Adding Value to Secondary Aluminum Casting Alloys: A Review on Trends and Achievements.

Aluminum is a critical element of the circular economy as it can be recycled several times. Moreover, Al recycling is a more economically and environmentally efficient procedure than the primary Al production from ores. Secondary aluminum alloys are mostly used in casting applications since it is possible to accommodate their chemical composition through secondary manufacturing processes.

Knee positioning systems for X-ray environment: a literature review.

The knee is one of the most stressed joints of the human body, being susceptible to ligament injuries and degenerative diseases. Due to the rising incidence of knee pathologies, the number of knee X-rays acquired is also increasing. Such X-rays are obtained for the diagnosis of knee injuries, the evaluation of the knee before and after surgery, and the monitoring of the knee joint's stability.

Bladder Wall Stiffness after Cystectomy in Bladder Cancer Patients: A Preliminary Study.

Bladder cancer (BlCa), specifically urothelial carcinomas, is a heterogeneous disease that derives from the urothelial lining. Two main classes of BlCa are acknowledged: the non-muscle invasive BlCa and the muscle-invasive BlCa; the latter constituting an aggressive disease which invades locally and metastasizes systemically. Distinguishing the specific microenvironment that cancer cells experience between mucosa and muscularis propria layers can help elucidate how these cells acquire invasive capacities.

Lock-In Thermal Test Simulation, Influence, and Optimum Cycle Period for Infrared Thermal Testing in Non-Destructive Testing.

Lock-in thermal tests (LTTs) are one of the best ways to detect defects in composite materials. The parameter that most affects their performance is the cycle period of the stimulation wave. Its influence on the amplitude-phase results was determined by performing various numeric simulations and laboratory tests.

Impact Fatigue Life of Adhesively Bonded Composite-Steel Joints Enhanced with the Bi-Adhesive Technique.

One of the most common loading conditions that bonded joints experience in service is repeated impact. Despite the destructive effects of impact fatigue, the behavior of metal-composite bonded joints subjected to repeated impact loads has rarely been studied in the literature. Therefore, it is of utmost importance to pay attention to this phenomenon on the one hand and to find solutions to improve the impact fatigue life of bonded composite metal components on the other hand.

The Effect of Ultrasonic Agitation on the Seedless Growth of Cu on Ru-W Thin Films.

Ru attracted considerable attention as a candidate to replace TaN as a diffusion barrier layer for Cu interconnect metallisation. The addition of W improves the diffusion barrier properties of Ru but appears to weaken the adhesion strength between the barrier and Cu and the direct (seedless) electroplatability behaviour. Although Cu can be directly electroplated on near equimolar Ru-W thin films, no complete substrate coverage is obtained.

A 3D printed hydrogel to promote human keratinocytes' spheroid-based growth.

Tissue engineering uses cells and biomaterials to develop bioartificial tissue substitutes for different purposes. For example, although several skin models have been developed for pharmaceutical and cosmetic research and skin wound healing, there are few studies on 3D cultures of keratinocytes in 3D printed scaffolds. So, this work aimed to develop a 3D-printed hydrogel scaffold to promote human keratinocyte growth.

Loading Rate and Temperature Interaction Effects on the Mode I Fracture Response of a Ductile Polyurethane Adhesive Used in the Automotive Industry.

Due to their high elongation at failure and damping capacity, polyurethanes are one of the main types of adhesives used in automotive structures. However, despite the wide range of applications of adhesives, their fracture mechanics behavior is still poorly studied in the literature, especially when both the loading rate and ambient temperature change. Accordingly, the main aim of the current work is to deal with the research gap.

Impact of in vitro findings on clinical protocols for the adhesion of CAD-CAM blocks: A systematic integrative review and meta-analysis.

Statement Of Problem: Computer-aided design and computer-aided manufacturing (CAD-CAM) blocks have evolved rapidly, making it difficult to establish the best clinical protocol for bonding a given block and whether an established protocol is appropriate for a newly introduced product.

Purpose: This integrative systematic review and meta-analysis aimed to clarify whether the clinician can select the most efficient adhesion protocols for CAD-CAM blocks by reading published in vitro studies and implementing them in daily practice.

Material And Methods: Based on the population, intervention, comparison, and outcome (PICO) strategy, 3 databases were searched for in vitro studies, randomized clinical trials, prospective or retrospective studies, and case reports from January 1, 2015, to July 31, 2021.

Artificial Intelligence and Anorectal Manometry: Automatic Detection and Differentiation of Anorectal Motility Patterns-A Proof-of-Concept Study.

Introduction: Anorectal manometry (ARM) is the gold standard for the evaluation of anorectal functional disorders, prevalent in the population. Nevertheless, the accessibility to this examination is limited, and the complexity of data analysis and report is a significant drawback. This pilot study aimed to develop and validate an artificial intelligence model to automatically differentiate motility patterns of fecal incontinence (FI) from obstructed defecation (OD) using ARM data.

Experimental and Numerical Study of Thermal Residual Stresses on Multimaterial Adherends in Single-Lap Joints.

The presence of residual stresses in composite materials can significantly affect material performance, especially when integrated in bonded joints. These stresses, often generated during the cure process, can cause cracking and distortion of the material, and are caused by differences in the coefficients of thermal expansion or cure shrinkage. In the current research, multimaterial adherends combining carbon-fibre-reinforced polymer (CFRP) and aluminium in a single-lap joint (SLJ) configuration are analysed, allowing us to understand the effect of the thermal residual stresses, developed during the curing process, in the overall performance of the joints.

A systematic review of ventilation conditions and airborne particulate matter levels in urban offices.

Many working activities are carried out in office buildings that are located in urban areas. Several studies have shown that these workplaces are likely to present poor indoor environmental quality (IEQ) due to inadequate ventilation rates, compromised thermal comfort conditions, and/or high concentration of air pollutants, such as particulate matter. This study aimed to review ventilation conditions, based on carbon dioxide (CO ) concentrations, and indoor airborne particulate matter (PM and PM ) levels assessed in offices worldwide.

A Miniaturized Device Coupled with Digital Image Correlation for Mechanical Testing.

Miniaturized mechanical testing based on small sample testing technology is a powerful technique to characterize the mechanical properties of different materials, and it is being used in different application fields. However, the small size of the specimens poses several challenges because the results are highly sensitive to measurement accuracy and the corresponding mechanical properties can change substantially due to the so-called specimen size effect. In this work, a novel testing device based on miniaturized specimens is presented.

An Experimental Analysis of the High-Cycle Fatigue Fracture of H13 Hot Forging Tool Steels.

In this study, the axial fatigue behaviour of hot forging tool steels at room temperature was investigated. Fatigue tests were performed on two steels within the same H13 specification. The fatigue tests were carried out in the high-cycle fatigue domain under normal conditions.

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps.

Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain-computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators.

Advanced Characterization of Adhesive Joints and Adhesives.

Structural adhesives have shown significant improvements in their behavior over the past few decades [...

Artificial intelligence and colon capsule endoscopy: Automatic detection of ulcers and erosions using a convolutional neural network.

Background And Aim: Colon capsule endoscopy (CCE) has become a minimally invasive alternative for conventional colonoscopy. Nevertheless, each CCE exam produces between 50 000 and 100 000 frames, making its analysis time-consuming and prone to errors. Convolutional neural networks (CNNs) are a type of artificial intelligence (AI) architecture with high performance in image analysis.

A Study on a Cast Steel Reinforced with WC-Metal Matrix Composite.

This study seeks to investigate the local reinforcement of low carbon cast steel specimens with WC-metal matrix composites (WC-MMCs), to obtain a new material effective in competing with hard alloy steels. For this purpose, a powder compact of tungsten carbide (WC) and iron (Fe) was prepared and placed in the mold cavity before casting. The reactions that occurred with the molten steel led to the formation of the WC-MMC and, consequently, to the local reinforcement of the steel.

Deep Learning for Automatic Differentiation of Mucinous versus Non-Mucinous Pancreatic Cystic Lesions: A Pilot Study.

Endoscopic ultrasound (EUS) morphology can aid in the discrimination between mucinous and non-mucinous pancreatic cystic lesions (PCLs) but has several limitations that can be overcome by artificial intelligence. We developed a convolutional neural network (CNN) algorithm for the automatic diagnosis of mucinous PCLs. Images retrieved from videos of EUS examinations for PCL characterization were used for the development, training, and validation of a CNN for mucinous cyst diagnosis.

Biodegradable Bone Implants as a New Hope to Reduce Device-Associated Infections-A Systematic Review.

Bone fractures often require fixation devices that frequently need to be surgically removed. These temporary implants and procedures leave the patient more prone to developing medical device-associated infections, and osteomyelitis associated with trauma is a challenging complication for orthopedists. In recent years, biodegradable materials have gained great importance as temporary medical implant devices, avoiding removal surgery.

Artificial intelligence and high-resolution anoscopy: automatic identification of anal squamous cell carcinoma precursors using a convolutional neural network.

Background: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell cancer (ASCC) precursors. Although it is superior to other diagnostic methods, particularly cytology, the visual identification of areas suspected of having high-grade squamous intraepithelial lesions remains difficult. Convolutional neural networks (CNNs) have shown great potential for assessing endoscopic images.

Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations.

This article details the ESAFORM Benchmark 2021. The deep drawing cup of a 1 mm thick, AA 6016-T4 sheet with a strong cube texture was simulated by 11 teams relying on phenomenological or crystal plasticity approaches, using commercial or self-developed Finite Element (FE) codes, with solid, continuum or classical shell elements and different contact models. The material characterization (tensile tests, biaxial tensile tests, monotonic and reverse shear tests, EBSD measurements) and the cup forming steps were performed with care (redundancy of measurements).

Artificial Intelligence and Device-Assisted Enteroscopy: Automatic Detection of Enteric Protruding Lesions Using a Convolutional Neural Network.

Introduction: Device-assisted enteroscopy (DAE) plays a major role in the investigation and endoscopic treatment of small bowel diseases. Recently, the implementation of artificial intelligence (AI) algorithms to gastroenterology has been the focus of great interest. Our aim was to develop an AI model for the automatic detection of protruding lesions in DAE images.

Computational simulation of cellular proliferation using a meshless method.

Background And Objective: During cell proliferation, cells grow and divide in order to obtain two new genetically identical cells. Understanding this process is crucial to comprehend other biological processes. Computational models and algorithms have emerged to study this process and several examples can be found in the literature.