Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical study of the utility of bioengineering technique for slope stabilisation

ABSTRACT The bioengineering technique of slope stabilisation, which has been developed as a sustainable alternative to traditional civil engineering structures, requires more scientific research and a good understanding of the factors that influence its effectiveness since many a time it fails to provide the desired outcome. The present study discusses the importance of understanding the variable root distribution and root-soil-slope relationship before implementation. The probabilistic analysis was used to take into account the natural variability of root features, which includes root length, strength, branching and orientation along with heterogeneity of slope material. It was observed that the mean rooting depth plays a vital role in deciding the utility of the bioengineering technique. Though its effect in gentle slopes is negligible, in the case of moderate to steep slopes, it can significantly affect the overall stability. Improper planning can lead to aggravation of the situation leading the slope more vulnerable to failure. Furthermore, the stabilisation using vegetation is best suitable for moderate slope inclinations, and the maximum shear strength increase is obtained for slope inclining around 50°. A gradual reduction in overall stability was observed with the reduction of mean rooting depth and an increase in the spacing of the plants.
Risk Analysis of Collapse for Tunnels Constructed by Drill and Blast Method

The occurrence of collapse is common in tunnels constructed by drill and blast method.It often brings about serious or even disastrous damage to construction works.Hence this paper was drawn up to review the main aspects related to collapse,to identify and evaluate its risk,and to present a risk analysis procedure for it.Firstly,risk factors are identified on the basis of an extensive collection of collapse cases.To show the main causes and mechanisms of collapse,the statistical analysis and the fault tree analysis are carried out,and risk factors ranking is given.Secondly,event tree analysis is employed to evaluate the collapse probability.And the analytic hierarchy process is used to evaluate the potential loss of collapse.Risk matrix method is employed in the following risk assessment.Then a flowchart for tunnel collapse risk analysis is presented,which provides an effective way to avoid or minimize the consequences of collapse during tunnel construction.
Methodology of exploring and analyzing the VOC based on extensive web data source

In order to track the market trends and obtain full understanding of Voice of Customers (VOC), a new method of analyzing dynamic product information through the web media was presented. Based on the analysis of advantages/disadvantages of the distributed and concentrated web data source, a systematic mapping relationship, from the original web source to structured marketing data setting, was established. Then a knowledge base organized on features of Products' Lifecycle Stage (PLS), as well as the involved quantitative rules used in classifying the VOC information, was developed. So, the rule-driven data mining method was applied to identify the PLS classification of the original data cell. Furthermore the methods of frequency counting and content analyzing were conducted to the data cell consequently so that both market trend and a systematic understanding of VOC could be obtained. Finally, a detailed process was presented by using typical web data on automotive product.
A deep learning approach for COVID-19 screening and localization on chest x-ray images

Chest X-ray (CXR) images have a high potential in the monitoring and examination of various lung diseases, including COVID-19. However, the screening of a large number of patients with diagnostic hypothesis for COVID-19 poses a major challenge for physicians. In this paper, we propose a deep learning-based approach that can simultaneously suggest a diagnose and localize lung opacity areas in CXR images. We used a public dataset containing 5, 639 posteroanterior CXR images. Due to unbalanced classes (69.2% of the images are COVID-19 positive), data augmentation was applied only to images belonging to the normal category. We split the dataset into train and test sets with proportional rate at 90:10. To the classification task, we applied 5-fold cross-validation to the training set. The EfficientNetB4 architecture was used to perform this classification. We used a YOLOv5 pre-trained in COCO dataset to the detection task. Evaluations were based on accuracy and area under the ROC curve (AUROC) metrics to the classification task and mean average precision (mAP) to the detection task. The classification task achieved an average accuracy of 0.83 ± 0.01 (95% CI [0.81, 0.84]) and AUC of 0.88 ± 0.02 (95% CI [0.85, 0.89]) in 5-fold over the test dataset. The best result was reached in fold 3 (0.84 and 0.89 of accuracy and AUC, respectively). Positive results were evaluated by the opacity detector, which achieved a mAP of 59.51%. Thus, the good performance and rapid diagnostic prediction make the system a promising means to assist radiologists in decision making tasks.
Aryl Hydrocarbon Receptor (AhR) Limits the Inflammatory Responses in Human Lung Adenocarcinoma A549 Cells via Interference with NF-κB Signaling

Apart from its role in the metabolism of carcinogens, the aryl hydrocarbon receptor (AhR) has been suggested to be involved in the control of inflammatory responses within the respiratory tract. However, the mechanisms responsible for this are only partially known. In this study, we used A549 cell line, as a human model of lung alveolar type II (ATII)-like cells, to study the functional role of the AhR in control of inflammatory responses. Using IL-1β as an inflammation inducer, we found that the induction of cyclooxygenase-2 and secretion of prostaglandins, as well as expression and release of pro-inflammatory cytokines, were significantly higher in the AhR-deficient A549 cells. This was linked with an increased nuclear factor-κB (NF-κB) activity, and significantly enhanced phosphorylation of its regulators, IKKα/β, and their target IκBα, in the AhR-deficient A549 cells. In line with this, when we mimicked the exposure to a complex mixture of airborne pollutants, using an organic extract of reference diesel exhaust particle mixture, an exacerbated inflammatory response was observed in the AhR-deficient cells, as compared with wild-type A549 cells. Together, the present results indicate that the AhR may act as a negative regulator of the inflammatory response in the A549 model, via a direct modulation of NF-κB signaling. Its role(s) in the control of inflammation within the lung alveoli exposed to airborne pollutants, especially those which simultaneously activate the AhR, thus deserve further attention.
Vitamin D replacement in children with acute wheeze: a dose-escalation study

Meta-analyses report protective effects of vitamin D supplementation against asthma exacerbations and acute respiratory infections in adults [1–3], but data relating to effects of vitamin D on risk of preschool wheeze and asthma attacks in childhood are more limited [4]. In preparation for a randomised controlled trial (RCT) of vitamin D in children with recurrent preschool wheeze or school-age asthma, we carried out a dose-escalation study to find the daily vitamin D3 supplementation regimen that is most effective in elevating circulating 25-hydroxyvitamin D (25(OH)D) concentrations in these children. We hypothesised that daily oral vitamin D3 supplementation of 1000 IU would be more effective than 400 IU (UK recommendation [5]) in elevating the circulating 25(OH)D concentration to ≥75 nmol·L−1 at 3 months in vitamin-D-insufficient children with recurrent preschool wheeze or school-age asthma. Vitamin D supplementation at the current UK recommended level (400 IU·day−1) or enhanced supplementation (1000 IU·day−1) failed to achieve adequate levels of vitamin D (>75 nmol·L−1) in vitamin-D-insufficient children with acute wheeze https://bit.ly/3J43Ouo
Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases

The SARS-CoV-2 (COVID-19) disease rapidly spread worldwide, thus increasing the need to create new strategies to fight it. Several researchers in different fields have attempted to develop methods to early identifying it and mitigating its effects. The Deep Learning (DL) approach, such as the Convolutional Neural Networks (CNNs), has been increasingly used in COVID-19 diagnoses. These models intend to support decision-making and are doing well to detecting patient status early. Although DL models have good accuracy to support diagnosis, they are vulnerable to Adversarial Attacks. These attacks are new methods to make DL models biased by adding small perturbations on the original image. This paper investigates the impact of Adversarial Attacks on DL models for classifying X-ray images of COVID-19 cases. We focused on the attack Fast Gradient Sign Method (FGSM), which aims to add perturbations to the testing images by combining a perturbation matrix, producing a crafted image. We conduct the experiments analyzing the model’s performance attack-free and adding attacks. The following CNNs models were selected: DenseNet201, ResNet-50V2, MobileNetV2, NasNet and VGG16. In the attack-free environment, we reach precision around 99%. When it adds the attack, our results revealed that all models suffer from performance reduction, and the most affected was MobileNet that reduced its ability from 98.61% to 67.73%. However, the VGG16 network showed to be the least affected by the attacks. Our finds describe that DL models for COVID-19 are vulnerable to Adversarial Examples. The FGSM was capable of fooling the model, resulting in a significant reduction in the DL performance.
Perceptions of Learning among Sport Management Students at a Short-Term, High-Profile Sporting Event Volunteer Opportunity

Abstract Volunteering at short-term, high-profile sporting events has become an increasingly popular form of experiential learning within the sport management discipline. Thus, the purpose of this study was to explore perceptions of sport management student volunteers regarding outcomes of their participation in this endeavor. Data was collected via surveys emailed to students at the conclusion of their volunteer experience. Quantitative results (n = 54) yielded many findings, including levels of students’ perceived learning in a number of transferable skill areas and career management competencies. Further, the results showed that this learning was primarily derived from engaging in assigned duties, speaking with event attendees, and informal meetings/conversations with faculty during the trip as opposed to formal training activities. Qualitative results provided some insight into disadvantages that may have diminished the learning experience for students. These results yield practical implications for educators and event managers, while also suggesting potential future research directions.
Validation of Self-Assessed Form of Diagnostic Criteria for Psychosomatic Research Adapted from Diagnostic Criteria for Psychosomatic Research - Structured Interview

Background: As the diagnostic criteria for psychosomatic research-structured interview (DCPR-SI) is a rater-assessed questionnaire, it has not been used vastly in community-based studies and clinics. Describing and investigating self-assessed form of DCPR are an attempt to apply it easier and more worthwhile for medical settings. The aim of this study was to describe and present self-assessed form of DCPR self-assessed (DCPR-SA) and test its validity and reliability. Materials and Methods: The DCPR-SI was translated to Persian according to the best practice methodology and the guideline for adaptation of self-report measures. In this cross-sectional study, 540 patients and healthy individuals were recruited and answered DCPR-SA and some related questionnaires. Inter-rater (test–interview) and test–retest reliability were determined. Construct, concurrent, discriminant, and known-group validity were tested. Results: The kappa coefficients were expressed substantial and almost perfect agreement (0.617–0.784, P ≤ 0.05). In addition, phi correlation coefficients were indicated adequate test–retest reliability for each cluster (0.548–0.754, P ≤ 0.05). Three domains (anxiety-related symptoms, functional symptoms, and dysfunctional traits and emotional patterns) were confirmed by factor analysis. The results of the discriminate validity analysis were promising. Conclusion: The findings show that the DCPR-SA is valid and reliable and can be used by medical professionals as a psychosomatic screening tool and can be used properly in Persian-speaking population.
Design of High-speed Spindle Dynamic Balancing Device's Drive

This paper analyzes the principle of electromagnetic dynamic balancing device of high-speed spindle. According to the equilibrator and clutch working sequence,the drive to activate the balancing device was de- signed,based on AT89C51 and PMM8713,to control the electromagnetic dynamic balancing device in real time.Designing the system can ensure dynamic balancing device work well and improve the quality of ma- chined part in the machining process.
Application of Indirect Adaptive Fuzzy Sliding Mode Control in Arc Furnace

The sliding mode control was combined with the fuzzy control and was applied to the electrode regulator systems of arc furnace, and the detailed design procedure of the adaptive fuzzy sliding mode control system was proposed.The adaptive fuzzy control was utilized to approach the uncertain parameter of sliding mode control, a switching-type control was added in order to guarantee the sliding condition, and then the adaptive law was derived.The parameter of the adaptive fuzzy control was adjusted on-line to deal with the electrode regulator systems of arc furnace uncertainty.The results of simulation show that this proposed arithmetic of control can restrain the disturbance of arc length effectively, accordingly obtains much better dynamic characteristics.
Does local planning culture influence the effectiveness of impact assessments?: reflecting on infrastructure projects in a Dutch UNESCO World Heritage site

ABSTRACT We explore whether local planning culture influences the effectiveness of heritage impact assessment (HIA) and we discuss the legitimacy of ICOMOS, the international advisory body to UNESCO on cultural heritage. We examined the HIA processes for two proposed infrastructure projects that potentially could affect the Defence Line of Amsterdam World Heritage site in the Netherlands. We interviewed key stakeholders involved in decision-making about these projects, and found that the Dutch planning culture positively influenced the effectiveness of the HIA processes. The interviewees predominantly discussed the substantive and transactive effectiveness of the HIA processes in that they praised the practitioner for facilitating a clear, inclusive and transparent process and having a solution-oriented mindset, which is common practice in the Dutch planning culture. However, in contrast to the Dutch planning culture, the role of ICOMOS was perceived as opaque and a ‘black box’, although this did not decrease its legitimacy among the key stakeholders.
Enhanced feature pyramidal network for object detection

Abstract. Powerful features, which contain more representative information, have become increasingly important in object detection. We exploit the attention mechanism and dilated convolution to strengthen the features used to construct the original feature pyramid network (FPN) and introduce a network that combines the dilated convolution and attention mechanism based on FPN (DAFPN). Specifically, motivated by the attention mechanism, a level-independent attention module (LIAM) is proposed to make high-level feature maps focus on semantic information and low-level feature maps concentrate on spatial information. Meanwhile, we present a pyramidal dilated convolution module (PDCM) that replaces standard convolution with dilated convolution. Instead of previous works that use the same dilation rate for all scales of feature maps, the PDCM applies dilation convolution with various dilation rates to enlarge the effective receptive field of each level’s feature maps suitably. Extensive experiments show that our DAFPN achieves extraordinary performance compared to the state-of-the-art FPN-based detectors on MS COCO benchmark.
Influence of Inter-car Wind-shield Schemes on Aerodynamic Performance of High-speed Trains

Based on a simplified CRH380 model consisting of 3 cars,the influence of 7 inter-car wind-shield schemes on the aerodynamic performance of cars and car-connecting parts was numerically studied at train speeds of 360,420,500 km/h.The analysis and contrast results indicate as follows: The types of inter-car wind-shield schemes have little influence on the aerodynamic pressure drag and viscous drag of cars;the influence of upper and lower wind-shields on the lift of cars is stronger than that of side wind-shields;comparing with the drag of the CRH380 typical wind-shield connecting-parts,the drag of the enclosed wind-shield connecting-parts is about 7% of it,which is the minimum;the drag in the absence of wind-shield connecting-parts is about 50%;and the drag of a connecting-part with upper,lower and both-side wind-shields is about 30%. Considering aerodynamic performance and easy implementation,the scheme with upper,lower and both-side enclosed wind-shields is more suitable for high-speed trains than other wind-shield schemes.
Environmental context and socio-economic status drive plastic pollution in Australian cities

Plastic pollution is a critical environmental concern. There is a growing focus on this transboundary issue, and a corresponding increase in public and government awareness. Understanding the key factors associated with litter and mismanaged waste on land will help to predict where and how waste enters the environment, providing opportunities for low cost, effective interventions. There exist only a few large-scale datasets with which such analyses can be conducted. To fill this knowledge gap we analysed a national, designed survey dataset of litter in the environment from Keep Australia Beautiful (2007–2017). We found that debris decreased significantly, with a nearly 6% decrease over the decade. Using generalised additive model modelling of 17 653 surveys at 983 sites around Australia, we found that site type, land use, state, population, and socio-economic status had the strongest relationships (in decreasing order) with litter distribution. Higher levels of litter were found in economically and socially disadvantaged neighbourhoods. Site types related to transitory human use such as highways and carparks, had more litter than areas with higher aesthetic or cultural value such as beaches, parks, and residential neighbourhoods. Sites that were sources of litter, such as shopping centres and retail strips, also had elevated litter counts, as did surveys near waterways. This enhanced understanding of the factors that influence litter deposition will help to craft more effective policy solutions, and can also improve our models of litter loads on land, and subsequent input to the ocean.
New-Onset Atrial Fibrillation Is a Risk Factor of Ischemic Stroke in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) induces atrial fibrillation (AF) and stroke, and COPD with AF increased ischemic stroke (IS) in a cross-sectional study. Therefore, healthcare providers must be concerned and well-informed about this particular situation. For this study, inpatient data were obtained from the Taiwan National Health Insurance Database in 2010. We identified patients who were hospitalized with COPD (International Classification of Disease, Ninth Revision, Clinical Modification [ICD-9-CM] is 491, 492, and 496). Patients who experienced AF (ICD-9-CM to 427.3) during the same admission or after COPD hospitalization were discharged and defined as new-onset AF. The outcome was IS (ICD-9-CM as 433–437). The factors related to IS after COPD were used for multivariate logistic regression. There were 4177/62,163 (6.72%) patients with incident IS. The risk of IS after COPD hospitalization was shown to have an adjusted odds ratio of 1.749 (95% CI: 1.584–1.93, p < 0.001) for patients with new-onset AF. Other factors included advanced age, atherosclerosis factors, comorbidity severity, sepsis and lower-level hospital admission. In conclusion, COPD patients suffering from new-onset AF had an increased incidence of IS in the population observation study. New-onset AF was an omit risk factor for IS in COPD in the Chinese population.
Addition of Inhalation Training Devices and Smartphone Application to Verbal Counseling for Asthmatic Patients

Background: One of the main issues with pressurized metered dose inhalers (pMDI) is that some patients find it difficult to use it properly. Methods: This study was carried out to compare the effect of traditional verbal counseling and that of adding an inhalation training device, such as Flo-Tone or Clip-Tone, along with a smartphone application on the incidence of inhalation technique mistakes and the pulmonary function of asthmatic adults and children. Results: The lung function of those in the advanced counseling group significantly improved on the second visit (p < 0.001), whereas for those in the verbal counseling group, their lung function only improved on the third visit (p < 0.001). For both the groups, the mean number of mistakes in regard to the steps in inhalation technique decreased significantly (p < 0.001), with an overall higher percentage in the advanced counseling group. Conclusion: The use of training devices and smartphone applications in addition to traditional verbal counseling for teaching asthmatic adults and children the correct inhalation technique steps using pMDI resulted in a significant improvement in pulmonary function and a significant reduction in the number of inhalation technique mistakes, compared to traditional verbal counseling alone.