A point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such as virtual reality and augmented reality. However, the point cloud, especially those representing dynamic scenes or objects in motion, must be compressed efficiently due to its huge data volume. The latest video-based point cloud compression (V-PCC) standard for dynamic point clouds divides the 3D point cloud into many patches using computationally expensive normal estimation, segmentation, and refinement. The patches are projected onto a 2D plane to apply existing video coding techniques. This process often results in losing proximity information and some original points. This loss induces artefacts that adversely affect user perception. The proposed method segments dynamic point clouds based on shape similarity and occlusion before patch generation. This segmentation strategy helps maintain the points\' proximity and retain more original points by exploiting the density and occlusion of the points. The experimental results establish that the proposed method significantly outperforms the V-PCC standard and other relevant methods regarding rate-distortion performance and subjective quality testing for both geometric and texture data of several benchmark video sequences.

As higher spatiotemporal resolution tactile sensing systems are being developed for prosthetics, wearables, and other biomedical applications, they demand faster sampling rates and generate larger data streams. Sparsifying transformations can alleviate these requirements by enabling compressive sampling and efficient data storage through compression. However, research on the best sparsifying transforms for tactile interactions is lagging. In this work we construct a library of orthogonal and biorthogonal wavelet transforms as sparsifying transforms for tactile interactions and compare their tradeoffs in compression and sparsity. We tested the sparsifying transforms on a publicly available high-density tactile object grasping dataset (548 sensor tactile glove, grasping 26 objects). In addition, we investigated which dimension wavelet transform-1D, 2D, or 3D-would best compress these tactile interactions. Our results show that wavelet transforms are highly efficient at compressing tactile data and can lead to very sparse and compact tactile representations. Additionally, our results show that 1D transforms achieve the sparsest representations, followed by 3D, and lastly 2D. Overall, the best wavelet for coarse approximation is Symlets 4 evaluated temporally which can sparsify to 0.5% sparsity and compress 10-bit tactile data to an average of 0.04 bits per pixel. Future studies can leverage the results of this paper to assist in the compressive sampling of large tactile arrays and free up computational resources for real-time processing on computationally constrained mobile platforms like neuroprosthetics.

Compression systems based electromechanical actuators require a good understanding of their dynamics for a better performance. This paper deals with the study of the nonlinear dynamics of an electromechanical system with two rotating arms subjected to a sinusoidal excitation for fluid compression purposes. The physical model integrating two balloons to be compressed by the arms alternately is presented and the mathematical equations traducing their dynamics are established. We emphasize on the influence of some control parameters namely the supply voltage, the discontinuity position and the viscoelastic ratio on the behaviour of the angular displacement of the arms. The study is also done by neglecting the inductance in the electrical part of the system. It is obtained that while the arms exhibit periodic motion during regular movement, compression of the balloons induces a shift to multi-periodic or chaotic dynamics, occasionally reverting to periodicity. Experimental and numerical simulation results demonstrate good agreement, with the R-system approximating more experimental outcomes than the RL-system. These findings hold significant implications for various environmental applications utilizing pump technology.

Remnant vascular grafts may result in significant neurological deficits owing to compression of adjacent neural structures. We report this finding in two cases after extracorporeal membrane oxygenation decannulation and removal of an arteriovenous fistula in the upper extremity. In both cases, removal of the graft, patch arteriotomy, and external neurolysis resulted in significant recovery of neurological function. We review the preoperative workup, diagnostic studies, and technical approach to treatment in an effort to increase recognition among vascular and cardiovascular surgeons and to demonstrate a safe and effective management option through a multidisciplinary approach.

Previous studies have shown that pharmaceutical agents such as lipoic acid have the ability to soften the lens, presenting a promising avenue for treating presbyopia. One obstacle encountered in the preclinical stage of such agents is the need for precise measurements of lens elasticity in experimental models. This study aimed to evaluate the effects of 25-hydroxycholesterol, lipoic acid, and obeticholic acid on the viscoelastic properties of mouse lenses using a custom-built elastometer system. Data were acquired on lenses from C57BL/6J female mice from two age groups: young (age: 8-10 weeks) and old (age: 32-43 weeks). OD lenses were used as the control and OS lenses were treated. Control lenses were immersed in Dulbecco\'s Modified Eagle Medium (DMEM) and treatment lenses were immersed in a compound solution containing 25-hydroxycholesterol (5 young and 5 old), lipoic acid at 2.35 mM (5 young and 5 old), lipoic acid at 0.66 mM (5 old), or obeticholic acid (5 old) at 37 °C for 18 h. After treatment, the mouse lenses were placed in a DMEM-filled chamber within a custom-built elastometer system that recorded the load and lens shape as the lens was compressed by 600 μm at a speed of 50 μm/s. The load was continuously recorded during compression and during stress-relaxation. The compression phase was fit with a linear function to quantify lens stiffness. The stress-relaxation phase was fit with a 3-term exponential relaxation model providing relaxation time constants (t1, t2, t3), and equilibrium load. The lens stiffness, time constants and equilibrium load were compared for the control and treated groups. Results revealed an increase in stiffness with age for the control group (young: 1.16 ± 0.11 g/mm, old: 1.29 ± 0.14 g/mm) and relaxation time constants decreased with age (young: t1 = 221.9 ± 29.0 s, t2 = 24.7 ± 3.8 s, t3 = 3.12 ± 0.87 s, old: t1 = 183.0 ± 22.0 s, t2 = 20.6 ± 2.6 s and t3 = 2.24 ± 0.43 s). Among the compounds tested, only 25-hydroxycholesterol produced statistically significant changes in the lens stiffness, relaxation time constants, and equilibrium load. In conclusion, older mouse lenses are stiffer and less viscous than young mouse lenses. Notably, no significant change in lens stiffness was observed following treatment with lipoic acid, contrary to previous findings.

UNASSIGNED: The ulnar\'s nerve compression at the Guyon\'s canal is not a frequent entity add to it that vascular lesions are rarely involved as a causative agent of this syndrome.
METHODS: We report a case of a young male patient admitted in our department for a Guyon\'s canal syndrome due to an aneurysm of the ulnar artery and underwent a surgical decompression. Post-operative course was uneventful and the patient was satisfied with the result.
UNASSIGNED: Many etiologies are involved in the Guyon\'s canal syndrome and these etiologies can be arranged into groups. Previous treatment attempts, the duration and severity of the symptoms and the underlying etiology dictate the treatment options. Adjacent vascular enlargement is not a usual cause of Guyon\'s canal compression and a few case reports were reported in the literature. Surgical treatment by opening and releasing the roof of Guyon\'s canal and removing the aneurysm helped to achieve good outcome in most reports.
CONCLUSIONS: Guyon\'s canal syndrome is less frequent than both cubital tunnel syndrome or carpal tunnel syndrome and many causative agents have been described. Vascular lesions are not the usual cause of compressing the ulnar nerve at the wrist and through this case we spotlighted this entity as another possible etiology requiring an adequate treatment for a better outcome.

High shear wet granulation (HSWG) is widely used in tablet manufacturing mainly because of its advantages in improving flowability, powder handling, process run time, size distribution, and preventing segregation. In line process analytical technology measurements are essential in capturing detailed particle dynamics and presenting real-time data to uncover the complexity of the HSWG process and ultimately for process control. This study presents an opportunity to predict the properties of the granules and tablets through torque measurement of the granulation bowl and the force exerted on a novel force probe within the powder bed. Inline force measurements are found to be more sensitive than torque measurements to the granulation process. The characteristic force profiles present the overall fingerprint of the high shear wet granulation, in which the evolution of the granule formation can improve our understanding of the granulation process. This provides rich information relating to the properties of the granules, identification of the even distribution of the binder liquid, and potential granulation end point. Data were obtained from an experimental high shear mixer across a range of key process parameters using a face-centred surface response design of experiment (DoE). A closed-form analytical model was developed from the DOE matrix using the discovery of evolutionary equations. The model is able to provide a strong predictive indication of the expected tablet tensile strength based only on the data in-line. The use of a closed form mathematical equation carries notable advantages over other AI methodologies such as artificial neural networks, notably improved interpretability/interrogability, and minimal inference costs, thus allowing the model to be used for real-time decision making and process control. The capability of accurately predicting, in real time, the required compaction force required to achieve the desired tablet tensile strength from upstream data carries the potential to ensure compression machine settings rapidly reach and are maintained at optimal values, thus maximising efficiency and minimising waste.

Hereditary neuropathy with liability pressure palsies (HNPP) is usually caused by compression and is an episodic, painless, recurrent hereditary neuropathy with focal motor and sensory involvement. It begins in adolescence and young adulthood. The most commonly affected nerves in HNPP are the ulnar, peroneal, radial, and median nerves. In this article, we present a 31-year-old female patient with a previously undescribed case of HNPP, which presented with wrist drop due to the trapping of the radial nerve in the spiral groove after the crow position in yoga.

As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand for greater bandwidth and computational resources can lead to greater infrastructural costs for healthcare providers and AI vendors. To that end, we developed ISLE, an intelligent streaming framework to address inefficiencies in current imaging infrastructures. Our framework draws inspiration from video-on-demand platforms to intelligently stream medical images to AI vendors at an optimal resolution for inference from a single high-resolution copy using progressive encoding. We hypothesize that ISLE can dramatically reduce the bandwidth and computational requirements for AI inference, while increasing throughput (i.e., the number of scans processed by the AI system per second). We evaluate our framework by streaming chest X-rays for classification and abdomen CT scans for liver and spleen segmentation and comparing them with the original versions of each dataset. For classification, our results show that ISLE reduced data transmission and decoding time by at least 92% and 88%, respectively, while increasing throughput by more than 3.72 × . For both segmentation tasks, ISLE reduced data transmission and decoding time by at least 82% and 88%, respectively, while increasing throughput by more than 2.9 × . In all three tasks, the ISLE streamed data had no impact on the AI system\'s diagnostic performance (all P > 0.05). Therefore, our results indicate that our framework can address inefficiencies in current imaging infrastructures by improving data and computational efficiency of AI deployments in the clinical environment without impacting clinical decision-making using AI systems.

The mechanical properties of textile materials play a crucial role in determining their comfort, functionality, performance, safety, and aesthetics. Understanding and optimizing these properties is essential to meet consumer demands. Key aspects of mechanical properties, such as surface roughness, abrasion resistance, and compression, have a significant impact on the touch and durability of the material, as demonstrated by various research studies. This study focuses on analyzing the mechanical properties of materials produced of different polymer yarns and their changes under combined aging factors. The findings emphasize the significance of textile abrasion resistance and surface roughness measurement, particularly for aged materials. Although the use of recycled polyester yarn is sustainable and offers advantages such as higher tensile strength, the results have shown that the use of conventional polyester yarn is more advantageous overall as it has higher abrasion resistance, a smoother surface texture, and better elasticity retention after aging. The insights presented are vital for designing high-performance sportswear, which is crucial in today\'s competitive environment.