Experimental and Numerical Study on Full-Scale Precast Steel Fibre-Reinforced Concrete Pipes

Reinforced concrete (RC) pipes are widely used as open channels (non-pressurized pipes) for sewage and storm water conveyance. RC pipes have generally achieved a reliable long-term performance. Depending on multiple parameters (e.g. pipe diameter, pipe wall thickness, required strength, etc.) the pipe may have up to three welded reinforcement cages in order to resist anticipated loads. Each cage is an assembled unit of steel reinforcement consisting of circumferential and longitudinal bars or wires. The fabrication process of a steel cage reinforcement is time and labour consuming. Thus, eliminating the steel cage reinforcement will yield an overall reduction in the production cost of precast concrete pipes. Dispersed steel fibres can be an effective alternative for the reinforcement of concrete pipes. The aim of this study is to explore using steel fibres as reinforcement in dry-cast concrete pipes. Mechanical properties of dry-cast steel-fibre reinforced concrete (DCSFRC) fabricated using multiple steel fibre types at various dosages were characterized. Consequently, precast pipes reinforced with Dramix RC-65/35-CN and Dramix RC-80/60-CN fibres at various dosages were fabricated. An extensive experimental program was carried out in order to evaluate the structural performance of the full-scale steel fibre-reinforced concrete (SFRC) pipes that were produced in comparison to plain concrete (PC) and RC pipes. Precast pipes had internal diameters of 300, 450, and 600 mm as well as a Type C wall thickness. The structural performance of pipes was characterized using both the continuous and cyclic three-edge-bearing tests (TEBT). Furthermore, the soil-pipe interaction of buried full-scale SFRC pipes was investigated. Finally, a three dimensional non-linear finite element model of the TEBT of SFRC pipes was developed. Subsequently, a parametric study covering multiple pipe configuration and reinforcement parameters was conducted. Results showed that hooked-end fibres with the largest fibre aspect ratio (Dramix RC-80/60-CN) induced the best flexural performance of DCSFRC specimens while crimped fibres (Novocon XR) were the least effective in enhancing the flexural strength and post-peak behaviour of DCSFRC. The load carrying capacity of SFRC pipes increased with increased fibre dosage. Results of the TEBT for 300 mm diameter pipes showed that the reinforcement specified for Class V pipes in ASTM C76 “Standard Specification For Reinforced Concrete Culvert, Storm Drain, And Sewer Pipe” could be achieved using a steel fibre dosage of 20 kg/m³, while a fibre dosage of 30 kg/m³ was sufficient for 450 and 600 mm diameter pipes to satisfy the same strength class (Class V). Furthermore, provided using a sufficient fibre dosage, SFRC pipes exhibited higher residual strengths and less deformations than that of RC pipes when subjected to small to moderate loading levels. In addition, results showed that using a hybrid system of short (Dramix RC-65/35-CN) and long (Dramix RC-80/60-CN) fibres did not result in synergetic effects. Full-scale testing results of buried SFRC pipes indicated that the pipes could sustain live loads consisting of a fully loaded 625CL Standard Ontario Truck without exhibiting any cracks or significant deformations, even when the pipe was installed in the least quality installation type (Type IV). This indicated that the current design recommendations for the pipe wall thickness in ASTM C76 (Type C wall) are overly conservative. Furthermore, it was found that the post-cracking behaviour of buried SFRC pipes was more sensitive to the installation type than to the type of steel fibre reinforcement. Finally, the findings of the parametric study were presented in a tabular form that can be used as a design aid supplementary to the newly released ASTM C1765 “Standard Specification for Steel Fiber Reinforced Concrete Culvert, Storm Drain, and Sewer Pipe”. The experimental findings of this study should assist the precast concrete industry in producing more economical SFRC pipe without the need for costly and time consuming welded steel cage reinforcement. The numerical and analytical study findings provided a simple and rational tool for the design of such SFRC pipes

Comparative study of the corrosion behaviour of conventional carbon steel and corrosion resistant reinforcing bars

Corrosion of reinforced concrete is the most challenging durability problem that threatens reinforced concrete structures, especially structures that are subject to severe environmental conditions (i.e., Highway Bridges, Marine structures, etc.). Corrosion of reinforcing steel leads to cracking and spalling of the concrete cover and billions of dollars are spent every year on repairing such damaged structures. New types of reinforcements have been developed in order to avoid these high cost repairs. Thus it is important to study the corrosion behavior of these new types of reinforcements and compare them to the traditional carbon steel reinforcements. This study aimed at characterizing the corrosion behavior of three competing reinforcing steels; conventional carbon steel, micro-composite steel (MMFX-2) and 316LN stainless steel, through experiments in carbonated and non-carbonated concrete exposed to chloride-laden environments. Synthetic pore water solutions have been used to simulate both cases of sound and carbonated concrete under chloride ions attack. A three electrode corrosion cell is used for determining the corrosion characteristics and rates. Multiple electrochemical techniques were applied using a Gamry PC4™ potentiostat manufactured by GAMRY INSTRUMENTS. DC corrosion measurements were applied on samples subjected to fixed chloride concentration in the solution. EIS measurements were applied on samples subjected to incremental chloride additions. Furthermore, carbon steel rebars embedded in concrete samples pre-contaminated with chloride ions added to the mix will be used to relate corrosion rates inside concrete to those obtained from synthetic solutions and to measure moisture content inside concrete using a nondestructive TDR-based technique

Cancer Patient Beliefs and Attitudes Regarding Immune Checkpoint Inhibitor Therapy

The development and widespread use of immune checkpoint inhibitors (ICIs) have advanced the field of oncology in a short period of time. Despite this, patient perception regarding this new medication class has not been adequately assessed, which may affect treatment decisions and adherence. The Belief about Medicines Questionnaire (BMQ) is a validated survey composed of 18 questions which analyzes patient’s beliefs about the necessity of prescribed medication and concern about the potential adverse events caused by the medication. General medication overuse and harm are also determined. This is the first study to utilize the BMQ for patients on ICI therapy

The Awareness of Clinical Doctors and Medical Students Toward Monkeypox in Jordan: A National Cross-Sectional Study

Background: Following the diagnosis of the first confirmed monkeypox case in Jordan in August 2022, the necessity for assessing the perceived knowledge among healthcare personnel has gained more significance. Given that the knowledge of healthcare professionals plays a great role in protection against newly emerging epidemics, we therefore in this study aim to assess the awareness of medical students and practicing physicians in Jordan toward the monkeypox virus. Method: This cross-sectional study was conducted in Jordan to assess medical students' attitudes, general practitioners, residents, and specialists regarding the monkeypox virus. Data from the WHO, CDC, and literature were used to design this questionnaire. The questionnaire comprises 53 questions divided into three sections: socio-demographic variables and work-related characteristics, general and specific knowledge about the monkeypox virus. Snowball sampling was employed since it was convenient. The data were analyzed using SPSS version 25.0. A p-value < 0.05 was considered statistical significance. Results: Four hundred twenty-three healthcare professionals participated in this study. Only 7.3% (n = 31) of respondents have ever received information about monkeypox during studies in medicine. Respectively, the mean and median knowledge scores were 12.77 and 13, ranging from 4 to 25. More than half (51.3%, n = 3012) have heard about monkeypox before. About 45.9% (n = 194) of respondents reported that they had heard about monkeypox a few days ago for the first time, while 48.7% (n = 206) heard it a month ago. Most participants had a low level of good knowledge of monkeypox. Only 2.1% of respondents had correctly identified the natural host and the incubation period of monkeypox. More than half (52.1%) correctly answered the sign and symptoms of monkeypox. Almost 49.2% of respondents believed that monkeypox and smallpox have similar signs and symptoms. Respondents aged more than 30 years had higher level of knowledge (COR = 19.45, 95% CI = 6.7683-55.8933, p< 0.001). Respondents who are specialist doctors had higher knowledge of monkeypox (COR = 7.3125, 95% CI = 1.6793-31.8429, p = 0.008) than others. Conclusion: Monkeypox awareness among Jordanian medical students and practitioners is low; hence immediate action should be taken to address this catastrophic problem. Consequently, learning about monkeypox and spreading information about its prevention is crucial. Furthermore, increasing Doctors' ability to react to human monkeypox cases and report them to a disease surveillance system will depend on their education about the sickness.   Keywords:  Jordan, Monkeypox, Clinicians, Medical Students, Knowledge

Neutrophil extracellular traps and long COVID

Post-acute COVID-19 sequelae, commonly known as long COVID, encompasses a range of systemic symptoms experienced by a significant number of COVID-19 survivors. The underlying pathophysiology of long COVID has become a topic of intense research discussion. While chronic inflammation in long COVID has received considerable attention, the role of neutrophils, which are the most abundant of all immune cells and primary responders to inflammation, has been unfortunately overlooked, perhaps due to their short lifespan. In this review, we discuss the emerging role of neutrophil extracellular traps (NETs) in the persistent inflammatory response observed in long COVID patients. We present early evidence linking the persistence of NETs to pulmonary fibrosis, cardiovascular abnormalities, and neurological dysfunction in long COVID. Several uncertainties require investigation in future studies. These include the mechanisms by which SARS-CoV-2 brings about sustained neutrophil activation phenotypes after infection resolution; whether the heterogeneity of neutrophils seen in acute SARS-CoV-2 infection persists into the chronic phase; whether the presence of autoantibodies in long COVID can induce NETs and protect them from degradation; whether NETs exert differential, organ-specific effects; specifically which NET components contribute to organ-specific pathologies, such as pulmonary fibrosis; and whether senescent cells can drive NET formation through their pro-inflammatory secretome in long COVID. Answering these questions may pave the way for the development of clinically applicable strategies targeting NETs, providing relief for this emerging health crisis

Natural Polymers in Micro- and Nanoencapsulation for Therapeutic and Diagnostic Applications: Part I: Lipids and Fabrication Techniques

Encapsulation, specifically microencapsulation is an old technology with increasing applications in pharmaceutical, agrochemical, environmental, food, and cosmetic spaces. In the past two decades, the advancements in the field of nanotechnology opened the door for applying the encapsulation technology at the nanoscale level. Nanoencapsulation is highly utilized in designing effective drug delivery systems (DDSs) due to the fact that delivery of the encapsulated therapeutic/diagnostic agents to various sites in the human body depends on the size of the nanoparticles. Compared to microencapsulation, nanoencapsulation has superior performance which can improve bioavailability, increase drug solubility, delay or control drug release and enhance active/passive targeting of bioactive agents to the sites of action. Encapsulation, either micro- or nanoencapsulation is employed for the conventional pharmaceuticals, biopharmaceuticals, biologics, or bioactive drugs from natural sources as well as for diagnostics such as biomarkers. The outcome of any encapsulation process depends on the technique employed and the encapsulating material. This chapter discusses in details (1) various physical, mechanical, thermal, chemical, and physicochemical encapsulation techniques, (2) types and classifications of natural polymers (polysaccharides, proteins, and lipids) as safer, biocompatible and biodegradable encapsulating materials, and (3) the recent advances in using lipids for therapeutic and diagnostic applications. Polysaccharides and proteins are covered in the second part of this chapter

Natural Polymers in Micro- and Nanoencapsulation for Therapeutic and Diagnostic Applications: Part II - Polysaccharides and Proteins

Encapsulation remains a fundamental and consistent approach of fabrication of drug and diagnostic delivery systems in the health space and natural polymers such as polysaccharides and proteins continue to play significant roles. Micro- or nanoencapsulation is employed for the conventional pharmaceuticals, biopharmaceuticals, or biologics, bioactives from natural sources and diagnostics such as biomarkers. The outcome of any encapsulation depends on the technique employed and the encapsulating material. The encapsulating materials employed influence the physical and chemical attributes of the fabricated micro- and nanocapsules. The encapsulating materials could be natural or synthetic, however, natural polymers are preferred because they are human and environmentally friendly. Polysaccharides and proteins are abundant in nature, biogenic, biocompatible, biodegradable and possess biological functions making them materials of choice for encapsulation of drugs and diagnostics. This chapter reviews the recent and advanced applications of polysaccharides and proteins as nanocarrier materials for micro- and nanoencapsulation of therapeutics and diagnostics

Review of solar energetic particle models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.</p

Multi-scale image preprocessing and feature tracking for remote CME characterization

Coronal Mass Ejections (CMEs) influence the interplanetary environment over vast distances in the solar system by injecting huge clouds of fast solar plasma and energetic particles (SEPs). A number of fundamental questions remain about how SEPs are produced, but current understanding points to CME-driven shocks and compressions in the solar corona. At the same time, unprecedented remote and in situ (Parker Solar Probe, Solar Orbiter) solar observations are becoming available to constrain existing theories. Here we present a general method for recognition and tracking solar images of objects such as CME shock waves and filaments. The calculation scheme is based on a multi-scale data representation concept à trous wavelet transform, and a set of image filtering techniques. We showcase its performance on a small set of CME-related phenomena observed with the SDO/AIA telescope. With the data represented hierarchically on different decomposition and intensity levels, our method allows extracting certain objects and their masks from the imaging observations in order to track their evolution in time. The method presented here is general and applicable to detecting and tracking various solar and heliospheric phenomena in imaging observations. It holds the potential to prepare large training data sets for deep learning. We have implemented this method into a freely available Python library

Multi-Scale Image Preprocessing and Feature Tracking for Remote CME Characterization

Coronal Mass Ejections (CMEs) influence the interplanetary environment over vast distances in the solar system by injecting huge clouds of fast solar plasma and energetic particles (SEPs). A number of fundamental questions remain about how SEPs are produced, but current understanding points to CME-driven shocks and compressions in the solar corona. At the same time, unprecedented remote and in situ (Parker Solar Probe, Solar Orbiter) solar observations are becoming available to constrain existing theories. Here we present a general method for recognition and tracking on solar images of objects such as CME shock waves and filaments. The calculation scheme is based on a multi-scale data representation concept a trous wavelet transform, and a set of image filtering techniques. We showcase its performance on a small set of CME-related phenomena observed with the SDO/AIA telescope. With the data represented hierarchically on different decomposition and intensity levels, our method allows to extract certain objects and their masks from the imaging observations, in order to track their evolution in time. The method presented here is general and applicable to detecting and tracking various solar and heliospheric phenomena in imaging observations. It holds potential to prepare large training data sets for deep learning. We have implemented this method into a freely available Python library.Comment: Accepted for publication in The Journal of Space Weather and Space Climat