Miracle-dz/UniFAR-FTUs huggingface dataset:
Forecasting Model of Silicon Content in Molten Iron Using Wavelet Decomposition and Artificial Neural Networks

Silicon content forecasting models have been requested by the operational team to anticipate necessary actions during the blast furnace operation when producing molten iron, to control the quality of the product and reduce costs. This paper proposed a new algorithm to perform the silicon content time series up to 8 h ahead, immediately after the molten iron chemical analysis is delivered by the laboratory. Due to the delay of the laboratory when delivering the silicon content measurement, the proposed algorithm considers a minimum useful forecasting horizon of 3 h ahead. In a first step, it decomposes the silicon content time series into different subseries using the Maximal Overlap Discrete Wavelet Packet Transform (MODWPT). Next, all subseries forecasts were determined through Nonlinear Autoregressive (NAR) networks, and finally, these forecasts were summed to furnish the long-term forecast of silicon content. Using data from a real industry, we showed that the prediction error was within an acceptable range according to the blast furnace technical team.
Method of ensuring the survivability of highly mobile computer networks

The article discusses the features of the functioning of mobile computer networks based on small-sized aircraft (highly mobile computer networks). It is shown that such networks, in contrast to stationary or low-mobile ones, have a low level of survivability in case of local damage to their nodes. The purpose of the article is to develop a method for ensuring the survivability of highly mobile computer networks under conditions of destructive external influences, which leads to local destruction of network nodes or links between them, using the method of assessing survivability at all stages of network functioning, by changing the main function to implement all available strategies for the functioning of the network when determining the critical values of the integrity of the network and its ability to perform at least one of the available functions. The results obtained allow: to continue the development of theoretical research in the development of strategies for managing highly mobile computer networks in extreme situations; to develop an applied solution to ensure the survivability of highly mobile computer networks by building multifunctional or redundant structures, increasing the value of their redundancy. The studies allow us to conclude that the proposed method can be used at the design stages of highly mobile computer networks, characterized by increased survivability and capable of functioning in conditions of multiple local damages without catastrophic destructive consequences for the network structure.
Network Modelling and Visualisation Analysis of the Undergraduate Dental Curriculum System in China

Objectives: This study aims to present the characteristics of the undergraduate dental curriculum system using network modelling and visualisation analysis based on complex network theory, thus providing a theoretical foundation for the course development and curriculum reform. Methods: The correlation coefficient was used to quantify the intensity of the correlation between courses, and a visualisation complex network of the dental curriculum was built to explore the curriculum pattern from a dynamic perspective. Further, the statistical measurements of curriculum network were adopted to express the most relevant topological features. Subsequently, the minimum spanning tree and parallel coordinates plot were drawn to explore the curriculum community structure, quantify the key courses, and present different courses in time and space relationships. Results: The correlation analysis results show that the courses are closely related to each other. The main courses focus on pathology, pathophysiology, oral anatomy and physiology, closely connecting almost all medicine-related courses. The whole course network has an average degree value of 41.53, and a clustering coefficient of 0.78, indicating an obvious small-world characteristic. From the perspective of curriculum attributes, the number of public and theoretical courses was more than that of skills and practical courses. Moreover, the academic performance of skills and practical courses was lower than that of public and theoretical courses. Conclusion: The undergraduate dental courses have a progressive structure from basic professional knowledge to professional skills, which is reasonable for the dental education in China. However, some efforts towards curriculum reform based on this study are needed.
Investigation of Flow Pattern and Void Fraction of Air and Low Surface Tension Liquid in A 30° Inclined Small Pipe

Two-phase flow in the mini pipe is applied in wide fields. The most common of two-phase flow is a couple of gas and liquid. The essential properties of the liquid are density, viscosity, and surface tension. There are many variations of the flow direction, horizontal, incline, and vertical, in terms of orientation. The two-phase investigation of flow pattern and void fraction of air and low surface tension liquid in a 30° inclined small pipe has been carried out. Dry air was used as a gas phase, while the liquid was the mixture solution of distilled water and 3% (by volume) of butanol. Butanol addition aimed to decrease the surface tension, which became 42.9 millinewton/meter, instead of 71 mN/m when using distilled water. The test section was a 130 mm length, 1.6 mm inner diameter circular glass pipe. The rig used was equipped with the air compressor, pressure tank, high-speed camera, liquid flow meter, and gas flow meter. The liquid was fed to the test section by the pressurized tank, instead of directly pumped, to avoid pulsation. Ranges of gas and liquid superficial velocities were 0.025 – 66.3 m/s and 0.033 – 4,935 m/s, respectively. Flow patterns were obtained from the captured high-speed video. Meanwhile, the void fractions were acquired by image processing of the video. As a result, five distinctive flow patterns were observed: plug, slug-annular, churn, bubbly, and annular. The separated flow was absent. The change of the liquid surface tension affected the shifting of some transition boundary lines in the flow pattern map. The transition line between slug-annular and annular against churn flow was shifted to the lower side or toward lower JL when the liquid surface tension decreased. In short, the churn flow was easier to be formed when the liquid surface tension was lower.
The Human Capital for Value Creation and Social Impact: The Interpretation of the IR’s HC Definition

The paper aimed at assessing and identifying in a comparative way the potentiality and suitability of the Integrated Reporting (IR)’s definition of human capital (HC) within a selection of companies and social cooperatives. Employing in-depth interviews, the qualitative study analyzed the points of view of a selection of human resources managers to firstly check and test the connection between human capital, value creation, and social impact. The contribution of human capital to value creation is not easily recognized, especially by smaller-sized companies. The results suggested that the HC definition of the IR in the for-profit sector seems to be more applicable to the top management than to the whole workforce, while it appears as “fitting” for the managers of social cooperatives because of its explicit focus on ethical values, loyalty, and motivation. This allowed opening possible channels of dialogue between the profit and not-for-profit sectors. The paper proposed practical recommendations to operationalize the IR’s HC definition.
A New Way to Play Hockey in Canada

Youth sport provides the opportunity for children to develop skills, motivation, and interests towards an active lifestyle. In Canada, more than 75% of young people (6-12 years old) are engaged in organized sport; more specifically, over 300 000 children participate in organized hockey. Hockey Canada recently decided to propose a new way to introduce young people to hockey by implementing the half-ice game play model for novice players (7-8 years old). Based on other similar contexts, changes in the culture of a sport tend to cause a divergence in public opinion, which makes them controversial, thus making implementation more difficult at the grassroots level. This paper studies the parents and coaches of young hockey players by measuring their beliefs regarding the half-ice game play model for novice hockey, in the preceding year to official implementation. More specifically, the objective is threefold: 1) to describe and verify parents’ and coaches’ beliefs regarding the half-ice game play model, 2) to examine their preferences regarding the format of play they believe is best for their children (or players), and 3) to verify if their beliefs differ based on their province or association. The sample consisted of 6,892 participants (81% parents, 19% coaches) from across Canada (8 provinces/regions). Questionnaires measuring socio-demographic factors, beliefs, and preferences regarding the play model were completed and group comparisons were conducted. Results indicate that mothers’ beliefs differ significantly from those of fathers and coaches. The second part of the analysis also reveals important differences, in terms of territorial predispositions towards the preferred format for novice ice hockey. To facilitate implementation of a new ice hockey program, the results of this study suggest there are crucial aspects to consider with respect to the education of parents and coaches. Further research perspectives based on a long-term approach are also discussed.
Humanoid adaptive locomotion control through a bioinspired CPG-based controller

Abstract To achieve adaptive gait planning of humanoid robots, a hierarchical central pattern generator (H-CPG) model with a basic rhythmic signal generation layer and a pattern formation layer is proposed to modulate the center of mass (CoM) and the online foot trajectory. The entrainment property of the CPG is exploited for adaptive walking in the absence of a priori knowledge of walking conditions, and the sensory feedback is applied to modulate the generated trajectories online to improve walking adaptability and stability. The developed control strategy is verified using a humanoid robot on sloped terrain and shows good performance.
Open Innovation in Healthcare Ecosystem – a systematic review

Background: Several countries are facing significant troubles of health services, particularly rising prices. Innovative technologies and services are expected to help boost medical quality and cut costs. In this sense, there is a lack of innovative work in spite of a growing interest in open innovation and approaches that advocate for expanded cooperation among various actors in healthcare. Objective: This paper describes the findings of a study concerning the commitment of the healthcare sector to open innovation. Materials and methods: The search for literature focused on English-language papers to 12 January 2020. Based on the indicated criteria for inclusion, 29 articles were included. Results: Results show that most experiments concentrate on the areas of pharmaceutical research (drug discovery) and health informatics (health information systems and infrastructures) that were brought out as concepts or applied as pilot and prototype. Conclusions: The participation of the healthcare sector limited in open innovation, and more work is required with an emphasis how to get open innovation.
Stratification At The Health District Level And Targeting of Malaria Control Interventions In Mali

IntroductionMalaria has been the leading cause of morbidity and mortality for several decades in Mali, with an increase from 2017 to 2020 (2,884,837 confirmed cases and 1,454 deaths). On the recommendation of the World Health Organization (WHO) and in the interests of efficient use of resources, Mali has begun a process of stratifying the health districts to target malaria control strategies.MethodMalaria, entomological and environmental data were collected through the local health information system (LHIS), the Demographic and Health Survey (DHS 2018), research institutions and MALI-METEO services. The WHO has recommended stratification at the district level consisted of assigning each district to one of 4 classes according to criteria based on incidence adjusted for attendance rate. Variables associated with monthly malaria incidence at the district level were identified using a general additive non-linear regression model.ResultsFrom 2017 to 2019, the median incidence across 75 health districts of Mali was 129.34 cases per 1,000 person-year (IQR=86.48). The results showed different periods of high malaria transmission in health districts level and durations varying from 2 to 6 months, showing a double peak for some health districts, which were located in the flooded areas. environmental variables such as rainfall, vegetation index (NDVI), maximum temperature and relative humidity were significantly associated at malaria incidence with a lag of around one month. A strata defines a geographical area with similar epidemiological, environmental and socio-economic factors. Stratification resulted in 12 health districts of very low transmission, 19 low transmission, 20 moderate transmission and 24 in high transmission areas. The number of rounds of season malaria chemoprevention will be based on the number of months in the high transmission period.ConclusionThis first stratification in Mali will allow targeting malaria control strategies. This approach will be dynamic and revised yearly in order to integrate information from the national epidemiological surveillance.
Fuzzy-Based Application Model and Profile Matching for Recommendation Suitability of Type 2 Diabetic

Diabetes Mellitus (DM) is a metabolic disease characterized by hyperglycemia due to insulin secretion abnormalities and a global health threat. DM has several types, namely type 1, 2, gestational, and other types. Type 2 diabetes patients have the largest number in the world. DM therapy can be done in 2 (two) ways: improving lifestyle and administering drugs. The problems and risks in recommending drugs are essential in the patient's healing process because they are likely to take medicine for life. Approximately 260,000 patients with type 2 diabetes experienced medication errors in 2017. The doctor's mistake in recommending drugs causes a long healing process and costs more. Recommending drugs requires pharmacological knowledge, and not all hospitals have pharmacologists. Several researchers have researched recommendations for antidiabetic drugs, but no studies have yet been found that discuss recommendations for combination antidiabetic drugs for type two to determine dosage and frequency. The number of medications used is 6 to 7, with many parameters 5 to 8. The latest endocrinology guidelines for 2020 state that in recommending antidiabetic drugs, not only 6 to 7 participants, but still need to maintain other aspects. Therefore, this study aims to build an expert system model with a new approach in recommending antidiabetic drugs with more complete parameters and recommend dosage and frequency. The model developed uses the Fuzzy Profile Matching method. Fuzzy is used to calculate the suitability between the patient's condition and the type of antidiabetic drug. Profile Matching is used to calculate the core factor and secondary factor to obtain each drug's total value. The dose was calculated using the FIS Tsukamoto for inputting low dosage, and high dosage calculated the weighted average value. Determination of frequency using the IF-Then function. Model evaluation is done by comparing recommendation data from doctors. The results of the evaluation of the model obtained an accuracy of 90%. This system will reduce medical personnel errors in recommending antidiabetic drugs that can positively impact patients' time, the healing process, and costs. This study provides knowledge that antidiabetes drugs' determination requires many parameters, while other studies used only 4 to 8. This study also provides an overview of the dosages of drugs that drug companies can produce. Usually, the company only makes low and high dosage. This study shows that creating multiple drug dosage is more efficient for patients.
Design of a Surface Plasmon Resonance Temperature Sensor with Multi-Wavebands Based on Conjoined-Tubular Anti-Resonance Fiber

In this work, a surface plasmon resonance (SPR) temperature sensor based on a con-joined-tubular anti-resonance optical fiber (CTF) was theoretically designed and analyzed using the finite element method. The CTF cladding was composed of eight pairs of conjoined tubes, and one or two holes of the tubes were selectively coated with gold to generate the SPR effect. Alcohol was injected into the core of the CTF to work as the sensing medium using vapor deposition. The proposed sensing structure exhibited excellent birefringence and produced more than six resonant peaks in different wavebands of the X and Y polarization. The positions of those resonant peaks were sensitive to temperature change, and the simulated sensitivity was about 3.2–3.6 nm/°C. The multiple working wavebands of the proposed sensing structure could be used for self-verification. Moreover, the influence of structural parameters on sensing performance was analyzed in detail. Possessing features of high sensitivity, good birefringence, multiple measuring wavebands, and self-verification, the proposed CTF-based SPR sensor has great potential in practical applications such as biological research and chemical sensing.
Assessment of the Impacts of Spatial Water Resource Variability on Energy Planning in the Ganges River Basin under Climate Change Scenarios

Availability of water in the Ganges River basin has been recognized as a critical regional issue with a significant impact on drinking water supply, irrigation, as well as on industrial development, and ecosystem services in vast areas of South Asia. In addition, water availability is also strongly linked to energy security in the region. Hence, quantification of spatial availability of water resources is necessary to bolster reliable evaluation of the sustainability of future thermal power plants in the Ganges River basin. This study focuses on the risks facing existing and planned power plants regarding water availability, applying climate change scenarios at the sub-basin and district level up to 2050. For this purpose, this study develops an integrated assessment approach to quantify the water-energy nexus in four selected sub-basins of the Ganges, namely, Chambal, Damodar, Gandak, and Yamuna. The results of simulations using Soil and Water Assessment Tools (SWAT) showed that future water availability will increase significantly in the Chambal, Damodar, and Gandak sub-basins during the wet season, and will negligibly increase in the dry season, except for the Yamuna sub-basin, which is likely to experience a decrease in available water in both wet and dry seasons under the Representative Concentration Pathway (RCP) 8.5 scenario. Changes in the water supply-demand ratio, due to climate change, indicated that water-related risks for future power plants would reduce in the Chambal and Damodar sub-basins, as there would be sufficient water in the future. For 19 out of 23 districts in the Chambal sub-basin, climate change will have a moderate-positive to high-positive impact on reducing the water risk for power plants by 2050. In contrast, existing and future power plants in the Yamuna and Gandak sub-basins will face increasing water risks. The proposed new thermal power installations, particularly in the Gandak sub-basin, are likely to face serious water shortages, which will adversely affect the stability of their operations. These results will stimulate and guide future research work to optimize the water-energy nexus, and will inform development and planning organizations, energy planning organizations, as well as investors, concerning the spatial distribution of water risks for future power plants so that more accurate decisions can be made on the location of future power plants.
Exploring Undergraduates’ Satisfaction with Library Resources and Services: A Case Study of the Science Library, University of Peradeniya, Sri Lanka

This study investigated the level of undergraduates’ satisfaction and their perceptions towards library resources and services provided by the Science Library, University of Peradeniya. The survey research method was adopted to achieve the above objectives. A questionnaire was administered to 442 undergraduates of the Faculty of Science. 371 duly filled questionnaires were returned, were then analyzed. The findings revealed that more than 60% of the undergraduates visited the library daily and weekly, while more than 80% of them visited the library for multiple purposes. Regarding the available resources, the majority of the undergraduates were satisfied with the library book collection, periodicals and available magazines. Yet, only 39% and 32% of students reported that they were satisfied with e-resources and audiovisual materials available in the library respectively. Considering the library services, the majority of respondents were satisfied with lending, reference, referral and photocopying services. However, 11% of them were not satisfied, where as 13% of the students were not even aware of online services provided by the library. Further, the findings demonstrated that limited number of computers, unavailability of Wi-Fi facilities, unawareness of the library website, difficulties of accessing the Internet and searching research articles were the main reasons for students’ dissatisfaction. However, the majority of the undergraduates praised the library staff for offering an impressive service. The results proved that undergraduates have positive perceptions towards the library and its services. Based on the findings, some suggestions were made to increase user satisfaction and to enhance the library resources and service quality.
An Automated Approach for Extracting Forest Inventory Data from Individual Trees Using a Handheld Mobile Laser Scanner

Many dendrometric parameters have been estimated by light detection and ranging (LiDAR) technology over the last two decades. Handheld mobile laser scanning (HMLS), in particular, has come into prominence as a cost-effective data collection method for forest inventories. However, most pilot studies were performed in domesticated landscapes, where the environmental settings were far from those presented by (near)natural forest ecosystems. Besides, these studies consisted of numerous data processing steps, which were challenging when employed by manual means. Here we present an automated approach for deriving key inventory data using the HMLS method in natural forest areas. To this end, many algorithms (e.g., cylinder/circle/ellipse fitting) and machine learning models (e.g., random forest classifier) were used in the data processing stage for estimation of the tree diameter at breast height (DBH) and the number of trees. The estimates were then compared against the reference data obtained by field measurements from six forest sample plots. The results showed that correlations between the estimated and reference DBHs were very strong at the plot level (r=0.83–0.99, p<0.05). The average RMSE for tree DBHs was 1.8 cm at the forest landscape level. As for tree detection, 92.5% of 292 trunks were correctly classified on point cloud data. In general, estimation accuracy was sufficient for operational forest inventory needs. However, they could markedly decrease in »hard plots« located at rocky terrains with dense undergrowth and irregular trunks. We concluded that area-based forest inventories might hugely benefit from the HMLS method, particularly in »easy plots«. By improving the algorithmic performances, the accuracy levels can be further increased by future research.