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The paper presents a simultaneous interpreter professional competence that consists of three components – communicative, extralinguistic and procedural or specialized (sub)competences. It is focused on the third component, which includes the abilities of inferencing, probabilistic forecasting and compression, specifically required for simultaneous interpreting (SI). Inferencing is a two-staged process of retrieving assumptions with regards to composing invariant senses, which means deriving inferences of the message in the source language (SL) and generating implicatures in the target language (TL). Probabilistic forecasting is based on the analysis of the invariant sense prompts in the SL message and boils down to anticipating invariant sense evolvement in the context. It is closely related to compression – an ability to eliminate the redundant information and to condense the retrieved invariant sense in the SI for linguistic and extralinguistic reasons, such as interlanguage asymmetries between the source and target languages and an acute shortage of time because of the speaker’s speed. Moreover, compression is one of the key discursive strategies used by the simultaneous interpreter in speech production. These information processing abilities stand for the SI inherent cognitive features or mechanisms and cognitive-and-discursive strategies employed by the simultaneous interpreter in order to meet the pragmatic needs of a SI communicative situation. Descriptive, comparative, model simulation, introspection and observation methods were used for the research task realization. The outcomes of the study show that the above mentioned three cognitive mechanisms, discursive strategies and abilities closely interact in the SI; it is manifested through inferences and implicatures generated on the basis of presuppositions. Relying on his/her professional competence and employing discursive strategies of inferencing, probabilistic forecasting and compression, the simultaneous interpreter chooses the adequate language means to render invariant sense in its transition from the source to target languages. The choice is facilitated by presuppositional knowledge rooted in the worldview of the source and target languages, constituting the simultaneous interpreter’s language and conceptual thesauri. Another important factor assisting SI cognitive processes and the choice of discursive strategies is the analysis of text functions that makes it possible to elicit presuppositions helpful for inferencing and probabilistic forecasting.

This review, complemented by empirical investigations, delves into the intricate world of industrial powders, examining their elastic properties through diverse methodologies. The study critically assesses Young’s modulus (E) across eight different powder samples from various industries, including joint filler, wheat flour, wheat starch, gluten, glass beads, and sericite. Employing a multidisciplinary approach, integrating uniaxial compression methodologies—both single and cyclic—with vibration techniques, has revealed surprising insights. Particularly notable is the relationship between porosity and Young’s modulus, linking loose powders to the compacts generated under compression methods. Depending on the porosity of the powder bed, Young’s modulus can vary from a few MPa (loose powder) to several GPa (tablet), following an exponential trend. The discussion emphasizes the necessity of integrating various techniques, with a specific focus on the consolidation state of the powder bed, to achieve a comprehensive understanding of bulk elasticity. This underscores the need for low-consolidation methodologies that align more closely with powder technologies and unit operations such as conveying, transport, storage, and feeding. In conclusion, the study suggests avenues for further research, highlighting the importance of exploring bulk elastic properties in loose packing conditions, their relation with flowability, alongside the significance of powder conditioning.

Cast tungsten carbide (CTC) is a biphasic, pearlitic-like structure composed of WC lamellae in a matrix of W2C. Besides excellent flowability, spherical CTC powders exhibit superior hardness and wear resistance. Nevertheless, the available literature generally fails to explain the physical mechanisms behind such a phenomenon. In the present work, the microstructure and the mechanical properties of the novel centrifugally-atomized spherical CTC have been extensively investigated. This material exhibited an extremely fine microstructure, with WC lamellae of 27–29 nm in thickness and bulk lattice strains of 1.0–1.4 %, resulting in a microindentation hardness of 31.4 ± 1.6 GPa. The results of this study clearly show that centrifugally-atomized CTC is mechanically superior to both spheroidized CTC and conventional cast-and-crushed CTC. In addition, the effect of a series of heat treatments on the bulk fracture toughness and the fatigue life of entire CTC particles was also investigated. The reduction of residual stresses in the bulk of particles upon annealing dramatically increased the indentation fracture toughness, whereas the bulk microindentation hardness remained essentially unaffected. Regarding the fatigue life of entire particles under uniaxial cyclic compressive loading, local phase transformation phenomena at the surface of the particles upon heat treatment were concluded to play the most critical role. Indeed, the cumulative fatigue damage was minimized in surface-carburized CTC powders, where compressive stresses were induced at the outermost surface.

Introduction: In this study, we aim to describe the radiological characteristics of degenerative cervical kyphosis (DCK) with cervical spondylotic myelopathy (CSM) and discuss the relationship between DCK and the pathogenesis of spinal cord dysfunction. Methods: In total, 90 patients with CSM hospitalized in our center from September 2017 to August 2022 were retrospectively examined in this study; they were then divided into the kyphosis group and the nonkyphosis group. The patients' demographics, clinical features, and radiological data were obtained, including gender, age, duration of illness, cervical Japanese Orthopaedic Association (JOA) score, cervical lordosis (CL), height of intervertebral space, degree of wedging vertebral body, degree of osteophyte formation, degree of disc herniation, degree of spinal cord compression, and anteroposterior diameter of the spinal cord. In the kyphosis group, kyphotic segments, apex of kyphosis, and segmental kyphosis angle were recorded. Radiological characteristics between the two groups were also compared. Correlation analysis was performed for different spinal cord compression types. Results: As per our findings, the patients in the kyphosis group showed more remarkable wedging of the vertebral body, more severe anterior compression of the spinal cord, and a higher degree of disc herniation, while the posterior compression of the spinal cord was relatively mild when compared with the nonkyphosis group. CL was related to the type of spinal cord compression, as cervical kyphosis is an independent risk factor for anterior spinal cord compression. Conclusions: DCK might play a vital role in the pathogenesis of spinal cord dysfunction. In patients with DCK, it was determined that the anterior column is less supported, and more severe anterior spinal cord compression is present. The anterior approach is supposed to be preferred for CSM patients with DCK.

Abstract Conventional photography can only provide a two-dimensional image of the scene, whereas emerging imaging modalities such as light field enable the representation of higher dimensional visual information by capturing light rays from different directions. Light fields provide immersive experiences, a sense of presence in the scene, and can enhance different vision tasks. Hence, research into light field processing methods has become increasingly popular. It does, however, come at the cost of higher data volume and computational complexity. With the growing deployment of machine-learning and deep architectures in image processing applications, a paradigm shift toward learning-based approaches has also been observed in the design of light field processing methods. Various learning-based approaches are developed to process the high volume of light field data efficiently for different vision tasks while improving performance. Taking into account the diversity of light field vision tasks and the deployed learning-based frameworks, it is necessary to survey the scattered learning-based works in the domain to gain insight into the current trends and challenges. This paper aims to review the existing learning-based solutions for light field imaging and to summarize the most promising frameworks. Moreover, evaluation methods and available light field datasets are highlighted. Lastly, the review concludes with a brief outlook for future research directions.

Abstract The syncytiotrophoblast is a multinucleated structure that arises from fusion of mononucleated cytotrophoblasts, to sheath the placental villi and regulate transport across the maternal–fetal interface. Here, we ask whether the dynamic mechanical forces that must arise during villous development might influence fusion, and explore this question using in vitro choriocarcinoma trophoblast models. We demonstrate that mechanical stress patterns arise around sites of localized fusion in cell monolayers, in patterns that match computational predictions of villous morphogenesis. We then externally apply these mechanical stress patterns to cell monolayers and demonstrate that equibiaxial compressive stresses (but not uniaxial or equibiaxial tensile stresses) enhance expression of the syndecan-1 and loss of E-cadherin as markers of fusion. These findings suggest that the mechanical stresses that contribute towards sculpting the placental villi may also impact fusion in the developing tissue. We then extend this concept towards 3D cultures and demonstrate that fusion can be enhanced by applying low isometric compressive stresses to spheroid models, even in the absence of an inducing agent. These results indicate that mechanical stimulation is a potent activator of cellular fusion, suggesting novel avenues to improve experimental reproductive modelling, placental tissue engineering, and understanding disorders of pregnancy development.

Over the last few decades, researchers have devoted significant consideration to the use of nanoscale elements in concrete. Silicon dioxide nanoparticles (SDNs) have been a popular subject of study among the several types of nanoparticles. This article describes the findings of a laboratory investigation that examined the properties of ultra-lightweight foamed concrete (ULFC) including different proportions of SDNs. Wide range of the properties was evaluated specifically the slump flow, density, consistency, flexural strength, modulus of elasticity, compressive strength, split tensile strength, thermal properties, porosity, water absorption, sorptivity, intrinsic air permeability, and chloride diffusion. Additionally, the scanning electron microscopy (SEM) and pore distributions analyses of different mixes were done. Results confirmed a noticeable increase in the mechanical properties of ULFC, with respective improvements in the 28-day compressive, split tensile, and flexural strengths of up to 70.49%, 76.19%, and 51.51%, respectively, at 1.5% of the SDNs inclusion. However, further increases in the SDNs percentage did not result in remarkable enhancements. As the SDN percentage increased from 1.5% to 2.5%, the ULFC's sorptivity, porosity, water absorption, intrinsic air permeability, and chloride diffusion showed substantial improvements. When compared to the control sample, ULFC with SDNs demonstrated higher thermal conductivity values. The reason for this occurrence was determined to be the smaller pore size observed in the ULFC specimens containing SDNs. A great adjustment in the distribution of pore diameters was witnessed in the ULFC mixes when the percentages of SDNs were adjusted. The ULFC specimens, which included SDNs at the percentages of 0.5%, 1.0%, and 1.5%, indicated a reduction in the total number of large voids measuring 500 nm or more, compared to the control ULFC specimen. The findings of this study highlight the potential benefits of incorporating SDNs into ULFC, which may improve its overall properties.

Abstract Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud‐assisted health systems. Deduplication eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple duplicates. Delta compression is usually regarded as a complementary technique to deduplication to further remove the redundancy of similar blocks, but our observations indicate that this is disobedient when data have sparse duplicate blocks. In addition, there are many overlapped deltas in the resemblance detection process of post‐deduplication delta compression, which hinders the efficiency of delta compression and the index phase of resemblance detection inquires abundant non‐similar blocks, resulting in inefficient system throughput. Therefore, a multi‐feature‐based redundancy elimination scheme, called MFRE, is proposed to solve these problems. The similarity feature and temporal locality feature are excavated to assist redundancy elimination where the similarity feature well expresses the duplicate attribute. Then, similarity‐based dynamic post‐deduplication delta compression and temporal locality‐based dynamic delta compression discover more similar base blocks to minimise overlapped deltas and improve compression ratios. Moreover, the clustering method based on block‐relationship and the feature index strategy based on bloom filters reduce IO overheads and improve system throughput. Experiments demonstrate that the proposed method, compared to the state‐of‐the‐art method, improves the compression ratio and system throughput by 9.68% and 50%, respectively.

The Reinforced Concrete (RC) beams containing Expanded Polystyrene Beads (EPS) and Palm Oil Fuel Ash (POFA) as sand and cement replacement with a percentage between 10% and 30% were studied in terms of load-deflection behaviour. RC beam’s size was 1000×150×150 mm and simply supported at spaced 750 mm apart. The 10% of POFA without EPS shows a slight increase which is 0.26% higher than normal concrete in compressive strength. The ultimate load and flexural performance of RC beams with EPS and POFA exhibited a decreasing trend. All beams’ ultimate load exceeds the design value. The cracks of the RC beam may be classified as vertical flexural cracks, and some of the cracks can be classified as shear cracks based on the crack angle. As the percentage of EPS and POFA increases above 20% for all specimens, cracking starts to change to shear cracking.

Abstract In the ongoing battle against adversarial attacks, adopting a suitable strategy to enhance model efficiency, bolster resistance to adversarial threats, and ensure practical deployment is crucial. To achieve this goal, a novel four-component methodology is introduced. First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. Second, weight compression is applied to streamline the deep neural network (DNN) parameters, boosting the storage efficiency and accelerating inference. It also introduces complexity to deter potential attackers, enhancing model accuracy in adversarial settings. This study compresses the generative pre-trained transformer (GPT) by 65%, saving time and memory without causing performance loss. Compared to state-of-the-art methods, the proposed method achieves the lowest perplexity (14.28), the highest accuracy (93.72%), and an 8 × speedup in the central processing unit. The integration of the preceding two components involves the simultaneous training of multiple versions of the compressed GPT. This training occurs across various compression rates and different segments of a dataset and is ultimately associated with a novel multi-expert architecture. This enhancement significantly fortifies the model's resistance to adversarial attacks by introducing complexity into attackers' attempts to anticipate the model's prediction integration process. Consequently, this leads to a remarkable average performance improvement of 25% across 14 different attack scenarios and various datasets, surpassing the capabilities of current state-of-the-art methods.

Abstract This study investigates the strain softening behavior of high-performance fiber-reinforced cementitious composites (HPFRCCs) under uniaxial compression. HPFRCC mixtures with different compressive strengths ranged from 120 to 170 MPa were prepared. The measurement method of feedback control on loading rate based transverse displacement was applied. Stress–strain and stress−inelastic displacement curves were plotted and analyzed with the results in the literature. It was found that the post-peak energy absorption of HPFRCC considering inelastic deformation was about 3–7 times higher than conventional concrete. Based on the experimental results in the present work, fitting models on post-peak stress–strain/−displacement curves were considering for different aspect ratios proposed.

Abstract Magnetic resonance imaging is a medical imaging technique to create comprehensive images of the tissues and organs in the body. This study presents an advanced approach for storing and compressing neuroimaging informatics technology initiative files, a standard format in magnetic resonance imaging. It is designed to enhance telemedicine services by facilitating efficient and high-quality communication between healthcare practitioners and patients. The proposed downsampling approach begins by opening the neuroimaging informatics technology initiative file as volumetric data and then planning it into several slice images. Then, the quantization hiding technique will be applied to each of the two consecutive slice images to generate the stego slice with the same size. This involves the following major steps: normalization, microblock generation, and discrete cosine transformation. Finally, it assembles the resultant stego slice images to produce the final neuroimaging informatics technology initiative file as volumetric data. The upsampling process, designed to be completely blind, reverses the downsampling steps to reconstruct the subsequent image slice accurately. The efficacy of the proposed method was evaluated using a magnetic resonance imaging dataset, focusing on peak signal-to-noise ratio, signal-to-noise ratio, structural similarity index, and Entropy as key performance metrics. The results demonstrate that the proposed approach not only significantly reduces file sizes but also maintains high image quality.

The utilization of environmentally friendly materials derived from agricultural sources is becoming more prevalent in the construction industry. Many studies have already been conducted on various agro-resources, providing a variety of information on the characteristics of botanical aggregates and bio-based concrete. However, the prediction of the mechanical behavior of bio-based concrete remains complex owing to the various factors that influence its properties. Hence, it is crucial to collect a multitude of diverse information scattered throughout the literature regarding the mechanical response of bio-based materials under different loading conditions.This paper review aims to evaluate the mechanical behavior law and mechanical properties of bio-based concrete under various loadings (compression, flexion, and shear) in accordance with multi-plant-aggregates and different mineral binders. The literature has provided around 120 papers listing a compilation of 18 plant aggregates sourced from various origins that are utilized in plant-based concrete. On the other side, a few types of aggregates and binders were introduced in the literature regarding the mechanical behavior of bio-based concrete. Several factors can affect the mechanical properties of bio-based concrete at the composite scale such as the formulation, the casting process (energy), the curing conditions, the morphology of the aggregates, the density, the porosity, the mineral matrix properties, and particles/binder physicochemical interactions. Hence, this paper elaborates on a conceptual understanding that focuses on the mechanical response of bio-based concrete in relation to the various influencing factors up to the application of these materials in building sector.

Linen fibers exhibit good moisture management properties and can effectively conduct heat. However, there are limited studies on the sensorial comfort properties of linen knitted fabrics. In this study, the sensorial comfort properties of optical bleached, different enzyme washed and softened 100% cotton, 50% cotton/50% linen, and 100% linen fabrics were investigated using the Kawabata KES-FB evaluation system. The results showed that the tensile resilience and compression linearity values of the 100% linen fabrics were higher than those of other fabrics. The compression energy and compressional resilience of the 50% cotton- 50% linen fabrics were higher than those of the other fabrics. The surface friction value of 100% linen fabrics can be improved by cellulase enzyme treatment. Pectinase enzyme treated fabrics showed higher smoothness values than cellulase enzyme treated 100% linen fabrics.

The utility of nonsurgical, mechanical compression-based joint injury models to study osteoarthritis pathogenesis and treatments is increasing. Joint injury may be induced via cyclic compression loading or acute overloading to induce anterior cruciate ligament rupture. Models utilizing mechanical testing systems are highly repeatable, require little expertise, and result in a predictable onset of osteoarthritis-like pathology on a rapidly progressing timeline. In this chapter, we describe the procedures and equipment needed to perform mechanical compression-induced initiation of osteoarthritis in mice and rats.

Abstract: It has been proposed that semantic systems evolve under pressure for efficiency. This hypothesis has so far been supported largely indirectly, by synchronic cross-language comparison, rather than directly by diachronic data. Here, we directly test this hypothesis in the domain of color naming, by analyzing recent diachronic data from Nafaanra, a language of Ghana and Côte d’Ivoire, and comparing it with quantitative predictions derived from the mathematical theory of efficient data compression. We show that color naming in Nafaanra has changed over the past four decades while remaining near-optimally efficient, and that this outcome would be unlikely under a random drift process that maintains structured color categories without pressure for efficiency. To our knowledge, this finding provides the first direct evidence that color naming evolves under pressure for efficiency, supporting the hypothesis that efficiency shapes the evolution of the lexicon.

Rationale and objectivesOsteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic compression fractures (OCFs), an osteoporosis biomarker, are often incidental and under-reported. Accurate automated opportunistic OCF screening can increase the diagnosis rate and ensure adequate treatment. We aimed to develop a deep learning classifier for OCFs, a critical component of our future automated opportunistic screening tool.Materials and methodsThe dataset from the Osteoporotic Fractures in Men Study comprised 4461 subjects and 15,524 spine radiographs. This dataset was split by subject: 76.5% training, 8.5% validation, and 15% testing. From the radiographs, 100,409 vertebral bodies were extracted, each assigned one of two labels adapted from the Genant semiquantitative system: moderate to severe fracture vs. normal/trace/mild fracture. GoogLeNet, a deep learning model, was trained to classify the vertebral bodies. The classification threshold on the predicted probability of OCF outputted by GoogLeNet was set to prioritize the positive predictive value (PPV) while balancing it with the sensitivity. Vertebral bodies with the top 0.75% predicted probabilities were classified as moderate to severe fracture.ResultsOur model yielded a sensitivity of 59.8%, a PPV of 91.2%, and an F1 score of 0.72. The areas under the receiver operating characteristic curve (AUC-ROC) and the precision-recall curve were 0.99 and 0.82, respectively.ConclusionOur model classified vertebral bodies with an AUC-ROC of 0.99, providing a critical component for our future automated opportunistic screening tool. This could lead to earlier detection and treatment of OCFs.

Conventional photography can only provide a two-dimensional image of the scene, whereas emerging imaging modalities such as light field enable the representation of higher dimensional visual information by capturing light rays from different directions. Light fields provide immersive experiences, a sense of presence in the scene, and can enhance different vision tasks. Hence, research into light field processing methods has become increasingly popular. It does, however, come at the cost of higher data volume and computational complexity. With the growing deployment of machine-learning and deep architectures in image processing applications, a paradigm shift toward learning-based approaches has also been observed in the design of light field processing methods. Various learning-based approaches are developed to process the high volume of light field data efficiently for different vision tasks while improving performance. Taking into account the diversity of light field vision tasks and the deployed learning-based frameworks, it is necessary to survey the scattered learning-based works in the domain to gain insight into the current trends and challenges. This paper aims to review the existing learning-based solutions for light field imaging and to summarize the most promising frameworks. Moreover, evaluation methods and available light field datasets are highlighted. Lastly, the review concludes with a brief outlook for future research directions. [ABSTRACT FROM AUTHOR]

In today's era, digital data is being created and transmitted majorly in the form of images and videos. Storing such a huge number of images and transmitting them requires a lot of computer resources. Instead of storing the image data as is, if we compress and store it, it saves a lot of resources. Image compression is the act of removing the maximum possible redundant data from an image and maintaining only the non-redundant data. In this paper, to compress and decompress such big image data, a distributed environment with a map-reduce paradigm using Hadoop Distributed File System (HDFS) and Spark is used. In addition to these, Microsoft Azure cloud environment is also used. Various setups like a single system, 1 + 4, 1 + 15, and 1 + 18 node clusters are used to show the time comparisons among these setups with the self-created large image dataset. On these four self-made clusters, more than 200 million (219,340,800) images are compressed and decompressed; the execution times are compared with two of the traditional image compression methods: JPEG and CCITT Group-3. To evaluate the efficiency of these two compression methods: Compression Ratio, Root Mean Square Error (RMSE), and Peak Signal to Noise Ratios (PSNR) are used. [ABSTRACT FROM AUTHOR]

The syncytiotrophoblast is a multinucleated structure that arises from fusion of mononucleated cytotrophoblasts, to sheath the placental villi and regulate transport across the maternal–fetal interface. Here, we ask whether the dynamic mechanical forces that must arise during villous development might influence fusion, and explore this question using in vitro choriocarcinoma trophoblast models. We demonstrate that mechanical stress patterns arise around sites of localized fusion in cell monolayers, in patterns that match computational predictions of villous morphogenesis. We then externally apply these mechanical stress patterns to cell monolayers and demonstrate that equibiaxial compressive stresses (but not uniaxial or equibiaxial tensile stresses) enhance expression of the syndecan-1 and loss of E-cadherin as markers of fusion. These findings suggest that the mechanical stresses that contribute towards sculpting the placental villi may also impact fusion in the developing tissue. We then extend this concept towards 3D cultures and demonstrate that fusion can be enhanced by applying low isometric compressive stresses to spheroid models, even in the absence of an inducing agent. These results indicate that mechanical stimulation is a potent activator of cellular fusion, suggesting novel avenues to improve experimental reproductive modelling, placental tissue engineering, and understanding disorders of pregnancy development. [ABSTRACT FROM AUTHOR]

The mechanical properties of porcupine quills have attracted the interest of researchers due to their unique structure and composition. However, there is still a knowledge gap in understanding how these properties can be utilized to design biomimetic structures with enhanced performance. This study delves into the nanomechanical and macro-mechanical properties of porcupine quills, unveiling varied elastic moduli across different regions and cross sections. The results indicated that the elastic moduli of the upper and lower epidermis were higher at 8.13 ± 0.05 GPa and 7.71 ± 0.14 GPa, respectively, compared to other regions. In contrast, the elastic modulus of the mid-dermis of the quill mid-section was measured to be 7.16 ± 0.10 GPa. Based on the micro- and macro-structural analysis of porcupine quills, which revealed distinct variations in elastic moduli across different regions and cross sections, various biomimetic porous structures (BPSs) were designed. These BPSs were inspired by the unique properties of the quills and aimed to replicate and enhance their mechanical characteristics in engineering applications. Compression, torsion, and impact tests illustrated the efficacy of structures with filled hexagons and circles in improving performance. This study showed enhancements in maximum torsional load and crashworthiness with an increase in filled structures. Particularly noteworthy was the biomimetic porous circular structure 3 (BPCS_3), which displayed exceptional achievements in average energy absorption (28.37 J) and specific energy absorption (919.82 J/kg). Finally, a response surface-based optimization method is proposed to enhance the design of the structure under combined compression-torsion loads, with the goal of reducing mass and deformation. This research contributes to the field of biomimetics by exploring the potential applications of porcupine quill-inspired structures in fields such as robotics, drive shafts, and aerospace engineering. [ABSTRACT FROM AUTHOR]

Soft tissue injuries are common in the military, generally producing simple hematomas without the need for intensive evaluation and management. In certain situations, a shearing effect between fascial planes whereby a disruption of the vasculature and lymphatic systems creates a "closed degloving injury" is more generally referred to as a Morel-Lavallée Lesion (MLL). With a consistent pool of blood, lymph, and pieces of soft tissue, an M7LL can cause significant poor cosmesis, chronic pain, and risk secondary infection if left undetected and untreated. Proper diagnosis can be made through the effective use of ultrasound and, if detected early enough, through conservative measures to include needle aspiration and compression sleeves. Prior cases describe chronic MLLs existing for extended periods of time, in some cases years, requiring operative intervention, and in some cases poor outcomes. We present two cases of active duty soldiers presenting with seemingly innocuous injuries found on closer evaluation to have MLL, treated in one case with needle aspiration and compression, in the other with operative management. [ABSTRACT FROM AUTHOR]

Median arcuate ligament syndrome (MALS) involves coeliac artery compression, causing a range of symptoms from chronic pain to life-threatening complications. This case features a 52-year-old patient with recurrent retroperitoneal bleeding from MALS-related inferior pancreaticoduodenal artery aneurysms (PDAAs). Emergency interventions, including surgical bleeding control, angioplasty, percutaneous drainage, and median arcuate ligament release, were conducted. The case highlights challenges in diagnosing and managing MALS-related PDAA, emphasizing the importance of early identification and tailored interventions based on clinical symptoms and imaging. Surgical intervention to release the ligament is the primary treatment, with considerations for prophylactic intervention in PDAA cases. Lack of established PDAA management protocols underscores the need for prompt intervention to prevent complications. In conclusion, this report stresses the association between MALS and PDAA, advocating for early identification and tailored management to mitigate complications. [ABSTRACT FROM AUTHOR]

Thermal–mechanical coupling during the molding process can cause compressive yield in the polymer foam core and then affect the molding quality of the sandwich structure. This work investigates the compressive mechanical properties and failure mechanism of polymethacrylimide (PMI) foam in the molding temperature range of 20–120 °C. First, the DMA result indicates that PMI foam has minimal mechanical loss in the 20~120 °C range and can be regarded as an elastoplastic material, and the TGA curve further proves that the PMI foam is thermally stable within 120 °C. Then, the compression results show that compared with 20 °C, the yield stress and elastic modulus of PMI foam decrease by 22.0% and 17.5% at 80 °C and 35.2% and 31.4% at 120 °C, respectively. Meanwhile, the failure mode changes from brittle fracture to plastic yield at about 80 °C. Moreover, a real representative volume element (rRVE) of PMI foam is established by using Micro-CT and Avizo 3D reconstruction methods, and the simulation results indicate that PMI foam mainly shows brittle fractures at 20 °C, while both brittle fractures and plastic yield occur at 80 °C, and most foam cells undergo plastic yield at 120 °C. Finally, the simulation based on a single-cell RVE reveals that the air pressure inside the foam has an obvious influence of about 6.7% on the yield stress of PMI foam at 80 °C (brittle–plastic transition zone). [ABSTRACT FROM AUTHOR]

Mechanical properties of a material play a pivotal role in its performance when such porous material is used in a flow‐through mode. This study delves into the effect of porosity and microstructure on the compressibility of methacrylate polymer, focusing on two distinct microstructures: cauliflower and high internal phase emulsion. Samples with various porosities yet identical chemical composition were prepared and their Young's modulus was measured. The effect of porosity on Young's modulus was described by an exponential law model with the cauliflower microstructure exhibiting an exponent of 3.61, while the high internal phase emulsion of only 1.86. A mathematical analysis of the compression caused by a liquid flow unveiled significant disparities in the porosity threshold where minimal compression is observed, being around 0.45 for the cauliflower while there is monotone decrease in compression with porosity increase for the high internal phase emulsion microstructure. Evaluating exponent integer values between 1 and 5 over entire porosity range reveals that the porosity where the minimal compression occurs increases with a decrease in exponent value, being approximately 0.33 for n = 5, 0.4 for n = 4, 0.55 for n = 3, 0.65 for n = 2 while no minimum occurs for n = 1. These findings indicate that lower exponent value results in lower compression under identical experimental conditions. [ABSTRACT FROM AUTHOR]

The article focuses on the use of compression therapy in managing varicose veins, highlighting its efficacy in improving symptoms, reducing leg swelling, and enhancing quality of life for patients with chronic venous disease. Topics discussed include the indications for compression therapy, its role in different stages of varicose veins, and recommendations for its use before and after venous interventions.

Mainstream research on information theory within the field of living systems involves the application of analytical tools to understand a broad range of life processes. This paper is dedicated to an opposite problem: it explores the information theory and communication engineering methods that have counterparts in the data transmission process by way of DNA structures and neural fibers. Considering the requirements of modern multimedia, transmission methods chosen by nature may be different, suboptimal, or even far from optimal. However, nature is known for rational resource usage, so its methods have a significant advantage: they are proven to be sustainable. Perhaps understanding the engineering aspects of methods of nature can inspire a design of alternative green, stable, and low-cost transmission. [ABSTRACT FROM AUTHOR]

Study Design: Retrospective Cohort Study Objectives: Cervical radiculopathy and peripheral entrapment neuropathies often have overlapping symptoms that are difficult to distinguish on physical examination. Small-scale studies have attempted to report the incidence of this phenomenon, often called double crush syndrome (DCS), with varying results. The present study aims to determine the incidence of concomitant cervical radiculopathy and peripheral nerve compression and to determine if the DCS hypothesis, which states that compression of a nerve at one site leaves it more susceptible to compression at another, is valid. Methods: The PearlDiver database was queried from 2010 to 2020. The incidence of peripheral neuropathy in cervical radiculopathy was assessed. Propensity score matching was used to determine if patients with cervical radiculopathy were more likely to have peripheral nerve compression compared to controls, and vice versa, to test the DCS hypothesis. Results: The database contains records of 90,772 632 patients. The incidence of carpal tunnel syndrome (CTS) or peripheral ulnar nerve compression (PUnC) in cervical radiculopathy was 9.98% and 3.15%, respectively. The incidence of both carpal tunnel syndrome and PUnC in cervical radiculopathy was 1.84%. Patients with cervical radiculopathy were more likely than matched controls to have both CTS (P <.001) and PUnC (P <.001). Patients with CTS (P <.001) and with PUnC (P <.001) were more likely to have cervical radiculopathy than the control cohort. Conclusions: The incidence of DCS is reported. Patients with cervical radiculopathy are more likely than matched controls to have peripheral nerve compression, and vice versa, in support of the DCS hypothesis. [ABSTRACT FROM AUTHOR]

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3D modeling and reconstruction are critical to creating immersive XR experiences, providing realistic virtual environments, objects, and interactions that increase user engagement and enable new forms of content manipulation. Today, 3D data can be easily captured using off-the-shelf, specialized headsets; very often, these tools provide real-time, albeit low-resolution, integration of continuously captured depth maps. This approach is generally suitable for basic AR and MR applications, where users can easily direct their attention to points of interest and benefit from a fully user-centric perspective. However, it proves to be less effective in more complex scenarios such as multi-user telepresence or telerobotics, where real-time transmission of local surroundings to remote users is essential. Two primary questions emerge: (i) what strategies are available for achieving real-time 3D reconstruction in such systems? and (ii) how can the effectiveness of real-time 3D reconstruction methods be assessed? This paper explores various approaches to the challenge of live 3D reconstruction from typical point cloud data. It first introduces some common data flow patterns that characterize virtual reality applications and shows that achieving high-speed data transmission and efficient data compression is critical to maintaining visual continuity and ensuring a satisfactory user experience. The paper thus introduces the concept of saliency-driven compression/reconstruction and compares it with alternative state-of-the-art approaches. [ABSTRACT FROM AUTHOR]