Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Hydraulic Blockage at Culverts using Lab Scale Simulated Hydraulic Data

ABSTRACT Blockage of culverts causes reduction in hydraulic capacity and is one of the main contributors to trigger urban flooding. However, the highly non-linear nature of debris interaction during the flood and lack of blockage-related data from actual flooding events make conventional numerical modelling almost impossible. Literature investigating blockage phenomena reports blockage as a complex hydraulic process, which suggests exploring adaptive solutions using latest technologies. In this context, motivated by the success of data-driven algorithms, in this article, four data driven models (i.e., K-NN, ANN, SVR, 1D-CNN) are implemented to predict the hydraulic blockage at culverts. A new numerical Hydraulics-Lab Blockage Dataset (HBD) is established from a series of lab-scale hydraulic experiments. From the experimental investigations, the ANN model was reported as the best with a R 2 score of 0.95. A potential use-case of presented research for real-world application is also discussed to demonstrate the practical feasibility.
Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province

Most studies in the field of ecological restoration have only focused on repairing damaged land and have made no attempt to account for the impact of high-intensity land use on future landscape patterns. The purpose of this study was to propose a framework for evaluating the expected effects of ecological restoration based on land-use change and the ecological security pattern. Therefore, we integrated the PLUS model with the ecological security pattern and used Hefei City as a case study to conduct research. The results showed that from 2020 to 2030, land-use changes would occur primarily in the main urban area of Hefei and along the eastern shore of the Chaohu Lake watershed. Under the ecological protection scenario, arable land would be converted to construction land and woodland. Additionally, there would be an increase in ecological sources and pinch points in the area, and the number and area of the barriers would show a certain degree of reduction. The ecosystem quality, ecological integrity, and landscape connectivity of Hefei would be improved. This study offers a novel perspective for evaluating the expected effects of regional ecological restoration and provides an important reference for the dynamic formulation of multilevel ecological restoration policies.
A Systematic Mapping Study on Machine Learning Techniques Applied for Condition Monitoring and Predictive Maintenance in the Manufacturing Sector

Background: Today’s production facilities must be efficient in both manufacturing and maintenance. Efficiency enables the company to maintain the required output while reducing production effort or costs. With the increasing interest in process automation and the Internet of things since Industry 4.0 was introduced, such shop floors are growing in complexity. Every component of the production needs to be continuously monitored, which is the basis for predictive maintenance (PdM). To predict when maintenance is needed, the components’ conditions are monitored with the help of a condition monitoring (CM) system. However, this task is difficult for human employees, as the monitoring and analysis is very demanding. To overcome this, machine learning (ML) can be applied to ensure more efficient production. Methods: This paper aims to investigate the application of ML techniques for CM and PdM in the manufacturing sector. For this reason, a systematic mapping study (SMS) is conducted in order to structure and classify the current state of research and identify potential gaps for future investigation. Relevant literature was considered between January 2011 and May 2021. Results: Based on the guidelines for SMSs and previously defined research questions, existing publications are examined and a systematic overview of the current state of the research domain is provided. Conclusions: Techniques such as reinforcement learning and transfer learning are underrepresented, but increasingly attracting more attention. The findings of this study suggest that the most promising results belong to the applications of hybrid ML methods, where a set of methods are combined to build a more powerful model.
Intergenerational Connections: An online community engagement project

Young adults hold many stereotypes about aging and older adults that formal education cannot always address. Interaction and community engagement projects with older adults can challenge and dispel stereotypes young adults hold about older adults. This semester-long project is designed for undergraduate students in interpersonal and relational communication classes to engage in intergenerational dialogue to ease social isolation, interact across generations, and dispel ageist stereotypes through community engagement. Courses Communication across the Life Course, Family Communication, Interpersonal Communication, Intergenerational Communication, Relational Communication. Objectives The purpose of this semester-long project is for participants: (1) to engage in meaningful conversation and dialogue with older adults; (2) to build relationships with community partners; (3) to learn skills in interacting across generations; and (4) to reflect on their attitudes and attitude change toward older adults.
Interactive Augmented Reality Technology via Blended Instruction Lesson on Cloud

The study aims to study the processes of the interactive augmented reality technology via blended instruction lesson on cloud, to design the interactive augmented reality technology via blended instruction lesson on cloud, to develop the interactive augmented reality technology via blended instruction lesson on cloud and to study the results of the development of interactive augmented reality technology via blended instruction lesson on cloud. The study’s sample was selected using purposive sampling, i.e., 5 people from various higher education institutions and 30 people from undergraduate students in the first year of social sciences division in Pakse Teacher Training College, Lao PDR. The results showed the following: 1) the results of the quality assessment of developed blended instruction lesson on cloud had an overall very high level (mean = 4.51, SD = 0.57); 2) the results of the developed blended instruction lesson on cloud summarised that the results of the post-test achieved a score higher than the pre-test, which is statistically significant at 0.01; 3) the results of the assessment of the digital literacy of students after studying had a good level (mean = 40.73, SD = 2.18); and 4) the results of the student satisfaction to study with the developed blended instruction lesson on cloud were found to have a high level of satisfaction (mean = 4.31, SD = 0.55).
A new registration method with improved phase congruency for application to GPR images

ABSTRACT In this letter, we propose an edge detection algorithm and a framework of points matching for ground penetrating radar (GPR) images to achieve the B-Scan image registration of GPR. In our proposed algorithm, the robust edge feature information of GPR images is detected by the improved phase congruency model. Then, the feature points are detected by the GPR image’s edge feature in the curvature scale space. Finally, a novel similarity metric is defined for feature point registration. Experimental results show that compared to the classic registration method and the state-of-the-art feature points registration methods, the proposed method shows the best matching performance and robustness in GPR images.
The Associations between Childhood Experiences and Occupational Choice Capability, and the Mediation of Societal Gender Roles

Experiences in family, school, and social life during childhood are associated with gender roles and occupational choice capability. This study examines how competent individuals are in occupational choice capability and the relationships of childhood experiences and gender roles with their competencies in occupational choice capability. The research is composed of 805 individuals aged 18 and older, who reside in Turkey. In the research, we used the Personal Information Form, Childhood Experiences Scale, Gender Roles Attitude Scale, and The Scale of Occupational Choice Capability. The SPSS 25 program and PROCESS-Macro were used to analyze the variables. The relationship between the scales was investigated using Pearson correlation analysis and multiple regression analysis. According to the findings we obtained, individuals’ family and school life were positively correlated with their career choices, and family function sexism harmed their choice of profession. We also found gender roles had a mediating role in the relationship between school life and career choice.
MECH 461 Project Proposal for Winter 2013 Control of a Pneumatic Gantry Robot for Tracking Applications

INTRODUCTION In 2007 a pneumatic gantry robot was developed to enable studies in hybrid force/velocity control for contour tracking applications [1]. See Fig. 1. Since that time the robot has been modified and upgraded as it was used by a series of graduate students. The main axis was recently refurbished with a new pneumatic cylinder, as a decrease in performance was observed in the most recent study, which was attributed to uneven wear in the bearing surface and higher than normal friction [2]. Data acquisition and control is PC-based with a dSPACE/DSP as the data acquisition hardware/software and MATLAB/Simulinkas the control software. Proportional flow control values are used in combination with both rodless and rodded pneumatic cylinders.
Understanding the controllability of complex networks from the microcosmic to the macrocosmic

meta-structures,meta-structure-drivencontrol,minimumdominatingset Abstract From a microcosmic perspective, nodes as meta-structures ( or ‘ smallest units ’ ) for the constitution of a graph are of great importance for understanding complex network-based systems. In this paper, we develop a new framework, which ﬁ rst of all de ﬁ nes the meta-structures of a graph in different levels and tries to depict a graph from a low to a high level of abstraction. Further, based on this framework we study the meta-structure-driven control model and try to understand the controllability of complex networks from a microcosmic to a macrocosmic perspective. Finally, we analyze the impact of the community strength of networks on meta-structure-driven control. The results for arti ﬁ cial networks and real-world networks indicate that for meta-structure-driven control, the number of driver nodes is dependent on the networks ’ degree distribution, and the dependence weakens as the level of the meta-structures increases. In addition, the networks are easier to control as the community strength increases, while this monotonicity is not preserved as the level of the meta-structures increases. We also ﬁ nd that it is harder to control sparse and inhomogeneous networks as the level of the meta-structures
Effect of Carbon Nanofibers on Physical, Adhesion and Rheological Properties of Liquid Epoxidized Natural Rubber Modified Asphalt

This study aimed to evaluate the effects of carbon nanofibers (CNFs) on the performance of liquid epoxidized natural rubber (LENR)-modified asphalt. The physical, adhesion and rheological properties were determined by several tests such as penetration, elastic recovery, ring and ball softening point, Brookfield rotational viscometer, AFM and dynamic shear rheometer. LENR was used at concentrations of 3, 6, and 9%, while CNFs were used at contents of 0.3, 0.4, and 0.5% by weight of asphalt. Conventional test results showed that the increases in LENR and LENR/CNFs composite contents in binder leads to an increase in the hardness and consistency and a reduction in the temperature susceptibility of base asphalt. Adhesion results revealed that the addition of CNFs significantly increases the adhesion and bonding properties of base and rubberized binders. Rheological properties analysis exhibited that LENR improved the viscoelastic properties and permanent deformation resistance of asphalt at different temperatures and frequencies. On the other hand, it was found that the addition of CNFs significantly improves the stiffness, elasticity, and hardness of LENR-modified binders. The 6% LENR and 0.4% CNFs were found to be the optimum to enhance the physical, adhesion, and rheological properties of asphalt in this study. Thus, it can be stated that the addition of CNFs is promising to improve the performance of rubberized binders for high temperature applications.
Identity Processing Style and Meaning in Life among Emerging Adults: Mediational Role of Commitment

Building one’s own identity and finding meaning in life are important tasks for emerging adults. Although many agree that both are essential in terms of the well-being and proper functioning of an individual, there is little empirical data concerning the relationship between the way young people process information about themselves and the feeling that their life has a purpose and value. Therefore, the aim of this study was to explore how identity processing styles (normative, diffuse-avoidant and informational) and two dimensions of meaning of life (presence and the search for meaning) are related. It was also assumed that identity commitment could play a mediating role between those variables. 183 emerging adults who participated in the study completed Identity Style Inventory (ISI-5) and Meaning in Life Questionnaire. The cross-sectional study design was used. Using Structural Equation Modeling revealed that commitment mediated the relationship between two of three identity styles (diffuse-avoidant and informational) and presence, but not search for or meaning in life. Normative identity style also negatively predicted the search for meaning in life. It seems that commitment might play an important role in meaning-making process, and as such, should be strengthened and encouraged when working with individuals at this stage in life.
How visible is your supply chain? A model for supply chain visibility assessment

ABSTRACT Recent studies have highlighted the potential of supply chain visibility (SCV) to improve companies’ performance, support the decision-making process and increase the resilience and sustainability of supply chains (SC). However, the definition and the approaches to manage visibility are not consensual, especially when it comes to its assessment. This paper studies the influence that some characteristics of the information shared among SC partners have on SCV and provides a model that allows to assess the level of visibility. Focus group research was used to discuss the visibility assessment model with academic and practical experts and case studies were conducted to evaluate the implementation of the model in real contexts. The results support the applicability of the model in complex SCs and show that the visibility indices proposed can help managers to identify the SC partners where improvement actions are needed. This study contributes to literature and practice by means of a model to assess the visibility throughout the SC by considering different types and characteristics of the information shared.
A Case Study on Part Engineering Change Management from a Development and Production Perspective at a Major Automotive OEM

ii Dedication . iii Acknowledgement . iv List of Tables . vii List of Figures . ix Chapter One Motivation: Managing Change . 1 1.1 What is Part Engineering Change? 2 1.2 Research Questions . 9 1.3 Thesis Outline . 10 Chapter Two Literature Review. 12 2.1 Literature Review on Engineering Part Change Management . 12 2.2 Literature Review on Key Performance Indicators . 23 2.3 Gaps in Current Knowledge . 26 Chapter Three Case Study Research . 28 3.1 What are Case Studies? 28 3.2 Data Collection through Interviewing . 31 Chapter Four Research at Automotive OEM R&D Facility (Germany) . 35 4.1 Research Procedure . 36 Title Page.i
A risk based appraisal of maritime regulations in the shipping industry

The risk of the excessive and inadequate implementation of maritime regulations that have been introduced by the IMO has been widely recognised during recent decades. The world has been separated into various geographical regions according to the thoroughness by which states implement the maritime regulations. Nevertheless, some ship managers endeavour to find an opportunity to make their ships more profitable by reducing relevant costs, which would otherwise have been generated from maritime regulations, so resulting in less safe ships. States facing difficulties in establishing high levels of standards need to motivate private stakeholders to become more involved in the processes of regulation implementation. Evaluating the implementation performance of maritime regulations can improve the current regulatory process to the benefit of ship safety. In order to improve the implementation performance of a maritime regulation this research has adopted the Balanced Scorecard (BSC) in developing a performance management system for the shipping industry and its stakeholders. The framework consists of two groups of BSCs, one for the IMO and the other for a ship operator who is a representative example of a stakeholder. Each group contains a number of BSCs with their own `perspectives' and `measures'. The framework has been developed following an extensive literature review and one survey for a broader verification of the proposed BSCs from industrial experts. By using a variety of mathematic methods such as Analytic Hierarchy Process (AHP) and fuzzy set theory the framework from BSCs has been further developed by introducing two tools, one for the IMO and the other for a ship operator. The stakeholders can have an effective but simplified measurement system for a variety of applications. Both tools have been tested through case studies and a survey to demonstrate their applicability and efficiency. This research has revealed a number of very significant conclusions. The most important conclusion is that the states have the highest weight in the regulatory process. However, the contribution of all private stakeholders is also very important. Another conclusion is that the stakeholders will themselves become motivated to
Baicalin Alleviates Short-Term Lincomycin-Induced Intestinal and Liver Injury and Inflammation in Infant Mice

The adverse effects of short-term megadose of antibiotics exposure on the gastrointestinal and liver tissue reactions in young children have been reported. Antibiotic-induced intestinal and liver reactions are usually unpredictable and present a poorly understood pathogenesis. It is, therefore, necessary to develop strategies for reducing the adverse effects of antibiotics. Studies on the harm and rescue measures of antibiotics from the perspective of the gut–liver system are lacking. Here, we demonstrate that lincomycin exposure reduced body weight, disrupted the composition of gut microbiota and intestinal morphology, triggered immune-mediated injury and inflammation, caused liver dysfunction, and affected lipid metabolism. However, baicalin administration attenuated the lincomycin-induced changes. Transcriptome analysis showed that baicalin improved immunity in mice, as evidenced by the decreased levels of intestinal inflammatory cytokines and expression of genes that regulate Th1, Th2, and Th17 cell differentiation, and inhibited mucin type O-glycan biosynthesis pathways. In addition, baicalin improved liver function by upregulating the expression of genes involved in bile acid secretion and lipid degradation, and downregulating genes involved in lipid synthesis in lincomycin-treated mice. Bile acids can regulate intestinal immunity and strengthen hepatoenteric circulation. In addition, baicalin also improved anti-inflammatory bacteria abundance (Blautia and Coprobacillus) and reduced pathogenic bacteria abundance (Proteobacteria, Klebsiella, and Citrobacter) in lincomycin-treated mice. Thus, baicalin can ameliorate antibiotic-induced injury and its associated complications such as liver disease.
Teaching organic nomenclature for pharmacy students: Adapting a course to online mode during COVID-19

Introduction: Due to the confinement of the COVID-19 pandemic, educational centres have remained closed, transferring the teaching process to online mode, thus adapting infrastructure, methodologies, and the university community. Objectives: This work aims to evaluate the effectiveness of strategies in learning organic nomenclature and seek student opinions about committing fraud in organic chemistry course assessments in the online mode in the pharmaceutical career. Methods: The methodologies used allowed the students to understand and apply the organic nomenclature rules, using online collaborative guides and crosswords worked in synchronous classes, previous reading, and the collaborative asynchronous creation of informative files for the recognition of heterocyclic compounds and formative assessment. All assessments were applied in three-people groups in the synchronous classes. Finally, an anonymous survey was administered to know the student perception of the possibility of fraud during the course. Results: A substantial improvement (from 47.7% to 80.5%) was observed in the application of IUPAC rules for organic compounds. Of the students who responded to the anonymous survey, 81% reported that the methodology used decreased the opportunity to commit fraud during assessments.
The Optimal Management of Fistulizing Crohn’s Disease: Evidence beyond Randomized Clinical Trials

Fistulizing Crohn’s disease (FCD) remains the most challenging aspect of treating patients with CD. FCD can occur in up to 30% of patients with CD and may lead to significant disability and impaired quality of life. The optimal treatment strategies for FCD require a multidisciplinary approach, including a combined medical and surgical approach. The therapeutic options for FCD are limited due to sparse evidence from randomized clinical trials (RCTs). The current recommendations are mainly based on post hoc analysis from RCTs, real-world clinical studies and expert opinion. There is variation in everyday clinical practice amongst gastroenterologists and surgeons. The evidence for anti-tumor necrosis factor therapy is the strongest in the treatment of FCD. However, long-term fistula healing can be achieved in only 30–50% of patients. In recent years, emerging data in the advent of therapeutic modalities, including the use of new biologic agents, therapeutic drug monitoring, novel surgical methods and mesenchymal stem cell therapy, have been shown to improve outcomes in achieving fistula healing. This review summarizes the existing literature on current and emerging therapies to provide guidance beyond RCTs in managing FCD.