement of the MMP-9/TIMP-1 system following burn injury. Two databases (Scopus and MEDLINE) were searched for all studies reporting MMP-9 and/or TIMP-1 after burn injury. Based on our eligibility criteria, we reviewed 24 studies involving 508 burns patients in 11 clinical studies and 367 animals in 13 preclinical studies. Local, systemic, and peripheral gene expression, protein levels and activity of MMP-9 and TIMP-1 were assessed. Increased MMP-9 was reported at the site of injury early after burn trauma in all studies, and remained elevated in non-healing wounds. Increased TIMP-1 expression in burn wounds occurred later than MMP-9, and was persistent in hypertrophic burn scars. Similar to local expression, systemic MMP-9 and TIMP-1 concentrations were significantly elevated after burn injury in response to upregulation of proinflammatory cytokines. While no association was found between systemic MMP-9 concentration and extent of injury or outcome, serum or plasma TIMP-1 showed good correlation with survival and burn severity. This review also found evidence of the MMP-9/TIMP-1 system contributing to secondary tissue damage distant from the burn site, including burn-associated musculoskeletal damage and acute lung injury. In addition, increased MMP-9 synthesis and activity in the brain after peripheral burn may lead to blood-brain barrier dysfunction and cerebral edema, a significant contributor to mortality. This systematic review provides an overview of the available evidence of the role of MMP-9 and TIMP-1 in burn injury pathophysiology and finds that TIMP-1 may be a promising biomarker in outcome prognostication of burns patients. Large-scale studies of both pediatric and adult burns patients with increased female representation and repeated sampling are recommended to validate the reliability of TIMP-1 as a prognostic marker following burn injury

Acute hemichorea associated with ipsilateral chronic subdural hematoma

Here we are describing left-sided hemichorea in a 71-year-old female which developed within 3 days without any history of weakness, unconsciousness, fever, headache, vomiting. She had a history of head trauma 5 year back. No abnormality was detected in routine blood investigations. Computed tomography revealed a left chronic subdural hematoma. Neurosurgical intervention in form of left temporal “burr hole” drainage was performed and the patient’s involuntary movements improved in the postoperative period.

Quantifying vehicle control from physiology in type 1 diabetes

Objective: Our goal is to measure real-world effects of at-risk driver physiology on safety-critical tasks like driving by monitoring driver behavior and physiology in real-time. Drivers with type 1 diabetes (T1D) have an elevated crash risk that is linked to abnormal blood glucose, particularly hypoglycemia. We tested the hypotheses that (1) T1D drivers would have overall impaired vehicle control behavior relative to control drivers without diabetes, (2) At-risk patterns of vehicle control in T1D drivers would be linked to at-risk, in-vehicle physiology, and (3) T1D drivers would show impaired vehicle control with more recent hypoglycemia prior to driving. Methods: Drivers (18 T1D, 14 control) were monitored continuously (4 weeks) using in-vehicle sensors (e.g., video, accelerometer, speed) and wearable continuous glucose monitors (CGMs) that measured each T1D driver’s real-time blood glucose. Driver vehicle control was measured by vehicle acceleration variability (AV) across lateral (AVY, steering) and longitudinal (AVX, braking/accelerating) axes in 45-second segments (N = 61,635). Average vehicle speed for each segment was modeled as a covariate of AV and mixed-effects linear regression models were used. Results: We analyzed 3,687 drives (21,231 miles). T1D drivers had significantly higher overall AVX, Y compared to control drivers (BX = 2.5 × 10−2 BY = 1.6 × 10−2, p \u3c 0.01)—which is linked to erratic steering or swerving and harsh braking/accelerating. At-risk vehicle control patterns were particularly associated with at-risk physiology, namely hypo- and hyperglycemia (higher overall AVX,Y). Impairments from hypoglycemia persisted for hours after hypoglycemia resolved, with drivers who had hypoglycemia within 2–3 h of driving showing higher AVX and AVY. State Department of Motor Vehicle records for the 3 years preceding the study showed that at-risk T1D drivers accounted for all crashes (N = 3) and 85% of citations (N = 13) observed. Conclusions: Our results show that T1D driver risk can be linked to real-time patterns of at-risk driver physiology, particularly hypoglycemia, and driver risk can be detected during and prior to driving. Such naturalistic studies monitoring driver vehicle controls can inform methods for early detection of hypoglycemia-related driving risks, fitness to drive assessments, thereby helping to preserve safety in at-risk drivers with diabetes

Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos

Recognizing the activities, causing distraction, in real-world driving scenarios is critical for ensuring the safety and reliability of both drivers and pedestrians on the roadways. Conventional computer vision techniques are typically data-intensive and require a large volume of annotated training data to detect and classify various distracted driving behaviors, thereby limiting their efficiency and scalability. We aim to develop a generalized framework that showcases robust performance with access to limited or no annotated training data. Recently, vision-language models have offered large-scale visual-textual pretraining that can be adapted to task-specific learning like distracted driving activity recognition. Vision-language pretraining models, such as CLIP, have shown significant promise in learning natural language-guided visual representations. This paper proposes a CLIP-based driver activity recognition approach that identifies driver distraction from naturalistic driving images and videos. CLIP's vision embedding offers zero-shot transfer and task-based finetuning, which can classify distracted activities from driving video data. Our results show that this framework offers state-of-the-art performance on zero-shot transfer and video-based CLIP for predicting the driver's state on two public datasets. We propose both frame-based and video-based frameworks developed on top of the CLIP's visual representation for distracted driving detection and classification task and report the results.Comment: 15 pages, 10 figure

Network meta‐analysis comparing the outcomes of treatments for intermittent claudication tested in randomized controlled trials

Background: No network meta‐analysis has considered the relative efficacy of cilostazol, home exercise therapy, supervised exercise therapy (SET), endovascular revascularization (ER), and ER plus SET (ER+SET) in improving maximum walking distance (MWD) over short‐ (<1 year), moderate‐ (1 to <2 years), and long‐term (≥2 years) follow‐up in people with intermittent claudication. Methods and Results: A systematic literature search was performed to identify randomized controlled trials testing 1 or more of these 5 treatments according to Preferred Reporting Items for Systematic Review and Meta‐Analysis guidelines. The primary outcome was improvement in MWD assessed by a standardized treadmill test. Secondary outcomes were adverse events and health‐related quality of life. Network meta‐analysis was performed using the gemtc R statistical package. The Cochrane collaborative tool was used to assess risk of bias. Forty‐six trials involving 4256 patients were included. At short‐term follow‐up, home exercise therapy (mean difference [MD], 89.4 m; 95% credible interval [CrI], 20.9–157.7), SET (MD, 186.8 m; 95% CrI, 136.4–237.6), and ER+SET (MD, 326.3 m; 95% CrI, 222.6–430.6), but not ER (MD, 82.5 m; 95% CrI, −2.4 to 168.2) and cilostazol (MD, 71.1 m; 95% CrI, −24.6 to 167.9), significantly improved MWD (in meters) compared with controls. At moderate‐term follow‐up, SET (MD, 201.1; 95% CrI, 89.8–318.3) and ER+SET (MD, 368.5; 95% CrI, 195.3–546.9), but not home exercise therapy (MD, 99.4; 95% CrI, −174.0 to 374.9) or ER (MD, 84.2; 95% CrI, −35.3 to 206.4), significantly improved MWD (in meters) compared to controls. At long‐term follow‐up, none of the tested treatments significantly improved MWD compared to controls. Adverse events and quality of life were reported inconsistently and could not be meta‐analyzed. Risk of bias was low, moderate, and high in 4, 24, and 18 trials respectively. Conclusions: This network meta‐analysis suggested that SET and ER+SET are effective at improving MWD over the moderate term (<2 year) but not beyond this. Durable treatments for intermittent claudication are needed