Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques.

Four state-of-the-art metaheuristic algorithms including the genetic algorithm (GA), particle swarm optimization (PSO), differential evolutionary (DE), and ant colony optimization (ACO) are applied to an adaptive neuro-fuzzy inference system (ANFIS) for spatial prediction of landslide susceptibility in Qazvin Province (Iran). To this end, the landslide inventory map, composed of 199 identified landslides, is divided into training and testing landslides with a 70:30 ratio. To create the spatial database, thirteen landslide conditioning factors are considered within the geographic information system (GIS). Notably, the spatial interaction between the landslides and mentioned conditioning factors is analyzed by means of frequency ratio (FR) theory. After the optimization process, it was shown that the DE-based model reaches the best response more quickly than other ensembles. The landslide susceptibility maps were developed, and the accuracy of the models was evaluated by a ranking system, based on the calculated area under the receiving operating characteristic curve (AUROC), mean absolute error, and mean square error (MSE) accuracy indices. According to the results, the GA-ANFIS with a total ranking score (TRS) = 24 presented the most accurate prediction, followed by PSO-ANFIS (TRS = 17), DE-ANFIS (TRS = 13), and ACO-ANFIS (TRS = 6). Due to the excellent results of this research, the developed landslide susceptibility maps can be applied for future planning and decision making of the related area

Interventions for increasing acceptance of local anaesthetic in children and adolescents having dental treatment

BACKGROUND: Delivery of pain-free dentistry is crucial for reducing fear and anxiety, completion of treatment, and increasing acceptance of future dental treatment in children. Local anaesthetic (LA) facilitates this pain-free approach but it remains challenging. A number of interventions to help children cope with delivery of LA have been described, with no consensus on the best method to increase its acceptance. OBJECTIVES: To evaluate the effects of methods for acceptance of LA in children and adolescents during dental treatment. SEARCH METHODS: Cochrane Oral Health's Information Specialist searched the Cochrane Oral Health's Trials Register (to 24 May 2019); the Cochrane Central Register of Controlled Trials (CENTRAL; 2019 Issue 4) in the Cochrane Library (searched 24 May 2019); MEDLINE Ovid (1946 to 24 of May 2019); Embase Ovid (1980 to 24 May 2019); and Web of Science (1900 to 24 May 2019). The US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov) and World Health Organization International Clinical Trials Registry Platform were also searched to 24 May 2019. There were no restrictions on language or date of publications. SELECTION CRITERIA: Parallel randomised controlled trials (RCTs) of interventions used to increase acceptance of dental LA in children and adolescents under the age of 18 years. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. We performed data extraction and assessment of risk of bias independently and in duplicate. We contacted authors for missing information. We assessed the certainty of the body of evidence using GRADE. MAIN RESULTS: We included 26 trials with 2435 randomised participants aged between 2 and 16 years. Studies were carried out between 2002 and 2019 in dental clinics in the UK, USA, the Netherlands, Iran, India, France, Egypt, Saudi Arabia, Syria, Mexico, and Korea. Studies included equipment interventions (using several LA delivery devices for injection or audiovisual aids used immediately prior to or during LA delivery or both) and dentist interventions (psychological behaviour interventions delivered in advance of LA (video modelling), or immediately prior to or during delivery of LA or both (hypnosis, counter-stimulation). We judged one study to be at low risk and the rest at high risk of bias. Clinical heterogeneity of the included studies rendered it impossible to pool data into meta-analyses. None of the studies reported on our primary outcome of acceptance of LA. No studies reported on the following secondary outcomes: completion of dental treatment, successful LA/painless treatment, patient satisfaction, parent satisfaction, and adverse events. Audiovisual distraction compared to conventional treatment: the evidence was uncertain for the outcome pain-related behaviour during delivery of LA with a reduction in negative behaviour when 3D video glasses where used in the audiovisual distraction group (risk ratio (RR) 0.13, 95% confidence interval (CI) 0.03 to 0.50; 1 trial, 60 participants; very low-certainty evidence). The wand versus conventional treatment: the evidence was uncertain regarding the effect of the wand on pain-related behaviour during delivery of LA. Four studies reported a benefit in using the wand while the remaining studies results suggested no difference between the two methods of delivering LA (six trials, 704 participants; very low-certainty evidence). Counter-stimulation/distraction versus conventional treatment: the evidence was uncertain for the outcome pain experience during delivery of LA with children experiencing less pain when counter-stimulation was used (RR 0.12, 95% CI 0.04 to 0.34; 1 trial, 134 participants; very low-certainty evidence). Hypnosis versus conventional treatment: the evidence was uncertain for the outcome pain experience during delivery of LA with participants in the hypnosis group experiencing less pain (mean difference (MD) -1.79, 95% CI -3.01 to -0.57; 1 trial, 29 participants; very low-certainty evidence). Other comparisons considered included pre-cooling of the injection site, the wand versus Sleeper One, the use of a camouflage syringe, use of an electrical counter-stimulation device, and video modelling acclimatisation, and had a single study each. The findings from these other comparisons were insufficient to draw any affirmative conclusions about their effectiveness, and were considered to be very low-certainty evidence. AUTHORS' CONCLUSIONS: We did not find sufficient evidence to draw firm conclusions as to the best interventions to increase acceptance of LA in children due to variation in methodology and nature/timing of outcome measures. We recommend further parallel RCTs, reported in line with the CONSORT Statement. Care should be taken when choosing outcome measures

The hijab between men and women in Saudi Society

Many studies by international organisations and non-Saudi researchers conclude that all Saudi women are forced to wear hijabs. This can now be questioned, particularly with the lifting of the requirement to wear hijab. Therefore, a comprehensive understanding of the hijab in Saudi Arabia is needed, especially in light of the monumental social reforms implemented in recent years. This study explores the concept of the hijab in Saudi thought, the social norms underpinning the wearing of the hijab within collectivist Saudi culture and the consequences of challenging these norms. The study also explores the views of Saudis on several stigmas linked to the hijab and the impact of specific declarations following the announcement of Saudi Vision 2030 on women’s hijab. This was achieved using a qualitative approach and semi-structured interviews to collect data on the studied topic. The findings of this study indicate that, according to Saudi thought, the hijab should cover a woman’s face and conceal her identity. These findings also reveal that there are three types of hijabs: the Sahwa hijab, the current generation’s hijab, and the hijab of new generation. These hijabs have varying degrees of modesty, and the study participants expressed different levels of acceptance for each type. Changing the rules around hijab is difficult, and it impacts the reputations of both men and women. The study findings show that Saudis reject the notion that the hijab is associated with oppression, thus invalidating the perceived stigma of oppression linked to the hijab in the West. Saudis have varying views on female freedom, with most supporting men’s prerogative to prescribe women’s behaviour regarding the hijab. Finally, participants expressed varying opinions on the recent changes in Saudi society, with most participants being aware of the impact of these changes on women’s wearing of the hijab

Neural Correlates of Gain Control in Drosophila and Humans

Previous research has shown that visual sensitivity in human epilepsy patients is abnormal – characterized by increased responses at high contrast levels. These abnormalities have been linked to changes in neuronal gain control. Using animal models to study these changes is a useful approach. In this thesis, we used a steady-state visually evoked potential (SSVEP) technique similar to that used in humans to study photoreceptor-level and neuronal gain control in wild type (w-) Drosophila across a range of ages. We then compared these responses to those obtained from Drosophila carrying the kcc potassium channel mutation that renders young flies susceptible to light and shock-induced seizures. By taking into account the age and temperature dependence of the mutant (kccDHS1) flies, we were able to identify increased neural activity that recovers to the normal profile as they get older. We also found that these kccDHS1 flies are hypersensitive to light, particularly when young. These two findings are consistent with the fact that the level of the KCC protein increases with age. In addition, we found that kccDHS1 flies generate high frequency oscillations in their ERGs in response (50 – 100 Hz) to abrupt light onsets and offsets – a phenomenon that might be linked to abnormal changes in the gain control of neuronal feedback circuits. Studying visual abnormalities in Drosophila can reveal important information but eventually we need to link any visual abnormalities observed in animal models to humans. We therefore, attempted to measure subtle changes in gain control in humans due to adaptation, and at the same time make use of the human mental ability to measure another measure of gain control, attention, using an fMRI technique. Although our data did not show any interaction between adaptation and attention, it suggests that attention in early visual pathways largely affects the level of suppression in non-stimulated regions around the adaptor rather than responses to the probe itself. This is a manipulation that links to our work on adaptation in Drosophila in Chapter 6. Overall, the results presented in this thesis showed that fly models of epilepsy can be useful for studying changes in visual gain control, and showed that this work might be extended to humans

Spectrophotometric flow injection method for the determination of Bendiocarb insecticide in water samples using chromogenic reagent 2,4-dinitrophenylhydrazine

Objective: Bendiocarb (BEN) is an acutely toxic carbamate insecticide which is used in public places and agriculture. The present study describes a new, sensitive, and accurate flow injection analysis method for the determination of BEN in its pesticide formulations and water samples.Methods: The developed method is based on an alkaline hydrolysis of BEN in NaOH, and the resultant product was coupled with 2,4-dinitrophenylhdrazin in the presence of sodium periodate to form red-colored product which measured at 515 nm.Results: Under the optimum conditions established (sample volume 150 μL, flow rate 2 mL/min, with 75 cm reaction coil length) for spectrophotometric determination of Bendiocarb. Beer's law is obeyed in the range of 1–150 μg/mL with a detection limit of 0.738 μg/mL, with average recovery of 100.737 and relative standard deviation % of 1.331%.Conclusion: The established method was successfully applied for the determination of BEN in pesticide formulation and real spiked water sample

Scaling up stochastic gradient descent for non-convex optimisation

Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions and large datasets. We address the bottleneck problem arising when using both shared and distributed memory. Typically, the former is bounded by limited computation resources and bandwidth whereas the latter suffers from communication overheads. We propose a unified distributed and parallel implementation of SGD (named DPSGD) that relies on both asynchronous distribution and lock-free parallelism. By combining two strategies into a unified framework, DPSGD is able to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied for non-convex problems such as those arising in statistical modelling and machine learning. Our theoretical analysis shows that DPSGD leads to speed-up with respect to the number of cores and number of workers while guaranteeing an asymptotic convergence rate of O(1/T) given that the number of cores is bounded by T1 / 4 and the number of workers is bounded by T1 / 2 where T is the number of iterations. The potential gains that can be achieved by DPSGD are demonstrated empirically on a stochastic variational inference problem (Latent Dirichlet Allocation) and on a deep reinforcement learning (DRL) problem (advantage actor critic - A2C) resulting in two algorithms: DPSVI and HSA2C. Empirical results validate our theoretical findings. Comparative studies are conducted to show the performance of the proposed DPSGD against the state-of-the-art DRL algorithms

Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums

In MOOCs, identifying urgent comments on discussion forums is an ongoing challenge. Whilst urgent comments require immediate reactions from instructors, to improve interaction with their learners, and potentially reducing drop-out rates—the task is difficult, as truly urgent comments are rare. From a data analytics perspective, this represents a highly unbalanced (sparse) dataset. Here, we aim to automate the urgent comments identification process, based on fine-grained learner modelling—to be used for automatic recommendations to instructors. To showcase and compare these models, we apply them to the first gold standard dataset for Urgent iNstructor InTErvention (UNITE), which we created by labelling FutureLearn MOOC data. We implement both benchmark shallow classifiers and deep learning. Importantly, we not only compare, for the first time for the unbalanced problem, several data balancing techniques, comprising text augmentation, text augmentation with undersampling, and undersampling, but also propose several new pipelines for combining different augmenters for text augmentation. Results show that models with undersampling can predict most urgent cases; and 3X augmentation + undersampling usually attains the best performance. We additionally validate the best models via a generic benchmark dataset (Stanford). As a case study, we showcase how the naïve Bayes with count vector can adaptively support instructors in answering learner questions/comments, potentially saving time or increasing efficiency in supporting learners. Finally, we show that the errors from the classifier mirrors the disagreements between annotators. Thus, our proposed algorithms perform at least as well as a ‘super-diligent’ human instructor (with the time to consider all comments)

Prevalence and Correlation with Other Diagnoses in Physiotherapy Practice—A 5-Year Retrospective Review.

Abstract (1) Background: The objective of this study was to assess the prevalence of Developmental Dysplasia of the Hip (DDH) as a primary or secondary diagnosis during physiotherapy practice. No other studies have investigated the prevalence and associations of DDH within the practice of pediatric rehabilitation. (2) Methods: This retrospective review was performed on 12,225 physiotherapy referrals to the King Abdullah Specialized Children’s Hospital (KASCH), Riyadh, Kingdom of Saudi Arabia, from May 2016 to October 2021. Only DDH referrals for conservative treatment were included in the study. The plan for brace treatment was carried out by the pediatric orthopedics clinic in KASCH. The diagnostic methods were either a pelvic radiograph or ultrasound, depending on the participant’s age. DDH is considered one of the most common secondary complications for children with other medical diagnoses. (3) Results: The most common indication for referral was neurological diagnosis (44%), followed by orthopedic (28%), genetic (19%), cardiac (5%), ophthalmologic (3%), dermatologic (1%) and rheumatologic (0.5%) diagnoses. (4) Conclusion: The prevalence of DDH among all referrals in this study was 6%. In physiotherapy practice, neurologic, genetic, and orthopedic primary or secondary diagnoses were the most prevalent when DDH referrals were investigated. A relatively high prevalence of DDH in the pediatric rehabilitation clinic at KASCH in Riyadh was reported in this study.(1) Východiská: Cieľom tejto štúdie bolo posúdiť prevalenciu vývojovej dysplázie bedra (DDH) ako primárnej alebo sekundárnej diagnózy počas fyzioterapeutickej praxe. Žiadne iné štúdie neskúmali prevalenciu a asociácie DDH v praxi pediatrickej rehabilitácie. (2) Metódy: Tento retrospektívny prehľad bol vykonaný na 12 225 fyzioterapeutických odporúčaniach do Špecializovanej detskej nemocnice kráľa Abdulláha (KASCH), Rijád, Kráľovstvo Saudskej Arábie, od mája 2016 do októbra 2021. Do štúdie boli zahrnuté iba odporúčania DDH na konzervatívnu liečbu. Plán liečby realizovala klinika detskej ortopédie v KASCH. Diagnostické metódy boli buď rádiografia panvy alebo ultrazvuk, v závislosti od veku účastníka. DDH sa považuje za jednu z najčastejších sekundárnych komplikácií u detí s inými medicínskymi diagnózami. (3) Výsledky: Najčastejšou indikáciou na odoslanie bola neurologická diagnóza (44 %), nasledovala ortopedická (28 %), genetická (19 %), kardiálna (5 %), oftalmologická (3 %), dermatologická (1 %) a reumatologické (0,5 %) diagnózy. (4) Záver: Prevalencia DDH medzi všetkými odporúčaniami v tejto štúdii bola 6 %. Vo fyzioterapeutickej praxi boli neurologické, genetické a ortopedické primárne alebo sekundárne diagnózy najrozšírenejšie, keď sa skúmali odporúčania DDH. V tejto štúdii bola hlásená relatívne vysoká prevalencia DDH na pediatrickej rehabilitačnej klinike v KASCH v Rijáde.(1) Background: The objective of this study was to assess the prevalence of Developmental Dysplasia of the Hip (DDH) as a primary or secondary diagnosis during physiotherapy practice. No other studies have investigated the prevalence and associations of DDH within the practice of pediatric rehabilitation. (2) Methods: This retrospective review was performed on 12,225 physiotherapy referrals to the King Abdullah Specialized Children’s Hospital (KASCH), Riyadh, Kingdom of Saudi Arabia, from May 2016 to October 2021. Only DDH referrals for conservative treatment were included in the study. The plan for brace treatment was carried out by the pediatric orthopedics clinic in KASCH. The diagnostic methods were either a pelvic radiograph or ultrasound, depending on the participant’s age. DDH is considered one of the most common secondary complications for children with other medical diagnoses. (3) Results: The most common indication for referral was neurological diagnosis (44%), followed by orthopedic (28%), genetic (19%), cardiac (5%), ophthalmologic (3%), dermatologic (1%) and rheumatologic (0.5%) diagnoses. (4) Conclusion: The prevalence of DDH among all referrals in this study was 6%. In physiotherapy practice, neurologic, genetic, and orthopedic primary or secondary diagnoses were the most prevalent when DDH referrals were investigated. A relatively high prevalence of DDH in the pediatric rehabilitation clinic at KASCH in Riyadh was reported in this study

Predicting the porosity in selective laser melting parts using hybrid regression convolutional neural network

Assessing the porosity in Selective Laser Melting (SLM) parts is a challenging issue, and the drawback of using the existing gray value analysis method to assess the porosity is the difficulty and subjectivity in selecting a uniform grayscale threshold to convert a single slice to binary image to highlight the porosity. This paper proposes a new approach based on the use of a Regression Convolutional Neural Network (RCNN) algorithm to predict the percent of porosity in CT scans of finished SLM parts, without the need for subjective difficult thresholding determination to convert a single slice to a binary image. In order to test the algorithm, as the training of the RCNN would require a large amount of experimental data, this paper proposed a new efficient approach of creating artificial porosity images mimicking the real CT scan slices of the finished SLM part with a similarity index of 0.9976. Applying RCNN improved porosity prediction accuracy from 68.60% for image binarization method to 75.50% using the RCNN. The algorithm was then further developed by optimizing its parameters using Bees Algorithm (BA), which is known to mimic the behavior of honeybees, and the hybrid Bees Regression Convolutional Neural Network (BA-RCNN) produced better prediction accuracy with a value of 85.33%