Trial Basis Research Articles

Structural equation model of the barriers to preliminary and sustained BIM adoption in a developing country

PurposeThe purpose of this paper is to investigate the barriers that are constituting significant obstructions to preliminary and sustained BIM adoption in the South African construction industry.Design/methodology/approachImplementation Process Theory was used to develop the theoretical model of barriers to continuous and consistent BIM adoption. This enabled the formulation of two hypotheses, the identification of two sub-constructs (barriers to preliminary BIM adoption and barriers to sustained BIM adoption), and five variables (resources, knowledge, work process, organisational and planning barriers), which were validated using structural equation modelling (SEM).FindingsThe SEM results show pieces of evidence that validate the hypotheses in the theoretical model. The path analysis confirms that the two sub-constructs and five variables are statistically significant.Research limitations/implicationsThis research extends the postulations on the barriers to BIM adoption by demonstrating that organisational challenges and planning difficulties constitute barriers to sustained BIM adoption in the South African construction industry.Practical implicationsThe findings of this research are useful in understanding the planning scope and organisational requirements towards continuous and consistent BIM adoption in the South African construction industry.Originality/valueThe difficulties with BIM adoption are the issues with the performance of BIM on projects and are the major reason for the non-consistent adoption of BIM on projects. Having difficulties adopting BIM on projects suggests that BIM adoption is majorly on a preliminary or trial basis in the developing countries. This research tests this theory by proposing two types of BIM adoption and their associated barriers.

Convolutional neural networks for decoding electroencephalography responses and visualizing trial by trial changes in discriminant features

BackgroundDeep learning has revolutionized the field of computer vision, where convolutional neural networks (CNNs) extract complex patterns of information from large datasets. The use of deep networks in neuroscience is mainly focused to neuroimaging or brain computer interface -BCI- applications. In electroencephalography (EEG) research, multivariate pattern analysis (MVPA) mainly relies on linear algorithms, which require a homogeneous dataset and assume that discriminant features appear at consistent latencies and electrodes across trials. However, neural responses may shift in time or space during an experiment, resulting in under-estimation of discriminant features. Here, we aimed at using CNNs to classify EEG responses to external stimuli, by taking advantage of time- and space- unlocked neural activity, and at examining how discriminant features change over the course of an experiment, on a trial by trial basis. New methodWe present a novel pipeline, consisting of data augmentation, CNN training, and feature visualization techniques, fine-tuned for MVPA on EEG data. ResultsOur pipeline provides high classification performance and generalizes to new datasets. Additionally, we show that the features identified by the CNN for classification are electrophysiologically interpretable and can be reconstructed at the single-trial level to study trial-by-trial evolution of class-specific discriminant activity. Comparison with existing techniquesThe developed pipeline was compared to commonly used MVPA algorithms like logistic regression and support vector machines, as well as to shallow and deep convolutional neural networks. Our approach yielded significantly higher classification performance than existing MVPA techniques (p = 0.006) and comparable results to other CNNs for EEG data. ConclusionIn summary, we present a novel deep learning pipeline for MVPA of EEG data, that can extract trial-by-trial discriminative activity in a data-driven way.

TO STUDY THE EFFECT OF BAMBOO PIECES ON THE PROPERTIES OF PAVEMENT QUALITY CONCRETE BY PARTIAL REPLCMENT OF COARSE AGGREGATES

Pavement is usually defined as a structure consisting of layers and their key purpose is to share out the applied load to the sub grade. Rigid pavements have usually three layers namely sub grade, base layer and top most layers known as concrete slab. This concrete slab should be of above M35 grade of concrete as per IS recommendations. The most common size of coarse aggregates to be used in the rigid pavements should be of 20 mm and fine aggregates should be of zone II. As for as flexible pavements are concerned concrete pavements are more durable, while requiring a lesser amount of preservation and having longer life. This report discusses about the settlement of rigid pavements utilizing bamboo pieces. The study aims to examine the practicability of using bamboo pieces in pavement quality concrete with 0.38 water/binder ratios. This report presents the detailed amount of bamboo pieces used ranging from 0 to 1.5% with a variation of 0.5% on trial basis. Adding bamboo pieces up to 0.5% the compressive strength gets increased and beyond 0.5% of bamboo pieces’ addition the strength starts decreasing and as we keep on mounting the bamboo pieces percentage up to 1.5% the flexural strength also rises.

Multivariate pattern analysis of electroencephalography data reveals information predictive of charitable giving

Charitable donations are an altruistic behavior whereby individuals donate money or other resources to benefit others while the recipient is normally absent from the context. Several psychological factors have been shown to influence charitable donations, including a cost-benefit analysis, the motivation to engage in altruistic behavior, and the perceived psychological benefits of donation. Recent work has identified the ventral medial prefrontal cortex (MPFC) for assigning value to options in social decision making tasks, with other regions involved in empathy and emotion contributing input to the value computation (e.g. Hare et al., 2010; Hutcherson et al., 2015; Tusche et al., 2016). Most impressively, multivariate pattern analysis (MVPA) has been applied to fMRI data to predict donation behavior on a trial-by-trial basis from ventral MPFC activity (Hare et al., 2010) while identifying the contribution of emotional processing in other regions to the value computation (e.g. Tusche et al., 2016). MVPA of EEG data may be able to provide further insight into the timing and scalp topography of neural activity related to both value computation and emotional effects on donation behavior. We examined the effect of incidental emotional states and the perceived urgency of the charitable cause on donation behavior using support vector regression on EEG data to predict donation amount on a trial by trial basis. We used positive, negative, and neutral pictures to induce incidental emotional states in participants before they made donation decisions concerning two types of charities. One category of charity was oriented toward saving people from current suffering, and the other was to prevent future suffering. Behaviorally, subjects donated more money in a negative emotional state relative to other emotional states, and more money to alleviate current over future suffering. The data-driven multivariate pattern analysis revealed that the electrophysiological activity elicited by both emotion-priming pictures and charity cues could predict the variation in donation magnitude on a trial-by-trial basis.

Symptomatic response to CPAP in obstructive sleep apnea versus COPD- obstructive sleep apnea overlap syndrome: Insights from a large national registry.

BackgroundThe symptomatic response to continuous positive airway pressure (CPAP) therapy in COPD-obstructive sleep apnea overlap syndrome (OVS) compared to OSA syndrome (OSA) alone has not been well studied so far. The aim of this study is to explore main differences in the clinical response to CPAP treatment in OVS compared to OSA alone.Study design and methodsUsing prospective data from the French National Sleep Apnea Registry, we conducted an observational study among 6320 patients with moderate-to-severe OSA, available spirometry, and at least one follow-up visit under CPAP therapy.ResultsCPAP efficacy measured on the residual apnea-hypopnea index and median adherence were similar between OVS and OSA patients. In both groups, the overall burden of symptoms related to sleep apnea improved with CPAP treatment. In a multivariable model adjusted for age, gender, body mass index, adherence to treatment and residual apnea-hypopnea index, OVS was associated with higher odds for persistent morning headaches (OR: 1.37 [95% CI; 1.04; 1.79]; P = 0.02), morning tiredness (OR: 1.33 [95% CI: 1.12; 1.59]; P<0.01), daytime sleepiness (OR; 1.24 [95% CI: 1.4; 1.46]: P<0.01) and exertional dyspnea (OR: 1.26 [95% CI: 1.00;1.58]; P = 0.04) when compared with OSA alone.InterpretationCPAP therapy was effective in normalizing the apnea-hypopnea index and significantly improved OSA-related symptoms, regardless of COPD status. CPAP should be offered to patients with OVS on a trial basis as a significant improvement in OSA-related symptoms can be expected, although the range of response may be less dramatic than in OSA alone.

Measurement survey using acoustic measurement network and sound environment evaluation system by experience sampling

The use of open-plan offices is increasing as they are effective in improving intellectual productivity by fostering a communication among workers. Previous research on the relationship between the indoor sound environment and intellectual productivity has mostly reported the impact of the sound environment on the tasks that individuals work on. However, there has been no research on the impact of sound environment on office spaces where multiple workers are actually working. In this study, we developed a system that can analyze the individual characteristics of workers in relation to the sound environment by simultaneously measuring their evaluation to the sound environment and the sound environment of the office. The system collected workers' evaluation of their impressions to the sound environment through a regular questionnaire using the experience sampling method. At the same time, it measured the sound environment of the office with multiple small measurement devices. The obtained sound environment evaluation data and the acoustic data of the office were stored in a single database. Finally, this system was run in a working environment to evaluate the sound environment on a trial basis.

Mixed oxide growth on combinatorial aluminium\u2013gadolinium alloys \u2014 a thermodynamic and first-principles approach

Metal surfaces covered with oxides have attracted considerable scientific attention in various applications. In particular, anodic films fabricated by cost-effective anodizing have been widely used in nano-structured engineering to provide various surface functionalities. However, understanding of alloy film stability, having individual elements with widely varying structures and morphologies, is very limited due to lack of thermodynamic information and effects of electrolyte chemistry. This requires many tedious efforts on a trial and error basis in selecting suitable electrolytes that can produce the protective film at high efficiency on alloys having mixed chemistries. It is, therefore, crucial to develop a combination of high throughput theoretical analysis and automated rapid localized electrochemical probing that provides a fast and simple solution for electrolyte choice and paves the way to the remarkable expansion of industrial applications of oxides. Herein, we demonstrate that combinatorial Al–Gd alloys covering 1.0 to 10.0 at.% Gd can be oxidized into ultra-thin anodic films of controlled thickness through a selection of electrolyte based on thermodynamics (phosphate buffer with a pH of 8.20). We propose that growth of anodic films on alloys at high efficiency is possible if Gibbs free energy minimization criteria would be systematically contemplate.Graphical abstract

Decoding binary decisions under differential target probabilities from pupil dilation: A random forest approach.

Although our pupils slightly dilate when we look at an intended target, they do not when we look at irrelevant distractors. This finding suggests that it may be possible to decode the intention of an observer, understood as the outcome of implicit covert binary decisions, from the pupillary dynamics over time. However, few previous works have investigated the feasibility of this approach and the few that did, did not control for possible confounds such as motor-execution, changes in brightness, or target and distractor probability. We report on our efforts to decode intentions from pupil dilation obtained under strict experimental control on a single trial basis using a machine learning approach. The basis for our analyses are data of 69 participants who looked at letters that needed to be selected with stimulus probabilities that varied systematically in a blockwise manner (n = 19,417 trials). We confirm earlier findings that pupil dilation is indicative of intentions and show that these can be decoded with a classification performance of up to 76% area under the curve for receiver operating characteristic curves if targets are rarer than distractors. To better understand which characteristics of the pupillary signal are most informative, we finally compare relative feature importances. The first derivative of pupil size changes was found to be most relevant, allowing us to decode intention within only about 800 ms of trial onset. Taken together, our results provide credible insights into the potential of decoding intentions from pupil dilation and may soon form the basis for new applications in visual search, gaze-based interaction, or human–robot interaction.

Modified Approach of NaFA based on its Step Size and its Performance in Bioreactor Processes

Objectives: The objective of this work is to fine tune the variant of FA (Firefly Algorithm), NaFA (Firefly Algorithm with neighbourhood Attraction) by parameter tuning such as a, b , g . Furthermore, a new variant called Step Size Modified FA with neighbourhood attraction (SSMFA-N) has been proposed in which the step size is updated during the algorithm run so that a balance between local and global search is achieved. The considered objective functions are PO and ITAE. Methods: It is well known that parameters that are considered initially for any metaheuristic algorithms are purely trial and error basis and this leads to erroneous optimized results. While analysing the algorithms, NaFA (a variant of FA) has been considered for efficient convergence and good performance. On analysing it is noticed that FA and its variants’ performances and convergence depend on Step Size(a), brightness (b ) and adsorption coefficient(g ). In both the FA and NaFA the parameters to be tuned for effective convergence are a, b and g . It is also understood that the parameter b had been done separately and the parameters a and g cannot be fine-tuned simultaneously. Therefore, in NaFA the parameter tuning for a has been done for the processes FOPDT, stable and unstable SOPDT and the new variant SSMFA-N is thus proposed. Findings: The algorithm is made to run in MATLAB and Simulink environment for three different processes such as FOPDT, Stable and Unstable Second order Process (bioreactor processes) with the objective functions of less PO and ITAE. The obtained results from all the three processes are compared with the conventional and optimization methods (PSO) and shown that SSMFA-N outperforms the conventional and optimization approaches in both the time domain and performance indices. Novelty: The novelty is the modification of step size of NaFA, which ultimately leads to a new variant called SSMFA-N. Keywords: FA; FA with neighbourhood attraction; Step size tuning; Bioreactor Process

A domain decomposition method for the Navier\u2013Stokes equations with stochastic input

The paper is committed to studying the domain decomposition method for the incompressible Navier–Stokes equations(NSEs) with stochastic input. The stochastic input is represented spectrally by employing orthogonal polynomial functionals from the Askey scheme as trial basis to represent the random space, and the stochastic NSEs system are transformed into deterministic ones via the polynomial chaos expansion. The corresponding deterministic equations are transformed into the constrained optimization problem by minimizing the cost function on the common interface after the whole domain decomposed into two sub-domains. The constrained optimization problems are transformed into unconstrained problems by the Lagrange multiplier rule. A gradient method-based approach to the solutions of domain decomposition problem is proposed to solve the unconstrained optimality system. Finally, one numerical simulation experiment for square cavity flow problem with the stochastic boundary conditions are performed to demonstrate the feasibility and applicability of the gradient method.

Development of Validated Stability-indicating High Performance Thin Layer Chromatography Method for Estimation of Rabeprazole Sodium and Aceclofenac in Bulk Drug

Objective: To develop a validated stability-indicating high performance thin layer chromatography method for the estimation of Rabeprazole Sodium (RZL) and Aceclofenac (ACF) in bulk drugs.&#x0D; Methods: A high performance thin layer chromatographic (HPTLC) method has been developed for the separation of RZL &amp; ACF on plates precoated with aluminium back silica gel 60 F254. Different mobile phases were used on trial and error basis for separation of two drugs. The final mobile phase selected for analysis was toluene: ethyl acetate: methanol: acetic acid: ammonia in the ration of 6:4:1:0.2:0.1 (v/v). Both the drugs showed maximum absorbance at 279 nm which was selected as the detection wavelength throughout the experimental work. Developed method was validated as per ICH guidelines. Forced degradation of drugs was carried out under various stress conditions and HPTLC method was used for analysing the stability of drugs.&#x0D; Results: HPTLC method was successfully developed for separation of RZL and ACF with clear separation of bands of the drugs. Method validation after assessment of various parameters indicated low % RSD within an acceptable limit of &lt; 2.0 and the stability studies indicated the satisfactory separation of both the drugs from that of degraded products with considerable % recovery profile.&#x0D; Conclusion: The developed method is rapid, reliable, precise, and reproducible and demonstrates the suitability of the method for stability determination of rabeprazole and aceclofenac.

A postgraduate experiment: a study of fabricating nanofibers by electrospinning

The purpose of this work is to propose an experiment based on the fabrication of nanofibers by an electrospinning method that may become part of curricula at postgraduate level, for students of physics. This addition will not only increase the teaching capabilities of scientist and researchers at this level but also enhance the basic understanding of physics students of experimental setup and their approach to explore untouched areas in the field of nano-science in the future. This experiment gives a qualitative analysis of some physical parameters that affects the morphology and size of polyvinyl alcohol (PVA) nanofibers. The experiment has been performed on a trial basis, at the Department of Physics, University of Karachi. During the experiment we studied the effect of needle diameter and concentration of PVA on the size of nanofibers by SEM analysis. The statistical analysis of PVA nanofibers was performed by one-way analysis of variance by considering a P-value equal to 0.05. The analysis concluded that variation at the lower range of needle diameter has no significant effect on the size and morphology of nanofibers. Moreover, it is suggested, for future research, to consider the orientation of fiber alignment and control.

The design of a protocol for identifying and supporting children with developmental delays and/or disabilities in South African child and youth care centres

BackgroundHistorically, there is a lack of structured assessment and intervention protocols to support care of children with developmental delays and/or disabilities (DDDs) in rural child and youth care centres (CYCCs) across South Africa. AimThis study aimed to design an assessment and intervention protocol for holistic management of children in such centres, based on the opinions and input from CYCC staff and experts in the community. MethodsData was collected in two stages, the first consisted of qualitative focus groups with CYCC staff using a semi-structured interview schedule and the second was qualitative individual interviews with experts in developmental health such as paediatricians and occupational therapists (OTs) using an interview schedule. ResultsThe results enabled the design of a preliminary Ecosystemic Assessment and Intervention Protocol (ECO-AIP) for children with DDDs in CYCCs that could be implemented on trial basis in further research. ConclusionsInformation relating to the identification, and care and support of children with DDDs in rural CYCCs was obtained to enable the design of the ECO-AIP. This algorithmic protocol will guide a multi-disciplinary CYCC team to identify DDDs and to assist children to reach their milestones.

A meta-analysis of tumour response and relapse kinetics based on 34,881 patients: A question of cancer type, treatment and line of treatment

PurposeCancer disease burden is commonly assessed radiologically in solid tumours in support of response assessment via the RECIST criteria. These longitudinal data are amenable to mathematical modelling and these models characterise the initial tumour size, initial tumour shrinkage in responding patients and rate of regrowth as patient's disease progresses. Knowing how these parameters vary between patient populations and treatments would inform translational modelling approaches from non-clinical data as well as clinical trial design. Experimental designHere a meta-analysis of reported model parameter values is reported. Appropriate literature was identified via a PubMed search and the application of text-based clustering approaches. The resulting parameter estimates are examined graphically and with ANOVA. ResultsParameter values from a total of 80 treatment arms were identified based on 80 trial arms containing a total of 34,881 patients. Parameter estimates are generally consistent. It is found that a significant proportion of the variation in rates of tumour shrinkage and regrowth are explained by differing cancer and treatment: cancer type accounts for 66% of the variation in shrinkage rate and 71% of the variation in reported regrowth rates. Mean average parameter values by cancer and treatment are also reported. ConclusionsMathematical modelling of longitudinal data is most often reported on a per clinical trial basis. However, the results reported here suggest that a more integrative approach would benefit the development of new treatments as well as the further optimisation of those currently used.

Non-Surgical Interventions for Lumbar Spinal Stenosis Leading To Neurogenic Claudication: A Clinical Practice Guideline

Lumbar spinal stenosis (LSS) causing neurogenic claudication (NC) is increasingly common with an aging population and can be associated with significant symptoms and functional limitations. We developed this guideline to present the evidence and provide clinical recommendations on nonsurgical management of patients with LSS causing NC. Using the GRADE approach, a multidisciplinary guidelines panel based recommendations on evidence from a systematic review of randomized controlled trials and systematic reviews published through June 2019, or expert consensus. The literature monitored up to October 2020. Clinical outcomes evaluated included pain, disability, quality of life, and walking capacity. The target audience for this guideline includes all clinicians, and the target patient population includes adults with LSS (congenital and/or acquired, lateral recess or central canal, with or without low back pain, with or without spondylolisthesis) causing NC. The guidelines panel developed 6 recommendations based on randomized controlled trials and 5 others based on professional consensus, summarized in 3 overarching recommendations: (Grade: statements are all conditional/weak recommendations) Recommendation 1. For patients with LSS causing NC, clinicians and patients may initially select multimodal care nonpharmacological therapies with education, advice and lifestyle changes, behavioral change techniques in conjunction with home exercise, manual therapy, and/or rehabilitation (moderate-quality evidence), traditional acupuncture on a trial basis (very low-quality evidence), and postoperative rehabilitation (supervised program of exercises and/or educational materials encouraging activity) with cognitive-behavioral therapy 12 weeks postsurgery (low-quality evidence). Recommendation 2. In patients LSS causing NC, clinicians and patients may consider a trial of serotonin–norepinephrine reuptake inhibitors or tricyclic antidepressants. (very low-quality evidence). Recommendation 3. For patients LSS causing NC, we recommend against the use of the following pharmacological therapies: nonsteroidal anti-inflammatory drugs, methylcobalamin, calcitonin, paracetamol, opioids, muscle relaxants, pregabalin (consensus-based), gabapentin (very low-quality), and epidural steroidal injections (high-quality evidence). PerspectiveThis guideline, on the basis of a systematic review of the evidence on the nonsurgical management of lumbar spine stenosis, provides recommendations developed by a multidisciplinary expert panel. Safe and effective non-surgical management of lumbar spine stenosis should be on the basis of a plan of care tailored to the individual and the type of treatment involved, and multimodal care is recommended in most situations.

Emergence of a New Zoonotic COVID-19 that Creates a Pandemic: Update on Current Pharmacotherapeutics and Future Prospective of Plasma Therapy

The current decade started on an unexpected note, with almost the entire world grappling with a newly arisen pandemic. A novel coronavirus, tracing its first human host to a Chinese province, has spread to all geographical areas with human populations. The virus, named SARS-CoV-2, infects the lower respiratory tract, much like other coronaviruses, that caused the 2002 epidemic, to which it is eponymous . The severity of infection is seen in individuals with comorbidities like diabetes, cardiovascular disorders, chronic respiratory problems, hypertension, cancer, etc. This virus represents another incidence of zoonosis to humans and has infected over eighteen million people since December 2019, of its first human transmission. All the currently employed therapies are either aimed at alleviating the severity of the symptoms or being administered on a trial basis. This review attempts to summarize brief aetiology of the virus, epidemiology of the outbreak, clinical symptoms of the disease with a postulated mechanism of pathogenesis and several existing and approved drugs and therapeutics along with plasma therapy, which are being clinically reviewed for their activity, as well as safety, against the disease; none of which are approved yet. A few promising vaccine candidates, as per in vivo studies, are also underway, but their evaluation might take a year at least. Meanwhile, experts have come up with the concept of “social distancing” to stem the viral spread, as the medical research fraternity of the world strives hard to find a safe, successful and effective cure for it.

Safety and Efficacy of Remdesivir for the Treatment of Covid-19: A Rapid Review of Available Evidence

Context: Remdesivir is an antiviral drug manufactured by Gilead Sciences, Inc., in which in-vitro studies have been shown to work in COVID-19 patients. Although it’s not approved by pharmaceutical authorities and has not passed the first and second phases of clinical trials, it is prescribed on a trial basis for patients with Covid-19. In more than 20 countries, researchers are monitoring the results of using Remdesivir in clinical settings to see if it can be prescribed for larger populations if patients respond positively. Methods: This is a rapid review of the evidence for the potential effects of Remdesivir, which intended to create a policy guide. To do so, health technology assessment studies indexed in MEDLINE and Cochrane Library databases were searched using the keywords, including drug name and disease name, on April 21, 2020. In addition, references of retrieved studies were checked to ensure throughout the capture of the literature. Studies on the safety and efficacy of Remdesivir in Covid-19 patients, both in Persian or English, were included. To identify ongoing clinical trials in Iran and some countries, clinical trial registration systems were also searched. Results: In total 90 titles were identified, which after removing duplicates and applying inclusion criteria, 32 were included, all of which were published in 2020. 25 of them were review studies, mostly on treating Covid-19 disease, and some of them were dedicated to the effects of Remdesivir in treating the disease. However, no systematic review was found. Of the remaining studies, three were finished clinical trials, two of which evaluated the safety and efficacy of Remdesivir on mild, moderate, and severe Covid-19 compared to a placebo, and the third study compared Remdesivir with routine treatment. A cohort study on the efficacy of Remdesivir in compassionate use was also found. Also, two case reports of patients receiving Remdesivir and a letter-to- editor describing Remdesivir as an appropriate treatment for Covid-19 were identified. Moreover, registered clinical trials with different designs intended to investigate the safety and efficacy of Remdesivir in treating Covid-19 were extracted from clinical trial registration systems (Table 3). In total 15 protocols were found, which 13 were in primary stages. The other two were in phase three of clinical trials and aimed to investigate the effect of Remdesivir in treating patients with severe, moderate, or mild Covid-19. In the clinical trial registration system, it is mentioned that the first study is stopped prematurely due to the lack of a sufficient number of patients, and the second study is also suspended. Conclusions: Evidence on the safety and efficacy of Remdesivir in treating Covid-19 are very limited to make a decision. However, if registered trials are completed, enough evidence would be available to decide whether to accept or reject the Remdesivir. Since the effectiveness of Remdesivir is not clear yet, its prescription for Covid-19 patients has so far been limited to clinical trials, compassionate use, or emergency use.

Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).

LMA® Gastro™: A paediatric experience

The laryngeal mask airway, the LMA® Gastro™ (Teleflex Medical, Athlone, Ireland), is a novel airway device which permits upper gastrointestinal (GI) endoscopy to be performed via a dedicated large calibre oesophageal lumen. It has been validated in adult studies, but to our knowledge, there have been no data published regarding its use in a paediatric population. Following a brief education programme, the LMA Gastro was introduced on a trial basis at our institution and made freely available. Over a four-month period, our pre-existing endoscopy audit framework captured data on a total of 55 patients who had the LMA Gastro device chosen as the primary airway for elective upper GI endoscopy. These data were collected prospectively by the treating anaesthetist and included a range of airway and endoscopy outcomes. Of the 55 patients, the LMA Gastro provided an adequate airway in 52 (94.5%). Forty-six (88.5%) were sited on first attempt, and 50 (96.2%) insertions were rated 'easy' by the anaesthetist. Aside from three insertion failures, there were no airway events. The endoscopy success rate was 100% in the 52 patients who had an LMA Gastro airway successfully inserted. First-pass oesophageal access was achieved in 51 (98%) cases, and 100% of insertions were rated 'easy' by the gastroenterologist. Despite our relative inexperience with it, the device had a high success rate for airway maintenance and oesophageal access in our paediatric patient population. In our institution, the LMA Gastro provided a useful airway option in older children undergoing elective upper GI endoscopy.

Vaccines and drugs under clinical trials for prevention and treatment of COVID-19.

The uncertainty related to prevention and treatment of Coronavirus disease 2019 due to lack of effective vaccine candidates or drug molecules has resulted in extensive spread of infection and mortality worldwide. Although the asymptomatic or mild patients are becoming healthy with regular over-the-counter medicines and proper rest and care, for the severe patients, in the absence of definite cure, different drug combinations are being used to treat on trial basis without the assurance of efficacy and safety. This scenario has however changed now with some medicines including antiviral Remdesivir and Favipiravir and anti-inflammatory drugs like dexamethasone and tocilizumab which have shown some positive results in trials such as decreasing need of mechanical or non-invasive ventilation or mortality. Further, a number of vaccine candidates are currently in pipeline and in advance stages of clinical trials, which will enhance their prospects in determining how the disease will be controlled in the times to come. In this article, an account of the under-trial potential drugs and vaccine candidates has been provided, and their future prospects have been discussed.