Search

This study addresses the critical need for realistic emergency training in industries where non-stationary conditions can quickly escalate into accidents or incidents. Real-life training is often impractical due to safety concerns and cost constraints. Consequently, incorporating immersive technologies into training curricula becomes crucial. This research explores participants' self-reflection on safety readiness during virtual reality (VR) emergency training and investigates the impact of interactive versus passive exposure to emergency situations in VR. Three distinct exposure methods were developed, varying in the degree of participant involvement. Surprisingly, no statistically significant differences were found among the groups, indicating a positive perception of VR emergency training regardless of the exposure method. Participants valued the opportunity to safely make mistakes, witness consequences, and repeat procedures in VR. They believed such training enhanced their real-life emergency responses by fostering calmness, quick thinking, and prudent reactions. However, some participants expressed skepticism, suggesting that VR training might not accurately simulate real-life stress conditions. Future research should explore the impact of photorealistic VR experiences on operators' perceptions and assess the benefits of additional efforts in VR development for emergency training. • Participants' self-reflection on safety readiness in VR emergency training. • Impact of interactive versus passive exposure to emergency situations in VR. • VR emergency training perceived to enhance real-life emergency responses. [ABSTRACT FROM AUTHOR]

The motivation for the production of specific nanostructured electrode materials emerges from the escalating energy demands of the forthcoming generation. In this study, we demonstrated the fabrication process and evaluated the performance of supercapacitors utilizing manganese aluminate (MnAl 2 O 4) nanoparticles adorned on graphitic carbon nitride (g-CN). The composite material produced via hydrothermal methods exhibited a notable increase in specific capacitance (C s) and demonstrated excellent long-term stability throughout cycling. The improved electrochemical functionality was caused by several aspects, such as the occurrence of various oxidation states of manganese ions, a substantial specific surface area (SSA), a structure rich in nitrogen and a porous nature that enables rapid ion transportation. The electrode composed of a composite material exhibited excellent stability over 5000th cycles in 2.0 M KOH at 1 A g−1. Additionally, the specific capacitance (C s) of the MnAl 2 O 4 /g-CN nanohybrid was determined to be 586 F g−1 at 5 mV s−1. MnAl 2 O 4 /g-CN nanohybrid revealed a C s of 1161 F g−1, an energy density (E d) of 74 Wh kg−1 and a power density (P d) value of 340 W kg−1 at 1 A g−1. The electrochemical characteristics of g-CN were influenced by the presence of electrochemically activated sites in its nanosheet structures. The findings suggested that utilizing MnAl 2 O 4 /g-CN composite as electrode materials for storing energy could be an appealing and cost-effective option. [ABSTRACT FROM AUTHOR]

Currently, the entire world is confronted with two major challenges such as a dearth of energy resources and a progressively deteriorating state of the environment. The significance of generating and storing ecologically sustainable energy has grown in prominence due to the depletion of non-renewable resources. Pseudocapacitors have attracted the attention of energy specialists because of their enhanced cyclic life and increased energy/power density. The current study involved the synthesis of ZnSe@FeSe nanocomposite by hydrothermal technique, with the aim of exploring its potential applications in supercapacitors. Multiple analytical approaches were used to examine the morphology, structure and texture of electrode material. Electrochemical experiments revealed that ZnSe@FeSe electrode showed a higher specific capacitance (C s) of 1419.8 F g−1, high energy density (E d) of 63.2 Wh kg−1, high power density (P d) of 283.2 W kg−1, and long cyclic stability over 5000th CV cycles as compared to ZnSe and FeSe electrodes in 2.0 M KOH. This study highlights the efficiency of ZnSe@FeSe nanocomposite developed by using the economic, environment friendly and efficient hydrothermal method, and it can also be used in future energy-related applications like fuel cells, photocatalysis and hydrogen evolution reactions (HER). • Hydrothermal synthesis of ZnSe@FeSe nanocomposite used as energy storage electrode material. • Investigation of the synergistic effect of binary transition metals with selenide nanocomposite for energy storage devices. • ZnSe@FeSe nanocomposite exhibited higher specific capacitance (C s) of 1419.8 F g−1 than individual metal chalcogenides. • The ZnSe@FeSe electrode showed exceptional cyclic stability for up to 5000th cycles of CV analysis. [ABSTRACT FROM AUTHOR]

• Tricuspid Regurgitation (TR) occurs when the tricuspid valve leaflets do not close properly, causing blood to flow backward from the right ventricle to the right atrium, leading to serious health issues like biventricular heart failure. • TriClip™ G4 system by Abbott was recently approved by FDA. It is a transcatheter edge-to-edge heart valve repair system that offers a minimally invasive alternative to open-heart surgery, guided by transoesophageal echocardiography (TOE). This review covers the main aspects of the system, including its benefits and drawbacks. Additionally, it offers a comparison between TriClip G4 and traditional TR treatments. Tricuspid valve regurgitation, or TR, is a difficult-to-manage condition. In addition to EVOQUE, percutaneous annuloplasty, and surgical repair, the TriClip G4 system has been added to the interventional therapeutic choices for TR. Recently, the Food and Drug Administration (FDA) approved the use of the TriClip G4 device to treat patients with symptomatic, severe TR who have received optimal medication therapy but are at intermediate or higher risk of surgery. This review attempts to offer a thorough examination of the procedural features, learning curves, results of the device and compares the TriClip G4 system to other interventional therapies for TR. TriClip G4 has shown to have promising results in pivotal clinical trials, be cost-effective, and improve the quality of life of patients. Furthermore, it has its unique advantages against other conventional techniques and devices. [Display omitted] [ABSTRACT FROM AUTHOR]

The upper belt of Azad Kashmir is a hilly, mountainous, and remote area where the indigenous communities mainly believe in traditional medicines for the treatment of different ailments. This study aimed to conserve scientifically and culturally important medicinal knowledge of Primula species in Azad Kashmir, Western Himalaya, Pakistan. The additional objective was to evaluate the antibacterial activity of these plants against pathogenic bacteria. The ethnomedicinal data of Primula species was explored by conducting structured interviews with 40 informants of the study area, especially asking about the medicinal uses of Primula species. The indigenously used Primula species were further analyzed for their antibacterial activity against both gram-positive and gram-negative bacteria by using disc diffusion assay supplemented with a more robust minimum inhibitory concentration assay. Ethnomedicinal data revealed that indigenous communities living in upper regions of Azad Kashmir use 5 Primula species for the treatment of various disorders. The highly cited disease category was ophthalmic disorders. P. denticulata and P. macrophylla were the most cited plant species with higher use reports such as 104 and 93, respectively. One or more extracts of different parts of Primula species showed a noteworthy antibacterial activity against one or more tested bacteria. This study provides novel information regarding several categories of traditional uses and antibacterial activity of Primula species in Azad Kashmir, Western Himalaya. The need for novel and more effective drugs derived from natural products is more important than ever, making future studies on herbal remedies both justified and urgently required. [ABSTRACT FROM AUTHOR]

M protein from SARS CoV-19 used for vaccine construction by merging the epitopes and docked with TLR3 receptor. Codon optimization done and cloned in pET28 (+) vector. [Display omitted] Since the SARS-CoV-2 outbreak in December 2019 in Wuhan, China, the virus has infected more than 153 million individuals across the world due to its human-to-human transmission. The USA is the most affected country having more than 32-million cases till date. Sudden high fever, pneumonia and organ failure have been observed in infected individuals. In the current situation of emerging viral disease, there is no specific vaccine, or any therapeutics available for SARS-CoV-2, thus there is a dire need to design a potential vaccine to combat the virus by developing immunity in the population. The purpose of present study was to develop a potential vaccine by targeting B and T-cell epitopes using bioinformatics approaches. B- and T-cell epitopes are predicted from novel M protein-SARS-CoV-2 for the development of a unique multiple epitope vaccine by applying bioinformatics approaches. These epitopes were analyzed and selected for their immunogenicity, antigenicity scores, and toxicity in correspondence to their ability to trigger immune response. In combination to epitopes, best multi-epitope of potential immunogenic property was constructed. The epitopes were joined using EAAAK, AAY and GPGPG linkers. The constructed vaccine showed good results of worldwide population coverage and promising immune response. This constructed vaccine was subjected to in-silico immune simulations by C-ImmSim. Chimeric protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using snapgene. This vaccine design proved effective in various computer-based immune response analysis as well as showed good population coverage. This study is solely dependent on developing M protein-based vaccine, and these in silico findings would be a breakthrough in the development of an effective vaccine to eradicate SARS-CoV-2 globally. [ABSTRACT FROM AUTHOR]

• Comparative study to model the growth of P. tricornutum under natural sunlight. • Machine learning models outperform traditional models. • Light history enhances growth modeling using machine learning models. • LSTM model can illuminate light acclimation effect. • Applications of the models: biomass softsensor & optimal harvest strategy. Accurate prediction of microalgae growth is crucial for understanding the impacts of light dynamics and optimizing production. Although various mathematical models have been proposed, only a few of them have been validated in outdoor cultivation. This study aims to investigate the use of machine learning algorithms in microalgae growth modeling. Outdoor cultivation data of Phaeodactylum tricornutum in flat-panel airlift photobioreactors for 50 days were used to compare the performance of Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) with traditional models, namely Monod and Haldane. The results indicate that the machine learning models outperform the traditional models due to their ability to utilize light history as input. Moreover, the LSTM model shows an excellent ability to describe the light acclimation effect. Last, two potential applications of these models are demonstrated: 1) use as a biomass soft sensor and 2) development of an optimal harvest strategy for outdoor cultivation. [ABSTRACT FROM AUTHOR]

Delays in care negatively affect patients with potentially resectable thoracic malignant diseases. The Alberta Thoracic Oncology Program established an automatic referral process for patients with chest computed tomographic (CT) scans suggestive of malignant disease. The objective of this study was to determine whether automatic referral was associated with decreased time to referral or differences in the quality of referral information received. A single-center retrospective review of patients referred to a Canadian tertiary thoracic surgical center was performed. The time between the CT scan and the date of referral was calculated, and the type of information provided with the referral was tabulated. Automatic and traditional referral groups were compared using the Student t test, the Mann-Whitney U test, and multivariable analysis. A total of 689 patients met inclusion criteria, and 405 of these patients were automatic referrals. Average time to referral was shorter in the automatic referral group (4.7 days vs 23.6 days; P <.001). Only 2 automatic referrals took longer than 30 days, compared with more than 25% of traditional referrals. Automatic referrals were always associated with a shorter time for referral on subgroup analysis of lung nodules, different referring physician types, and patient location. There was no difference between referral types in the number of referral data provided to the center. Automatic referrals for patients with potential thoracic malignant disease have a significant beneficial impact on delays in care, and this could result in improved outcomes, such as decreased upstaging and improved survival. This was not associated with a decrease in the amount of information provided with the referral. Thus, automatic referrals may streamline patient care without compromising quality. [ABSTRACT FROM AUTHOR]