Prevalent Mode Research Articles

Soil microbiome bacteria protect plants against filamentous fungal infections via intercellular contacts

Bacterial-fungal interaction (BFI) has significant implications for the health of host plants. While the diffusible antibiotic metabolite-mediated competition in BFI has been extensively characterized, the impact of intercellular contact remains largely elusive. Here, we demonstrate that the intercellular contact is a prevalent mode of interaction between beneficial soil bacteria and pathogenic filamentous fungi. By generating antibiotics-deficient mutants in two common soil bacteria, Lysobacter enzymogenes and Pseudomonas fluorescens, we show that antibiotics-independent BFI effectively inhibits pathogenic fungi. Furthermore, transcriptional and genetic evidence revealed that this antibiotics-independent BFI relies on intercellular contact mediated by the type VI secretion system (T6SS), which may facilitate the translocation of bacterial toxic effectors into fungal cells. Finally, by using a "conidia enrichment" platform, we found that T6SS-mediated fungal inhibition resulting from intercellular contact naturally occurs within the soil microbiome, particularly represented by Pseudomonas fulva. Overall, these results demonstrate that bacteria from the soil microbiome can protect host plants from fungal infection through antibiotics-independent intercellular contacts, thus revealing a naturally occurring and ecologically important mode of BFI in agricultural contexts.

Electrocatalytic Mapping of Metal Fatigue with Persistent Slip Bands.

Metal fatigue, characterized by the accumulation of dislocation defects, is a prevalent failure mode in structural materials. Nondestructive early-stage detection of metal fatigue is extremely important to prevent disastrous events and protect human life. However, the lack of a precise quantitative method to visualize fatigue with spatiotemporal resolution poses a significant obstacle to timely detection. Here, we demonstrate a nondestructive electrocatalytic method to visualize metal fatigue, which is promising for future fatigue early detections. The persistent slip band (PSB) is considered one of the most consequential defect structures for metal fatigue failure. The selective electrochemistry is highly dependent on the metal crystallography and the collective dislocations in the PSB structure, enabling the amplification of the electrochemical response and differentiation of the fatigue stages at a submillimeter resolution. In addition, this nondestructive electrocatalytic method is applicable to several common metals, including copper, silver, iron, and aluminum, holding great significance where metal fatigue is a critical concern.

Edible Mushrooms: a Nutrient-Rich Ingredient for Healthier Food Products - A Review.

Edible mushrooms are found to be foods with high nutritional content, which have been shown to be more widely used ingredients in cooking in traditional dishes. This article explores the rising trend in the use of edible mushrooms in new formulations of functional foods, taking advantage of their properties and benefits in human health. The use of mushrooms as an ingredient in new or modified food formulations is driven by solid evidence of their nutritional content and bioactivity. Mushrooms stand out for their high biological value and high bioavailability protein content, as well as dietary fiber that promotes improved digestive health. Other micronutrients present are B vitamins and minerals such as selenium, phosphorus and potassium. Mushroom flour has been the prevalent mode of addition to food formulations. This type of format aims to preserve and concentrate the nutritional content of mushrooms and has achieved nutritional enrichment of products. The use of this food has also been explored to improve technological qualities in food development, so it is intended to position itself as a natural additive. This review synthesizes data on the nutritional composition, bioactive properties, and physicochemical attributes of mushrooms, emphasizing their multifaceted contributions to modern food formulations. It advocates for further research to optimize mushroom application in diverse food products and to address practical challenges for seamless integration.

Platform's blockchain introduction strategy with considering competition between new and refurbished products

As the second-hand market continues to grow, many retail platforms initially specializing in selling new products (e.g., Amazon, JD, and Walmart.com) have begun allowing refurbishers to directly sell refurbished goods on their platforms and gain additional profits. The platform can provide blockchain certification services for refurbishers to eliminate consumers' concerns about quality. In contrast to the existing literature, which primarily examines the introduction of blockchain technology from the perspective of cost factors, this paper investigates the platform's blockchain introduction in the context of competition between the new and refurbished products and its impacts on the manufacturer's and the refurbisher's profitability. Motivated by practices, two prevalent selling modes for the new product are considered: reselling mode (R) and agency selling mode (A). Even without considering the cost of blockchain, we find that the platform may have no incentive to introduce blockchain under both modes because it could trigger a severe cannibalization problem or an excessively high price for the refurbished product. The refurbisher (manufacturer) benefits with (without) blockchain under mode R, but this result occurs under mode A only when the blockchain service fee is low. We also discuss the welfare and environmental implications of blockchain. We find that the selling modes may modify the environmental implications of blockchain, but not the welfare implications of blockchain.

A Two-Individual-Based Evolutionary Algorithm for Flexible Assembly Job Shop Scheduling Problem with Uncertain Interval Processing Times

The assembly job shop is a prevalent production organization mode in manufacturing enterprises. During the processing and assembly of products, operation processing times are influenced by numerous factors, leading to significant uncertainty. This paper investigates the flexible assembly job shop scheduling problem (FAJSP) with uncertain processing times, where processing times are represented as variable interval numbers. We develop a robust optimization model for the FAJSP, utilizing confidence level estimation to determine the ranges of processing times and reformulating the model based on the chance-constrained method. A two-individual-based master–apprentice evolutionary (MAE) algorithm is proposed. Two effective encoding schemes are designed to prevent the generation of infeasible solutions under assembly sequence constraints. Additionally, a decoding method based on interval scheduling theory is devised to accurately represent interval processing times. Case studies are conducted to validate the effectiveness of the proposed robust optimization model and demonstrate the superiority of the MAE algorithm.

Investigation of Ductility and Damage Behavior of C/GFRP Composite Laminates under Bending Loads

Carbon and glass fabric reinforced polymer (C/GFRP) composites are extensively used in aerospace and sports industry because of their exceptional properties. However, during service, static and dynamic bending loads can ensue damage in composites affecting their strength, stiffness and energy absorption. Carbon fiber composites, being inherently brittle, are prone to sudden catastrophic fracture without ductile-like behavior of metals. This study investigates mechanical behavior and damage mechanisms of woven C/GFRP composites in on- and off-axis orientations during bending. Initially, bending tests with quasi-static loading were performed, followed by dynamic ones using an Izod impact testing apparatus. Results showed distinct behavior in on-axis CFRP laminates with brittle fracture. Off-axis CFRP samples and both on- and off-axis GFRP laminates showed signs of damage and non-linear behavior, yet they retained their ability to bear loads. Significantly, off-axis specimens of both types and on-axis GFRP laminates exhibited enhanced energy absorption capabilities without experiencing fracture, undergoing pseudo-ductile deformation. CFRP specimens were analyzed with micro-computed tomography (micro-CT), provided insights into prevalent damage modes such as matrix mircocracking, debonding of tows, delamination and breakage of fabric. While on-axis CFRP laminates experienced brittle fracture, off-axis specimens exhibited a ductile-like response attributed to matrix plasticity, cracking and fiber trellising before eventual failure.

Online and Offline Fault Detection and Diagnostics in a Nuclear Power Plant Condenser

Nuclear power plants (NPPs) face significant financial pressures due to operational and maintenance costs. This research investigates Fault Detection and Diagnostics (FDD) techniques to optimize maintenance schedules and reduce expenses. The NPP condenser plays a critical role in converting turbine exhaust steam back into water for reuse. Condenser tube fouling, a prevalent fault mode, impedes heat transfer efficiency and can lead to decreased plant efficiency and safety risks. This study proposes an FDD framework that leverages raw signal analyses from temperature and pressure monitoring to detect and diagnose condenser tube fouling in both online and offline settings. The online approach facilitates close-to-real-time predictions, enabling proactive maintenance strategies. Additionally, the framework explores incorporating a condenser’s maintenance history for enhanced diagnostics. We employ a dataset obtained from a simulated nuclear power plant condenser using the Asherah Nuclear Power Plant Simulator (ANS). ANS replicates the operational dynamics of a pressurized water reactor (PWR) type NPP. The proposed methodology utilizes an encoder-decoder (E-D) structured 1DCNN model to analyze the raw signals. The research demonstrates consistent and accurate fault detection and diagnostics for condenser tube fouling in both online and offline scenarios. A high potential for generalization to unseen conditions was observed. However, online detection using small data windows necessitates caution due to potential false alarms around the transition points. Our findings pave the way for further exploration of robust diagnostics by accommodating a wider spectrum of fouling rates within degradation classes using ANS. This combined online and offline FDD approach offers a promising solution for promoting operational safety, efficiency, and cost-effectiveness in NPP condensers.

Examining the impacts of school bus travel on students' academic performance in two major cities

AbstractSchool buses are a prevalent mode of school travel that may negatively affect students’ academic performance due to numerous factors, including longer commutes. These extended travel times can introduce or exacerbate mental and physical stressors, including air pollution exposure and bullying, while reducing opportunities for health‐promoting activities like physical activity and sleep. While a few researchers have explored the effects of school bus transportation on academic achievement, the research is limited. In this study, we used data from two major Canadian cities, Toronto and Ottawa, to investigate the relationship between the proportion of students commuting by bus to and from school and the percentage meeting standards on standardized tests. We employed beta regression models to analyze performance in reading, writing, math, and literacy across Grades 3, 6, 9, and 10 while controlling for family and income variables that may influence school travel mode and student achievement. Our findings indicate a significant inverse correlation between school bus transportation and academic achievement for Grade 10 literacy. Longer commutes appear to impair academic performance, given that Grade 10 students presumably spend more time on the bus than younger students. Notably, the negative effects on literacy outcomes are greater than on math.

Survival in STEMI in resource limited settings - obstacles and potential solutions. Critical lesson learnt thorough a prospective observational study

Abstract Background Early revascularization in ST segment elevation myocardial infarction(STEMI) by Primary Percutaneous coronary Intervention (PPCI) or fibrinolysis, reduces mortality. In the absence of a well-functioning STEMI care system, patients may not get guideline directed revascularisation (GDR). Objective We sought to determine the prevalent mode of revascularisation for STEMI in the community, to discern the factors contributing to lack of GDR during their initial medical encounter, and to investigate the consequences of not getting GDR. Methods Consecutive patients within 24 hours of STEMI from October 2021 to December 2021 in a public hospital from a developing nation, were enrolled. In addition to baseline data, the details of the first medical contact (FMC) and second medical contacts (SMC) before reaching the study site were collected. The hospitals where patients sought care earlier, could be lysis capable hospitals (LCH), PCI/lysis capable hospitals (PLCH) and non-lysis-capable hospitals (NLCH). Medical records related to these visits were scrutinised and in-depth interviews were conducted with patients and their care givers. Details of GDR offered / received during FMC/SMC and the reasons for not receiving GDR were collected. Results 300 patients were enrolled during the study period. 19 reported directly to the study site, while others had visited 1-3 hospitals en route(Figure-1). The 159 who received fibrinolysis in at least one of their medical contacts, had a significantly lower incidence of cardiogenic shock and in-hospital mortality, compared to the rest(Figure-2). 162(54%) patients had had FMC in NLCH and had to be referred to SMC for GDR. Of the 157 visits by a patient with STEMI in a LCH / PLCH within 6 hours’ time window (6HTW), GDR was provided only 44 visits(28%) (Figure-1). The common reason for not receiving GDR was financial. This revascularisation solutions offered were not affordable. These include, PPCI only or pharmaco-invasive package only in PLCH and high cost bolus lytic only in LCH. Of the 132 patients, who had FMC ≤ 12 hours in LCH, only 33 had lysis. Patients who did not receive revascularisation, despite reaching within 6HTW, had adverse in-hospital outcome. (Figure-2) Conclusion The public awareness of the need for early revascularisation in STEMI and the revascularisation solutions available in the neighbourhood hospitals is low. Most patients with STEMI do not receive GDR despite reaching revascularisation capable hospitals within 6HTW. The common reasons for this include, non-availability of low cost fibrinolytics and lack of financial resources. Hospitals should offer fibrinolysis when patients cannot afford PPCI, and low-cost infusion lytics, when patients cannot afford high cost bolus lytics. Provision of GDR in STEMI at the first medical contact, is a social responsibility. Governmental and non-governmental organisations should work in tandem, to ensure 100% GDR at first medical contact.

The Effect of Silver Nanoparticles on Bond Strength of Calcium Silicate-Based Sealer: An In Vitro Study

The aim of this study was to evaluate the bond strength of the calcium silicate-based sealer (CSS) modified with the silver nanoparticles (AgNPs) using the single-cone technique (SC) and the continuous wave condensation (CWC) technique, measured by a universal testing machine. The AgNPs and the modified sealers were characterized by scanning electron microscopy and transmission electron microscopy. One hundred single-rooted extracted human permanent teeth with a single root canal were cleaned and shaped with a Protaper Next system. The teeth were randomly divided into four groups (n = 25) as follows: Group 1, canals were obturated using the SC technique with TotalFill® BC Sealer. Group 2, canals were obturated using the SC technique with TotalFill® BC Sealer mixed with AgNPs. Group 3, canals were obturated using the CWC technique with TotalFill® HiFlow BC Sealer. Group 4, canals were obturated using the CWC technique with TotalFill® HiFlow BC Sealer mixed with AgNPs. After two weeks, 1 mm-thick dentin slices were cut and exposed to a push-out bond strength test using a universal testing machine. Specimens were examined under a digital microscope to determine the mode of failure. Statistical analysis was performed using ANOVA and Tukey multiple comparison tests (p < 0.05). The nanoparticle characterization revealed a spherical morphology with no obvious aggregations. The results showed that group 4 had the highest dislodgement resistance compared to all groups (p < 0.05). Group 4 was significantly higher in push-out bond strength value than group 1 (p < 0.001) and group 3 (p < 0.003), but not significantly higher than group 2. Cohesive failure was the most prevalent failure mode among all groups. It can be concluded that the incorporation of silver nanoparticles into the calcium silicate-based sealer significantly increased the bond strength. The warm obturation approach demonstrated significantly higher resistance to dislodgment as compared to the single-cone technique.

Statistical analysis of seroprevalence and risk factors of hepatitis C in Nowshera District, Pakistan

Hepatitis C virus (HCV) transmission remains a significant public health concern. It is well documented globally, however, Nowshera district, Pakistan, is lacking such profile. This study aims to explore the relationship between HCV infection and several risk factors, including socio-demographic, clinical and personal life-style factors. This study using a cross-sectional design, examined 606 randomly selected individuals visiting the Pathology department at Qazi Hussain Medical Complex and District Headquarter (DHQ) Hospital Nowshera between May 1, 2022 and Jun 30, 2023. This research investigation employed a methodical approach involving formal interviews in conjunction with structured questionnaires to gather comprehensive information related to socio-demographic characteristics, clinical history, and personal hygiene practices. We collected 10 ml of blood samples and tested the separated serum to identify markers using the Immuno-Chromatographic Test (ICT) and the Enzyme-Linked Immunosorbent Assay (ELISA). IBM SPSS Statistics version 27 was used for data analysis. To measure the association between dependent variable and independent variables, a chi-square and risk analysis was carried out; multiple logistic regression was employed for modeling the risk factors associated with independent variable. A statistical significance level was established at a P-value of less than 0.05. In present study, which included 606 participants, 12% were found to be infected with HCV. Importantly it revealed that facial shave at barber (adjusted odds ratio, aOR = 40.65, p = 0.000) represents the most prevalent mode of HCV transmission. Additionally, a strong association was observed between HCV infection and history of past surgery (RR = 2.98, p = 0.001), HCV infected family member (aOR = 4.28, p = 0.001), workplace injuries (aOR = 6.68, p = 0.000), history of hospital admission (RR = 2.09), practicing ear and nose piercing (aOR = 5.01, p = 0.001), dental treatment (RR = 2.31) and the frequency of injections (aOR = 8.607, p = 0.000). These findings underscore the pressing need for targeted interventions. This study highlights the paramount importance of understanding the modes of HCV transmission and their associated risk factors. The results emphasize the need for educational initiatives, both within the healthcare sector and among the general public, to combat HCV transmission effectively. By implementing sterilization procedures and increasing awareness, we can make significant strides in reducing the burden of HCV infection. Moreover, proactive measures within families can help contain the spread of the virus, ultimately contributing to improved public health.

Characterising the permanent deformation of subgrade soils under seasonal variation

Rutting, a prevalent failure mode in flexible pavements, largely stems from subgrade issues. Despite this, there is a lack of standard protocols to evaluate subgrade rutting or permanent deformation (PD). This study attempted to characterise PD in subgrades, focusing on a poorly graded sand and two silty sands. Moisture contents above and below optimum levels were considered to account for seasonal variations. The research involved adapting a test to assess the PD by determining typical stresses on the subgrade. Moreover, given these soils' unsaturated state and medium- to fine-grained nature, suction is an important factor. Suction-controlled multi-stage Repeated Load Triaxial tests were conducted, and the results were fitted by a PD model modified to account for suction. The characterisation was compared with the subgrade strain criterion used in pavement design solutions. Results indicated discrepancies between the PD characterisation and strain criteria predictions, with the silty sands performing better than the poorly graded sand, consistent with the shakedown theory.

Optimization and forecasting of reinforced wire ropes for tower crane by using hybrid HHO-PSO and ANN-HHO algorithms

Wire rope is a vital component of every crane. Wire rope faults are related to the operation, fabrication environment, etc., and the prevalent mode of failure is fatigue. The aim of this study is to develop an advanced tower crane applicable to wire rope with integrated reinforcement. Steel wire ropes are superiorly used in several tower crane applications, but they may create certain failures such as less fatigue and wear-resistant. In this study, steel wires are strengthened by granite and Zinc oxide (ZnO) reinforcement. Two sets of wire ropes are prepared as complete and partial reinforcement of steel wire with seven strands and 15 wires. The failure tests such as hardness, wear analysis, tensile strength, and fatigue life are optimized using hybrid Harris Hawk optimization-based Particle swarm Optimization (Hybrid HHO-PSO). Besides, the experimented wire rope performances are predicted using hybrid Artificial Neural Network based HHO (Hybrid ANN-HHO). Fully reinforced wire ropes provide better performances for both experimented and optimization behaviors. This provides 1818 MPa of maximum tensile strength, 0.23 mm of minimal wear depth, and 3.38x104 times better fatigue life. In the HHO-PSO optimization method, the obtained better tensile strength is 1822 MPa, wear depth is 0.66 mm, and Fatigue life is 3.57 x104 times. Besides, from the predicted outcomes, ANN-HHO provides a minimal error value than the ANN approach. The result of this study will open up different ways for the advancement of wire rope in tower crane application by improving its load bearing capacity. The outcomes from this research can be practically applicable for increasing the load bearing capacity of the tower crane without increasing the number of wires and strands in the wire rope.

Seasonal variations and temporal instability of motorcyclist injury severity in Cambodia: Analyses based on a random parameter logit model with heterogeneity in means and variances

Motorcycles are a prevalent mode of transportation in countries like Cambodia that experience distinct rainy and dry seasons. However, the safety concerns associated with motorcycling in this region have not been thoroughly investigated. This study addresses this research gap by examining the severity of motorcyclist injuries in Cambodia, considering the potential variations across seasons and the fluctuations in contributing factors over time. Utilizing a random parameter logit model with heterogeneity in means and variances, the research analyzes motorcycle crash data from 2015 to 2017 to identify heterogeneities in the determinants of injury severity. The study confirms seasonal variations and temporal instabilities in influential factors, highlighting the need for distinct modeling for dry and rainy seasons due to varying contributing factors. Key findings include the consistent increase in fatal injury risk associated with head-on collisions and elderly rider involvement across both seasons. During the rainy season, motorcycle-to-motorcycle crashes significantly heighten the likelihood of severe injuries, with weekend crashes more likely to result in fatalities. Furthermore, more than half of speeding incidents during the rainy season consistently led to fatal injuries across all three years. In contrast, during the dry season, riders faced a greater risk of severe injuries compared to pillion riders, with crashes on national roads more likely to lead to fatal outcomes. Temporal stability tests further reveal that the influence of external variables on motorcyclist injury severity varies across years, stressing the need for tailored, season-specific approaches to effectively mitigate and prevent crashes.

Considerations for continuing professional development in the post-pandemic era: national experiences from psychiatry.

COVID-19 led to rapid innovations in continuing professional development (CPD). We surveyed Canadian Psychiatry CPD directors to understand the pandemic's impact and to identify effective practices. In fall 2021, an online 31-item survey was created iteratively based on discussions among CPD educators and disseminated to CPD program leaders at 17 Canadian medical schools through the Council of Psychiatry Continuing Education (COPCE). We collected information on each CPD program, adaptations associated with pandemic restrictions, and intentions regarding future delivery of CPD. Nine responses were received. COVID-19 led to a shift to virtual CPD delivery, with creative and transformative strategies to maintain engagement and online security. Virtual CPD was associated with an increase in attendance and decrease in costs. Many respondents anticipated that virtual or hybrid modalities would continue post-COVID-19. The pandemic led to a pivot to virtual delivery of Psychiatry CPD programming. Hybrid delivery will likely be the prevalent mode of future CPD programming, requiring more technological, financial, and human resources to tackle potential challenges. In times of rapid adaptation, a national network of CPD directors can provide an important venue for knowledge exchange about innovations and effective practices and build capacity of expertise.

Mechanism based four-linear cohesive zone model for mode I fracture of different stacking sequence CFRP laminates

Delamination, a prevalent failure mode observed in laminated composites, exerts a significant impact on structural integrity and performance. The occurrence of fiber bridging during the fracture process adds complexity and elevates the research challenges associated with this phenomenon. Existing models exhibit limitations in accurately capturing bridging behavior and discerning its underlying mechanical mechanisms. This study addresses these limitations by analyzing experimental results, employing the J-integral, and analyzing R-curve behavior, proposing a mechanism-based four-linear cohesive zone model along with a new finite element implementation method. Comprising three overlapping bi-linear CZMs, this model effectively simulates mode I fracture behavior in laminates with different stacking sequences. Moreover, it intuitively illustrates the mechanical mechanisms during crack propagation and offers simplicity in implementation. This research contributes to a deeper understanding of composite fracture mechanics and provides a practical model for predicting delamination behavior in laminated structures.

A Multimodal Sentiment Analysis Model for Graphic Texts Based on Deep Feature Interaction Networks

Due to the widespread adoption of social networks, image-text comments have become a prevalent mode of emotional expression compared to traditional text descriptions. However, there are currently two major challenges. The first is the question of how to extract rich representations effectively from both text and images, and the second is the question of how to extract cross-modal shared emotion features. This study proposes a multimodal sentiment analysis method based on a deep feature interaction network (DFINet). It leverages word-to-word graphs and deep attention interaction networks (DAIN) to learn text representations effectively from multiple subspaces. Additionally, it introduces a cross-modal attention interaction network to extract cross-modal shared emotion features efficiently. This approach helps alleviate the difficulties associated with acquiring image-text features and representing cross-modal shared emotion features. Experimental results on the Yelp dataset demonstrate the effectiveness of the DFINet method.

Genetics and Traumatic Brain Injury: Findings from an Exome-Based Study of a 50-Patient Case Series.

Traumatic brain injury (TBI) is the leading cause of global mortality and morbidity. Because TBI is accident-related, the role of genetics in predisposing to TBI has been largely unexplored. However, the likelihood of injury may not be entirely random and may be associated with certain physical and mental characteristics. In this study, we analyzed the exomes of 50 patients undergoing rehabilitation after TBI. Patients were divided into three groups according to rehabilitation outcome: improvement, no change, and deterioration/death. We focused on rare, potentially functional missense and high-impact variants in genes intolerant to these variants. The concordant results from the three independent groups of patients allowed for the suggestion of the existence of a genetic predisposition to TBI, associated with rare functional variations in intolerant genes, with a prevalent dominant mode of inheritance and neurological manifestations in the genetic phenotypes according to the OMIM database. Forty-four of the 50 patients had one or more rare, potentially deleterious variants in one or more neurological genes. Comparison of these results with those of a 50-sampled matched non-TBI cohort revealed significant differences: P = 2.6 × 10-3, OR = 4.89 (1.77-13.47). There were no differences in the distribution of the genes of interest between the TBI patient groups. Our exploratory study provides new insights into the impact of genetics on TBI risk and is the first to address potential genetic susceptibility to TBI.

A Deep Learning-Enhanced Compartmental Model and Its Application in Modeling Omicron in China.

The mainstream compartmental models require stochastic parameterization to estimate the transmission parameters between compartments, whose calculation depend upon detailed statistics on epidemiological characteristics, which are expensive, economically and resource-wise, to collect. In addition, infectious diseases spread in three dimensions: temporal, spatial, and mobile, i.e., they affect a population through not only the time progression of infection, but also the geographic distribution and physical mobility of the population. However, the parameterization process for the mainstream compartmental models does not effectively capture the spatial and mobile dimensions. As an alternative, deep learning techniques are utilized in estimating these stochastic parameters with greatly reduced dependency on data particularity and with a built-in temporal-spatial-mobile process that models the geographic distribution and physical mobility of the population. In particular, we apply DNN (Deep Neural Network) and LSTM (Long-Short Term Memory) techniques to estimate the transmission parameters in a customized compartmental model, then feed the estimated transmission parameters to the compartmental model to predict the development of the Omicron epidemic in China over the 28 days for the period between 4 June and 1 July 2022. The average levels of predication accuracy of the model are 98% and 92% for the number of infections and deaths, respectively. We establish that deep learning techniques provide an alternative to the prevalent compartmental modes and demonstrate the efficacy and potential of applying deep learning methodologies in predicting the dynamics of infectious diseases.

WP6.11 - Systematic Review and Meta-Analysis of Written Interventions Used In the Informed Consent Process

Abstract Aim Written interventions are the earliest and most prevalent mode of information provided to patients in clinical practice. They are used as an adjunct to the verbal discussions between clinician and patients during the informed consent process. This review aimed to assess the effects of these interventions. Method This was a subgroup analysis from a larger systematic review and meta-analysis conducted according to the predefined protocol developed and registered on PROSPERO (CRD42023380406). . Five databases were searched using pre-defined search criterion in December 2022 for randomised trials of written interventions designed to improve the informed consent process. Adults > 18 years with the capacity to consent were included. The Cochrane risk of Bias (RoB) tool was used to assess study quality. Effect measurements were assessed using standardised mean differences and risk ratios for continuous variables and dichotomous variables respectively. Results 35 studies (37 intervention arms) contributing 3600 patients met the inclusion criteria. All but one study were conducted in an elective setting across a variety of surgical, radiological, endoscopic, oncological, and medical disciplines. Statistically significant improvement was demonstrated, in short (SMD 0.88, 95% CI 0.29 to 1.47, I2 = 81%) and long-term knowledge (SMD 0.38, 95% CI 0.14 to 0.62, I2 = 66%). There was no difference in immediate knowledge, satisfaction, or anxiety with the informed consent process. Conclusions This review provides a global overview of the impact of written interventions which has demonstrated improvement in short and long-term knowledge. These readily accessible intervention types should be considered as an adjunct during informed consent consultations to better inform decision making.