Mastoid Cyst in a Child.

Mastoid cysts are a rare condition that occurs either congenitally or secondary to chronic otological diseases with poor ventilation of the middle ear and mastoid cavity. In this presenting case, the authors report a case of secondary mastoid cyst with evidence of bony destruction and fistulous tract formation into adjacent structures. Concurrently, we reviewed other similar cases reported in the literature. A 12-year-old Malay boy with partially controlled allergic rhinitis presented with right-sided postauricular swelling and intermittent fever for three months. Examination revealed a non-tender bony swelling over the mastoid area. High-resolution computed tomography of the temporal bone revealed a large bony lytic lesion at the inferior aspect of the mastoid bone. Multidirectional fistulous tracts towards the splenius capitis muscle were seen extending from the lesion. Right mastoid exploration was done and revealed an infected mastoid cyst. Complete removal of the cyst wall and saucerization of the mastoid cavity were performed. Our patient showcases the potential of mastoid cysts to cause bony erosion, fistulation and abscess formation. Complete removal of mastoid cysts is therefore advocated to prevent its potential complications and unwarranted recurrence.

Acquired Hemophilia A: Rare Cause of Upper Airway Hematoma and a Literature Review.

BACKGROUND: Acquired hemophilia A (AHA) is a rare blood disorder with high morbidity and even mortality as severe bleeding can occur in up to 90% of affected patients. Unlike congenital hemophilia which presents with intra-articular bleeding, acquired hemophilia causes bleeding into the skin, muscle, mucous membranes and soft tissues. CASE PRESENTATION: We report an unusual case of upper airway hematoma in a 61-year-old man who presented with acute onset dysphagia and shortness of breath. There were bruises on his neck and blood clots on the floor of mouth when he was examined. Endoscopic examination revealed an extensive laryngeal hematoma. A prolonged activated partial thromboplastin time (APTT) prompted us to investigate for factor VIII deficiency leading to the diagnosis of AHA. He recovered completely after a treatment regime instituted by the hematology team without suffering any grave debilitating events. CONCLUSION: AHA with laryngeal hematoma is a rare condition with only a handful of cases reported. Although a life-threatening disease, it is easily reversed with early recognition and administration of medical therapy involving the hematology team.

Intrinsic and Extrinsic Tunability of Double-Network Hydrogel Strength and Lubricity.

Double-network (DN) hydrogels are promising materials for tissue engineering due to their biocompatibility, high strength, and toughness, but understanding of their microstructure-property relationships still remains limited. This work investigates a DN hydrogel comprising a physically crosslinked agarose, as the first network, and a chemically crosslinked copolymer with a varying ratio of acrylamide and acrylic acid, as the second network. The charge, intrinsic to most DN hydrogels, introduces a responsive behavior to chemical and electrical stimuli. The DN strengthens agarose hydrogels, but the strengthening decreases with the swelling ratio resulting from increasing acrylic acid content or reducing salt concentration. Through careful imaging by atomic force microscopy, the heterogenous surface structure and properties arising from the DN are resolved, while the lubrication mechanisms are elucidated by studying the heterogeneous frictional response to extrinsic stimuli. This method reveals the action of the first (agarose) network (forming grain boundaries), copolymer-rich and poor regions (in grains), charge and swelling in providing lubrication. Friction arises from the shear of the polymeric network, whereas hydrodynamic lift and viscoelastic deformation become more significant at higher sliding velocities. We identify the copolymer-rich phase as the main source of the stimulus-responsive behavior. Salt concentration enhances effective charge density and reduces viscoelastic deformation, while electric bias swells the gel and improves lubrication. This work also demonstrates the dynamic control of interfacial properties like hydrogel friction and adhesion, which has implications for other areas of study like soft robotics and tissue replacements.

AI-Enabled Mosquito Surveillance and Population Mapping Using Dragonfly Robot.

Mosquito-borne diseases can pose serious risks to human health. Therefore, mosquito surveillance and control programs are essential for the wellbeing of the community. Further, human-assisted mosquito surveillance and population mapping methods are time-consuming, labor-intensive, and require skilled manpower. This work presents an AI-enabled mosquito surveillance and population mapping framework using our in-house-developed robot, named 'Dragonfly', which uses the You Only Look Once (YOLO) V4 Deep Neural Network (DNN) algorithm and a two-dimensional (2D) environment map generated by the robot. The Dragonfly robot was designed with a differential drive mechanism and a mosquito trapping module to attract mosquitoes in the environment. The YOLO V4 was trained with three mosquito classes, namely Aedes aegypti, Aedes albopictus, and Culex, to detect and classify the mosquito breeds from the mosquito glue trap. The efficiency of the mosquito surveillance framework was determined in terms of mosquito classification accuracy and detection confidence level on offline and real-time field tests in a garden, drain perimeter area, and covered car parking area. The experimental results show that the trained YOLO V4 DNN model detects and classifies the mosquito classes with an 88% confidence level on offline mosquito test image datasets and scores an average of an 82% confidence level on the real-time field trial. Further, to generate the mosquito population map, the detection results are fused in the robot's 2D map, which will help to understand mosquito population dynamics and species distribution.

Remote drain inspection framework using the convolutional neural network and re-configurable robot Raptor.

Drain blockage is a crucial problem in the urban environment. It heavily affects the ecosystem and human health. Hence, routine drain inspection is essential for urban environment. Manual drain inspection is a tedious task and prone to accidents and water-borne diseases. This work presents a drain inspection framework using convolutional neural network (CNN) based object detection algorithm and in house developed reconfigurable teleoperated robot called 'Raptor'. The CNN based object detection model was trained using a transfer learning scheme with our custom drain-blocking objects data-set. The efficiency of the trained CNN algorithm and drain inspection robot Raptor was evaluated through various real-time drain inspection field trial. The experimental results indicate that our trained object detection algorithm has detect and classified the drain blocking objects with 91.42% accuracy for both offline and online test images and is able to process 18 frames per second (FPS). Further, the maneuverability of the robot was evaluated from various open and closed drain environment. The field trial results ensure that the robot maneuverability was stable, and its mapping and localization is also accurate in a complex drain environment.

False Ceiling Deterioration Detection and Mapping Using a Deep Learning Framework and the Teleoperated Reconfigurable 'Falcon' Robot.

Periodic inspection of false ceilings is mandatory to ensure building and human safety. Generally, false ceiling inspection includes identifying structural defects, degradation in Heating, Ventilation, and Air Conditioning (HVAC) systems, electrical wire damage, and pest infestation. Human-assisted false ceiling inspection is a laborious and risky task. This work presents a false ceiling deterioration detection and mapping framework using a deep-neural-network-based object detection algorithm and the teleoperated 'Falcon' robot. The object detection algorithm was trained with our custom false ceiling deterioration image dataset composed of four classes: structural defects (spalling, cracks, pitted surfaces, and water damage), degradation in HVAC systems (corrosion, molding, and pipe damage), electrical damage (frayed wires), and infestation (termites and rodents). The efficiency of the trained CNN algorithm and deterioration mapping was evaluated through various experiments and real-time field trials. The experimental results indicate that the deterioration detection and mapping results were accurate in a real false-ceiling environment and achieved an 89.53% detection accuracy.

The effects of phthalate and nonylphenol exposure on body size and secondary sexual characteristics during puberty.

BACKGROUND: Some phthalic acid esters (PAEs) and nonylphenol (NP) are endocrine-disrupting chemicals (EDCs) that are widely used in consumer products. Consequently, the general population is exposed simultaneously to both groups of chemicals. OBJECTIVE: To investigate the single- and co-exposure effects of PAEs (DMP, DEP, DnBP, DiBP, BBzP, and DEHP) and NP on obesity and pubertal maturity to compare the body sizes of general adolescents with the complainants of the phthalate-tainted foods scandal that occurred in Taiwan. METHODS: This study included 270 general adolescents aged 6.5-15.0 years and 38 complainants aged 6.5-8.5 years. Nine metabolites of the five PAEs and of NP were measured in urine. We used a questionnaire to evaluate pubertal maturity, measured anthropometric indices (APs) to assess body size, and collected urine samples to measure the two groups of chemicals. RESULTS: We found that urinary PAE metabolite concentrations (specifically, metabolites of DEP, DnBP, DiBP, and DEHP) were positively associated with the APs for abdominal obesity (including skinfold thickness, waist circumference, waist-to-height ratio, and waist-to-hip) and indicated a dose-response relationship. Mono-methyl phthalate (MMP) exposure was inversely associated with pubarche among boys. The daily intake of DEHP in general adolescents exceeded the reference doses (RfD-20 µg/kgbw/day) and tolerable daily intake (TDI-50 µg/kgbw/day) by 3.4% and 0.4%, respectively. No associations were observed between NP exposure or co-exposure and the APs or pubertal maturity. No significant differences were observed between general adolescents and the complainants with regard to weight, height, or BMI. CONCLUSIONS: The study suggests that PAE (specifically, DEP, DnBP, DiBP, and DEHP) exposure is associated with abdominal obesity in adolescents and that the APs for abdominal obesity are more sensitive than BMI for measuring obesity among adolescents. We suggest that the RfD and TDI for PAEs should be revised to provide sufficient protection.