Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep learning for prediction of isocitrate dehydrogenase mutation in gliomas: a critical approach, systematic review and meta-analysis of the diagnostic test performance using a Bayesian approach

Background Conventionally, identifying isocitrate dehydrogenase (IDH) mutation in gliomas is based on histopathological analysis of tissue specimens acquired via stereotactic biopsy or definitive resection. Accurate pre-treatment prediction of IDH mutation status using magnetic resonance imaging (MRI) can guide clinical decision-making. We aim to evaluate the diagnostic performance of deep learning (DL) to determine IDH mutation status in gliomas. Methods A systematic search of Cochrane Library, Web of Science, Medline, and Scopus was conducted to identify relevant publications until August 1, 2021. Articles were included if all the following criteria were met: (I) patients with histopathologically confirmed World Health Organization (WHO) grade II, III, or IV gliomas; (II) histopathological examination with the IDH mutation; (III) DL was used to predict the IDH mutation status; (IV) sufficient data for reconstruction of confusion matrices in terms of the diagnostic performance of the DL algorithms; and (V) original research articles. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) was used to assess the studies' quality. Bayes theorem was utilized to calculate the posttest probability. Results Four studies with a total of 1,295 patients were included. In the training set, the pooled sensitivity, specificity, and area under the summary receiver operating characteristic (SROC) curve were 93.9%, 90.9% and 0.958, respectively. In the validation set, the pooled sensitivity, specificity, and area under the SROC curve were 90.8%, 85.5% and 0.939, respectively. With a known pretest probability of 80.2%, the Bayes theorem yielded a posttest probability of 97.6% and 96.0% for a positive test and 27.0% and 30.6% for a negative test for training sets and validation sets, respectively. Discussion This is the first meta-analysis that summarizes the diagnostic performance of DL in predicting IDH mutation status in gliomas via the Bayes theorem. DL algorithms demonstrate excellent diagnostic performance in predicting IDH mutation in gliomas. Radiomic features associated with IDH mutation, and its underlying pathophysiology extracted from advanced MRI may improve prediction probability. However, more studies are required to optimize and increase its reliability. Limitations include obtaining some data via email and lack of training and test sets statistics.
Geometry of silent chain - involute sprocket

Silent chains tend to have more and more usage in automotive industry. The study of these types of chains has a lot to consider due to the fact that silent chains are not standardized yet. The aim of this paper is to study and analyse the theoretical contact point between a silent chain’s toothed plate and an involute sprocket. Varying different parameters of the chain and sprocket, there will be studied its effects on the theoretical contact point and the sprocket’s profile geometry.
Investigating the use of Appreciative Inquiry as a process for coach development within a National Governing Body talent development programme

ABSTRACT Coach development continues to be positioned as a ‘problem to be solved’ for national governing bodies (NGBs) with policy makers persisting in their quest to find an effective solution to bring about sustained change. Here, we suggest that coach development should instead consider a strength-based approach to change in an effort to build on current practice. This study, conducted ‘in-situ’ by the Head of Performance, focused on coach development within a NGB field hockey talent development programme. In a shift from the traditional ‘top down’, cut and paste approach to change interventions synonymous with coach development, this study adopted an appreciative inquiry (AI) approach that focuses on strengths and collaboration within groups and has been found to assist in the identification of new ways of working. The results showed that by adopting an AI framework to coach development, the themes of positivity and collaboration leading to generativity were integral to coach development within a NGB talent development programme. Positivity was clearly a highlight in this context as findings indicate that coaches were highly motivated to interrogate new ideas through a positive mindset. Similarly, results show that the collaborative approach to change and personal learning ensured a sustained movement towards the collective vision for the programme. Interestingly, results also show the theme of complexity when adopting an AI approach to coach learning and the need to maintain an element of flexibility that does not follow a ‘clean’ approach to AI that is often reported within the literature. Lastly, the importance of facilitation from the researcher was highlighted within the inquiry and sheds new light into the complexity of coach learning in a collaborative setting. This investigation highlights the potential of strengths-based inquiry in relation to coach development and provides a rich insight into context specific personal development within coaching.
Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits

Recently, a dynamic development of intermittent renewable energy sources (RES) has been observed. In order to allow for the adoption of trading contracts for unplanned events and changing weather conditions, the day-ahead markets have been complemented by intraday markets; in some countries, such as Poland, balancing markets are used for this purpose. This research focuses on a small RES generator, which has no market power and sells electricity through a larger trading company. The generator needs to decide, in advance, how much electricity is sold in the day-ahead market. The optimal decision of the generator on where to sell the production depends on the relation between prices in different markets. Unfortunately, when making the decision, the generator is not sure which market will offer a higher price. This article investigates the possible gains from utilizing forecasts of the price spread between the intraday/balancing and day-ahead markets in the decision process. It shows that the sign of the price spread can be successfully predicted with econometric models, such as ARX and probit. Moreover, our research demonstrates that the statistical measures of forecast accuracy, such as the percentage of correct sign classifications, do not necessarily coincide with economic benefits.
The Associations between Religion, Impulsivity, and Externalizing Behaviors in the Adolescent Brain Cognitive Development (ABCD) Study

ABSTRACT In studies of adolescents and adults, religiosity has been identified as a protective factor for impulsivity-related behaviors and externalizing problems. No known studies to date have examined the relationship between religiosity and such outcomes in children. Thus, the current study examined in children whether (1) religion is associated with decreased impulsivity and externalizing symptoms, and if (2) religiosity is a protective factor in the association between impulsivity and externalizing symptoms. Data were from Wave 1 of the Adolescent Brain Cognitive Development (ABCD) study (children aged 9–10, N = 11,875). Two self-report measures and the Cash Choice Task assessed impulsivity; the Child Behavior Checklist assessed externalizing symptoms; and child religiosity was assessed in parent interviews. Structural equation models examined religiosity (affiliation, service attendance, importance) as a moderator between impulsivity and externalizing symptoms. Greater religious attendance was significantly associated with decreased impulsivity. Christian affiliation was associated with increased impulsivity as compared to other religions. Contrary to our hypotheses, religiosity did not moderate associations between impulsivity and externalizing symptoms. Findings suggest that impulsivity and externalizing behaviors are related to some domains of religiosity in children; however, the magnitude of the effect sizes was small, suggesting religiosity is not a particularly salient predictor of externalizing problems in children. Given these findings differ from those seen in studies of adolescents and adults, future studies should consider longitudinal designs to better understand how these relationships form across the lifespan.
Examining the Effects of Challenges Faced in Green Construction on Project Outcomes: A Chinese Perspective

This study aims to investigate the common challenges that project managers encounter while managing green building construction projects and their impact on project success. Furthermore, the study aims to examine the mediating effect of project performance in the relationship between project management challenges related to green construction and their success. This paper seeks to contribute to the green construction in China. In total 500 questionnaires were distributed, and 376 completed survey questionnaires were received. Structural equation modelling (SEM) using AMOS was conducted to check various proposed relationships. The results reveal that Challenge 2 and Challenge 5 are insignificant and have no impact on project success, whereas Challenges 1, 3 and 4 are found to be the predictors of project success. No mediation effect of project performance is found between Challenges 1 and 5 and project success. However, a partial mediation effect is found between Challenge 1 and project success.
Vessel wall magnetic resonance and arterial spin labelling imaging in the management of presumed inflammatory intracranial arterial vasculopathy

Abstract Optimal criteria for diagnosing and monitoring response to treatment for infectious and inflammatory medium–large vessel intracranial vasculitis presenting with stroke are lacking. We integrated intracranial vessel wall MRI with arterial spin labelling into our routine clinical stroke pathway to detect presumed inflammatory intracranial arterial vasculopathy, and monitor disease activity, in patients with clinical stroke syndromes. We used predefined standardized radiological criteria to define vessel wall enhancement, and all imaging findings were rated blinded to clinical details. Between 2017 and 2018, stroke or transient ischaemic attack patients were first screened in our vascular radiology meeting and followed up in a dedicated specialist stroke clinic if a diagnosis of medium–large inflammatory intracranial arterial vasculopathy was radiologically confirmed. Treatment was determined and monitored by a multi-disciplinary team. In this case series, 11 patients were managed in this period from the cohort of young stroke presenters (<55 years). The median age was 36 years (interquartile range: 33,50), of which 8 of 11 (73%) were female. Two of 11 (18%) had herpes virus infection confirmed by viral nucleic acid in the cerebrospinal fluid. We showed improvement in cerebral perfusion at 1 year using an arterial spin labelling sequence in patients taking immunosuppressive therapy for >4 weeks compared with those not receiving therapy [6 (100%) versus 2 (40%) P = 0.026]. Our findings demonstrate the potential utility of vessel wall magnetic resonance with arterial spin labelling imaging in detecting and monitoring medium–large inflammatory intracranial arterial vasculopathy activity for patients presenting with stroke symptoms, limiting the need to progress to brain biopsy. Further systematic studies in unselected populations of stroke patients are needed to confirm our findings and establish the prevalence of medium–large artery wall inflammation.
Nephrotoxic effect of Hydrogen Cyanamide (Dormex) and possible protective role of N-acetyl cysteine in male albino rats

Background: Dormex is a highly toxic fertilizer that causes local tissue irritation in addition to multiple organ toxicity mainly through oxidative stress. Aim of the study: This study aimed to investigate nephrotoxic effect of dormex and to evaluate potential protective role of N-acetyl cysteine (NAC) on kidney of male albino rats. Methods: This study was conducted on forty mature male albino rats were distributed to; Group I, II: rats were given normal saline and NAC, respectively. Group III: rats received single dose of dormex. Group IV: rats were given the same dose of dormex plus NAC. Blood urea and serum creatinine were assessed. Oxidative stress markers as malondialdehyde (MDA), catalase, reduced glutathione and superoxide dismutase (SOD ) were measured. Renal specimens were studied with hematoxylin and eosin. Results: Renal indices, urea and creatinine, MDA were significantly increased, while glutathione reductase, catalase and glutathione peroxidase were lowered significantly in experimental rats received dormex. Kidney tissue of dormex administered rat’s revealed tubulointerstitial nephritis, tubular necrosis and obstruction. Treatment with NAC markedly improved oxidative stress parameters but did not show marked effect on dormex induced histopathological changes. Conclusions: It can be concluded that dormex triggers oxidative stress causing affection of the renal function. Although NAC could decrease oxidative stress, it was not able to protect against cellular toxicity of dormex.
Linkage between Gold and Stock Return: Evidence from Nonlinear Causality and Rolling Window Volatility Spillover

This paper investigates nonlinear causality relationship between gold and stock return in the USA for the period of December 1969-November 2021. The nonlinearity is detected in both series, and nonlinear unit root tests are applied for each variable. It is seen that both return series are nonlinear stationary according to whole nonlinear unit root findings. There is unidirectional nonlinear Granger causality from stock to gold return in all lags, except lag three, whereas there is unidirectional nonlinear Granger causality from gold to stock return just in lag three. So, this finding reflects safe haven seeking of investors between gold and stock markets. Moreover, causality findings of volatility spillover display that causal link is from gold to stock return before 2000, and shift direction after 2000. Meanwhile, rolling window spillover causality is employed from beginning to ending period in 120 month fixed range of consecutive movement. It is attained that bidirectional reciprocal causality exists and mainly present at the fixed periods among December 1999-January 2015, mirror financial crisis impact.
Vanishing Schistosomiasis Endemicity in North of Khuzestan Province, Iran: A Twenty-Five-Year Assessment

Background: Schistosomiasis, after malaria, is the second most important parasitic disease in the world in terms of morbidity and mortality and is one of the 14 neglected tropical diseases. In 2016, about 206.4 million people needed preventive treatment for the disease. Objectives: This study evaluated schistosomiasis’s incidence rate and spatial-temporal cluster distribution in the north of Khuzestan province, Iran. Methods: This cross-sectional study collected data from January 1977 to December 2001. The data of 1,390 definitive patients with Schistosoma haematobium in the north of Khuzestan province, Iran, were analyzed for the disease incidence in rural districts over five-year periods. Also, the changes in median age and sex were examined. Spatial scan statistics were used to diagnose and evaluate the spatial clusters of S. haematobium cases. The pure retrospective temporal analysis and retrospective spatial-temporal analysis were carried out to identify the temporal clusters and spatial-temporal clusters of schistosomiasis with high rates, respectively, using the discrete Poisson model. Results: The schistosomiasis incidence decreased over the years, with the last case reported in 2001. Using Kulldorff’s spatial scan method, spatial clustering showed nine high-risk areas in the north of Khuzestan province from 1977 to 2001. Besides, S. haematobium was not randomly distributed in this area. Spatial-temporal clusters identified three high-risk areas during the study period. Temporal clusters decreased from 17 months and five days to one day, and they mainly occurred in the winter and summer. Conclusions: The study indicated a zero incidence and vanishing S. haematobium endemicity in the northern region of Khuzestan province of Iran in 2002. Due to snail vectors of the disease resident in this region, the disease surveillance still needs continuation.
Deep-Learning-Based Wireless Visual Sensor System for Shiitake Mushroom Sorting

The shiitake mushroom is the second-largest edible mushroom in the world, with a high nutritional and medicinal value. The surface texture of shiitake mushrooms can be quite different due to different growing environments, consequently leading to fluctuating market prices. To maximize the economic profit of the mushroom industry, it is necessary to sort the harvested mushrooms according to their qualities. This paper aimed to develop a deep-learning-based wireless visual sensor system for shiitake mushroom sorting, in which the visual detection was realized by the collection of images and cooperative transmission with the help of visual sensors and Wi-Fi modules, respectively. The model training process was achieved using Vision Transformer, then three data-augmentation methods, which were Random Erasing, RandAugment, and Label Smoothing, were applied under the premise of a small sample dataset. The training result of the final model turned out nearly perfect, with an accuracy rate reaching 99.2%. Meanwhile, the actual mushroom-sorting work using the developed system obtained an accuracy of 98.53%, with an 8.7 ms processing time for every single image. The results showed that the system could efficiently complete the sorting of shiitake mushrooms with a stable and high accuracy. In addition, the system could be extended for other sorting tasks based on visual features. It is also possible to combine binocular vision and multisensor technology with the current system to deal with sorting work that requires a higher accuracy and minor feature identification.
Utilization of Pharmacokinetic/Pharmacodynamic Modeling in Pharmacoepidemiological Studies: A Systematic Review on Antiarrhythmic and Glucose-Lowering Medicines

Introduction: In human pharmacology, there are two important scientific branches: clinical pharmacology and pharmacoepidemiology. Pharmacokinetic/pharmacodynamic (PK/PD) modeling is important in preclinical studies and randomized control trials. However, it is rarely used in pharmacoepidemiological studies on the effectiveness and medication safety where the target population is heterogeneous and followed for longer periods. The objective of this literature review was to investigate how far PK/PD modeling is utilized in observational studies on glucose-lowering and antiarrhythmic drugs. Method: A systematic literature search of MEDLINE, Embase, and Web of Science was conducted from January 2010 to 21 February 2020. To calculate the utilization of PK/PD modeling in observational studies, we followed two search strategies. In the first strategy, we screened a 1% random set from 95,672 studies on glucose-lowering and antiarrhythmic drugs on inclusion criteria. In the second strategy, we evaluated the percentage of studies in which PK/PD modeling techniques were utilized. Subsequently, we divided the total number of included studies in the second search strategy by the total number of eligible studies in the first search strategy. Results: The comprehensive search of databases and the manual search of included references yielded a total of 29 studies included in the qualitative synthesis of our systematic review. Nearly all 29 studies had utilized a PK model, whereas only two studies developed a PD model to evaluate the effectiveness of medications. In total, 16 out of 29 studies (55.1%) used a PK/PD model in the observational setting to study effect modification. The utilization of PK/PD modeling in observational studies was calculated as 0.42%. Conclusion: PK/PD modeling techniques were substantially underutilized in observational studies of antiarrhythmic and glucose-lowering drugs during the past decade.
Manual 3D Control of an Assistive Robotic Manipulator Using Alpha Rhythms and an Auditory Menu: A Proof-of-Concept

Brain–Computer Interfaces (BCIs) have been regarded as potential tools for individuals with severe motor disabilities, such as those with amyotrophic lateral sclerosis, that render interfaces that rely on movement unusable. This study aims to develop a dependent BCI system for manual end-point control of a robotic arm. A proof-of-concept system was devised using parieto-occipital alpha wave modulation and a cyclic menu with auditory cues. Users choose a movement to be executed and asynchronously stop said action when necessary. Tolerance intervals allowed users to cancel or confirm actions. Eight able-bodied subjects used the system to perform a pick-and-place task. To investigate the potential learning effects, the experiment was conducted twice over the course of two consecutive days. Subjects obtained satisfactory completion rates (84.0 ± 15.0% and 74.4 ± 34.5% for the first and second day, respectively) and high path efficiency (88.9 ± 11.7% and 92.2 ± 9.6%). Subjects took on average 439.7 ± 203.3 s to complete each task, but the robot was only in motion 10% of the time. There was no significant difference in performance between both days. The developed control scheme provided users with intuitive control, but a considerable amount of time is spent waiting for the right target (auditory cue). Implementing other brain signals may increase its speed.