Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Evolutionary Multi-Objective Optimization Algorithm for Helping Multi-Criterion Decision Makers

ABSTRACT Obtaining a specific region from the efficient front for multi-objective and practical optimization problems helps decision-makers. Reference point approaches are suggested to reach the region of interest. Many evolutionary algorithms integrated with a reference point idea to obtain apart from the efficient front solutions close to the reference solution. This paper integrated a penalty boundary intersection (PBI) with the non-dominated sorting genetic algorithm (NSGA-II) to reach the efficient front close to the reference point. The proposed approach allows theoretically convergent solutions to be found. Also, using the advantage of PBI, our algorithm is able to reach a specific part for a set multi and many-objective optimization problems effectively. The proposed algorithm compared with other evolutionary algorithms, such as the original reference-based NSGA-II (R-NSGA-II), r-NSGA-II, and g-NSGA-II. The R-metric values show that the proposed algorithm outperforms the compared algorithms. Using the proposed algorithm for solving the multi-objective engineering design problem helps find solutions according to the decision-makers interest.
Boundary simulation – a hierarchical approach for multiple categories

Geological modelling is a crucial step in mineral resource evaluation. The traditional approach to modelling the volumetric limits, explicit modelling, presents a series of limitations and disadvantages which makes it costly to assess the uncertainty in relation to the location of the limits between different domains in the mineral deposit. In many cases, the geological model can be a source of crucial uncertainty, for this reason, the uncertainty associated with the geological model must be assessed. This paper proposes a method for assessing geological model uncertainty by simulating the contacts between different domains in a mineral deposit in a hierarchical manner using signed distances. The proposed method was demonstrated in a case study conducted on a porphyry copper deposit. Models generated by the proposed method do not show much noise, as this method leads to continuous contacts between domains while the volume variation and contacts characteristics can be controlled by the parameters. Results are compared to sequential indicator simulation, a traditionally used technique to model geobodies and assess its uncertainty.
Archaeological, Alethurgical, and Dispositif Analysis: Discourse Studies on Higher Education in Poland from a Post-Foucauldian Perspective

At the present stage of the reception of Foucault’s ideas, various theoretical and methodological trends coexist, within which the concepts of Michel Foucault are used fruitfully in empirical research. One of them is discourse studies understood as an inter- and transdisciplinary research area. This article distinguishes and describes three post-Foucauldian strategies of discourse analysis, the combined use of which in one research project is a proposal to integrate concepts scattered in Foucault’s various works. The strategies distinguished (archaeological, alethurgical, and dispositif) are characterized by the different analytical categories, understanding of discourse, and its relations with knowledge and power. The article presents selected results of the complementary use of concepts such as knowledge formation, alethurgy, confession, or the dispositif in the empirical research on the reform of higher education in Poland.
Managing a World Heritage Site in Malawi: do residents’ sentiments matter?

ABSTRACT Residents are an integral stakeholder in any tourism destination and understanding their sentiments on any tourism activity within their locality is very critical. Although local people are the most affected by tourism development at such places, there is a deficit of research on the local communities’ perceptions on the impacts of and changes to their communities due to World Heritage Site (WHS) operations. Thus, the study sought to assess residents’ sentiments towards cultural heritage tourism at Chongoni Rock Art Heritage sites. Data were collected from 35 respondents who were purposively selected from three villages surrounding the WHS. Data were thematically analysed and the main theme that emerged was a lack of community involvement in tourism activities at the sites which has destroyed heritage assets. The findings contribute to the extant literature on local communities’ participation and perceptions of tourism development at WHS. The study recommends residents’ participation as one way of empowering the local community and enhancing economic benefits from tourism.
Improvement of Concrete Properties using Granulated Blast Furnace Slag Sand

A high volume of ground granulated blast furnace slag (GGBS) or granulated blast furnace slag (BFS) can enhance the resistance of concrete to freezing and thawing without the use of air-entraining (AE) agents. Furthermore, it can also enhance the resistance of concrete to chloride ion penetration and sulfuric acid attack, although the mechanism of improvement differs. In particular, BFS can reduce time-dependent strains, such as drying shrinkage strain and creep strain. The use of granulated blast furnace slag, either GGBS or BFS, promotes the durability of concrete structures by improving the mechanical properties of cementitious materials. Some of the concrete properties that are improved by the incorporation of BFS are presented in this paper. The detailed improvement mechanism of BFS has not yet been clarified. However, it is clear that it depends on the chemical reactions involving BFS and thus a critical time is required for BFS to hydrate in order to improve concrete properties. It takes four weeks to achieve high resistance to freezing and thawing by using BFS without the addition of an AE agent; use of a thickening agent can further shorten this curing period to one week. This paper is an English translation from a previous work by the authors [Ayano et al., (2014). “Resistance to freezing and thawing attack of concrete with blast furnace slag fine aggregate. ” Journal of Japan Society of Civil Engineers, Ser. E2 (Materials and Concrete Structures), 70(4), 417-427 (in Japanese)] and [Jariyathitipong et al., (2013). “Improvement of resistance to sulfuric acid attack of concrete by use of blast furnace slag sand. ” Journal of Japan Society of Civil Engineers, Ser. E2 (Materials and Concrete Structures), 69(4), 337-347 (in Japanese)].
Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning

Industry standards pertaining to Human-Robot Collaboration (HRC) impose strict safety requirements to protect human operators from danger. When a robot is equipped with dangerous tools, moves at a high speed or carries heavy loads, the current safety legislation requires the continuous on-line monitoring of the robot’s speed and a suitable separation distance from human workers. The present paper proposes to make a virtue out of necessity by extending the scope of on-line monitoring to predicting failures and safe stops. This has been done by implementing a platform, based on open access tools and technologies, to monitor the parameters of a robot during the execution of collaborative tasks. An automatic machine learning (ML) tool on the edge of the network can help to perform the on-line predictions of possible outages of collaborative robots, especially as a consequence of human-robot interactions. By exploiting the on-line monitoring system, it is possible to increase the reliability of collaborative work, by eliminating any unplanned downtimes during execution of the tasks, by maximising trust in safe interactions and by increasing the robot’s lifetime. The proposed framework demonstrates a data management technique in industrial robots considered as a physical cyber-system. Using an assembly case study, the parameters of a robot have been collected and fed to an automatic ML model in order to identify the most significant reliability factors and to predict the necessity of safe stops of the robot. Moreover, the data acquired from the case study have been used to monitor the manipulator’ joints; to predict cobot autonomy and to provide predictive maintenance notifications and alerts to the end-users and vendors.
Evaluation of nutritional quality and mineral composition of fermented milk (nono) sold in Kano, north-western Nigeria

Nono is produced traditionally by spontaneous fermentation in homes, especially in villages where the safety of the product is not considered and due to the increasing environmental pollution, toxic elements may find their way into the food chain which may create significant health concerns. This study therefore, was conducted to evaluate the nutritional quality and mineral composition of nono milk sold in Kano, North-Western Nigeria using standard procedures. The physical and nutritional characteristics including protein, carbohydrate, ash, moisture, fat and total solids were determined using the method of the Association of Official Analytical Chemists while the elemental content was determined using flame atomic absorption spectroscopy analytic method. The mean protein content ranged from 2.90 to 7.0%, carbohydrate 4.60 - 8.20%, ash content 0.50 - 0.85%, moisture content 79.82 - 87.0%, fat content 2.90 - 4.66% and total solid 8.60 - 12.43%. The values of protein content and that of carbohydrate obtained in this study exceeded the FAO standard. The mean sodium content ranged from 2.22 - 3.28 mh/l, potassium (0.86 - 2.65mg/l), magnesium (3.95 0 6.30 mg/l), calcium (39.85 - 59.07 mg/l), iron (1.23 - 4.53 mg/l), copper (0.61 0 1.28mg/l), zinc (0.43 - 0.64 mg/l), cadmium (0.00 - 0.03 mg/l), chromium (0.78 - 1.58 mg/l), and lead (0.00 - 1.07 mg/l). The value of lead observed in Dawakin tofa is significantly higher than other markets and this constitutes serious risk to public health. It is recommended that studies on preservation methods should be carried out as it affects nono production.
CRISPR/Cas9 uses

Nora MIMOUNE*#, (Corresponding author: nora.mimoune@gmail.com), National High School of Veterinary Medicine, Algiers, Algeria; National Institute of Veterinary Sciences, Laboratory of Biotechnology Related to Animal Reproduction (LBRA), University Saad Dahleb, Blida, Algeria; Oumayma BENADJEL#,, Ratiba BAAZIZI, Djamel KELEF, National Institute of Veterinary Sciences, Laboratory of Biotechnology Related to Animal Reproduction (LBRA), University Saad Dahleb, Blida, Algeria; Rachid KAIDI, Laboratory of Biotechnology Related to Animal Reproduction (LBRA), University Saad Dahleb, Blida, Algeria *These authors have contributed equally to this work. Abstract
Smart Home Battery for the Multi-Objective Power Scheduling Problem in a Smart Home Using Grey Wolf Optimizer

The power scheduling problem in a smart home (PSPSH) refers to the timely scheduling operations of smart home appliances under a set of restrictions and a dynamic pricing scheme(s) produced by a power supplier company (PSC). The primary objectives of PSPSH are: (I) minimizing the cost of the power consumed by home appliances, which refers to electricity bills, (II) balance the power consumed during a time horizon, particularly at peak periods, which is known as the peak-to-average ratio, and (III) maximizing the satisfaction level of users. Several approaches have been proposed to address PSPSH optimally, including optimization and non-optimization based approaches. However, the set of restrictions inhibit the approach used to obtain the optimal solutions. In this paper, a new formulation for smart home battery (SHB) is proposed for PSPSH that reduces the effect of restrictions in obtaining the optimal/near-optimal solutions. SHB can enhance the scheduling of smart home appliances by storing power at unsuitable periods and use the stored power at suitable periods for PSPSH objectives. PSPSH is formulated as a multi-objective optimization problem to achieve all objectives simultaneously. A robust swarm-based optimization algorithm inspired by the grey wolf lifestyle called grey wolf optimizer (GWO) is adapted to address PSPSH. GWO has powerful operations managed by its dynamic parameters that maintain exploration and exploitation behavior in search space. Seven scenarios of power consumption and dynamic pricing schemes are considered in the simulation results to evaluate the proposed multi-objective PSPSH using SHB (BMO-PSPSH) approach. The proposed BMO-PSPSH approach’s performance is compared with that of other 17 state-of-the-art algorithms using their recommended datasets and four algorithms using the proposed datasets. The proposed BMO-PSPSH approach exhibits and yields better performance than the other compared algorithms in almost all scenarios.
Combination Therapy Revives Hope for Patients with Diabetic Foot Ulcer: A Case Report

BackgroundDiabetic foot ulcers, as one of the most debilitating complications of diabetes, can lead to amputation. Treatment and management of diabetic foot ulcers are among the most critical challenges for the patients and their families. Case presentationThe present case report is of a 63-year-old man with a 5-year history of uncontrolled type 2 diabetes who has had diabetic foot ulcers for the past three years on three sites of the left external ankle in the form of two deep circular ulcers with sizes of 6×4 cm and 6×8 cm, the sole as a superficial ulcer with a size of 6×3 cm, and the left heel as a deep skin groove. Moreover, the left hallux was completely gangrenous. The patient's ulcers were infected with Staphylococcus aureus and multidrug-resistant Pseudomonas aeruginosa. Despite antibiotic therapy and routine dressing changes, the patient showed no improvement during the hospital stay. Accordingly, the patient was transferred to our service after consulting with the wound management team. Diabetic foot ulcers were treated and managed using a combination of maggot therapy, the Negative Pressure Wound Therapy (NPWT), and silver foam dressing. After three months and ten days, the patient's ulcers completely healed, and he was discharged from our service with the excellent and stable condition. Conclusions﻿Based on the present case report study's clinical results, wound-care teams can use the combination therapy applied in this study to treat refractory diabetic foot ulcers.
Intelligent personalised exercise recommendation: A weighted knowledge graph‐based approach

As a critical function for intelligent tutoring system services, personalised exercise recommendation plays an important role in boosting the study performance of students. However, recent studies on personalised exercise recommendations have only considered the ability of a student during recommendation and have failed to include the essential relationships between knowledge points, which provide a suitable learning sequence of these knowledge points during a study procedure. In this study, we propose an intelligent exercise recommendation method (weighted knowledge graph‐based recommendation [WKG‐R]) for students, based on weighted knowledge graphs, wherein each node represents a knowledge point weighted by the ability of a student and an arrowed edge between two knowledge points indicates their prerequisite relationship. The novelty of WKG‐R can be summarised as follows: (1) It makes a leading attempt to quantify the ability of a student based on various testing behaviours and (2) it attempts to employ the ability of a student and the prerequisite dependencies between knowledge points for enhancing the effectiveness of personalised exercise recommendation. A real classroom teaching practice was conducted to evaluate the effectiveness of the proposed WKG‐R method. The experimental results demonstrated the distinct advantage of WKG‐R in improving the testing scores of students as compared with contemporary solutions. The average score improvement ratio of students for WKG‐R is up to 33%, whereas for the state‐of‐the‐art solution, it is only 22%. The questionnaires collected from the students also reflected a higher level of satisfaction towards WKG‐R than with the contemporary solutions.
Proposal for a Fuzzy Model to Assess Cost Overrun in Healthcare Due to Delays in Treatment

Apart from the effects of treating those infected with COVID-19, the pandemic has also affected treatment for other diseases, which has been either interrupted or canceled. The aim of this paper is to provide a financial model for obtaining the cost overrun resulting from the worsening of illnesses and deaths for each of the causes considered. To achieve this, first deaths have been classified into causes of death and for each of these causes, an estimation has been made of the worsening condition of patients due to delay in treatment. Through these data, a fuzzy relation between deaths and the worsening condition of patients can be obtained. Next, the expertise process has been used to estimate cost overrun in relation to patients’ pathologies. The experts’ opinions have been aggregated using ordered weighted average (OWA). Lastly, using fuzzy logic again, a correction coefficient has been determined, which optimizes the future implementation of the proposed model without the need for a new estimation of inputs. The paper concludes with a numerical example for a better comprehension of the proposed theoretical model. Ultimately, it provides the scientific community in general and in particular managers of public administration entities with a novel tool for improving the efficiency of the healthcare system.
Probing Baryogenesis using Neutron-Anti-Neutron Oscillation

Neutron-anti-neutron (=− =̄) oscillation is a baryon number violating process that requires physics beyond the Standard model. Future experiments at ESS and DUNE aim to either discover (= − =̄) oscillation or to put more stringent constraints on the oscillation time. We study the impact of such a discovery on different baryogenesis scenarios using an effective field theory framework for (= − =̄) oscillation. We also study the implications of observing the mediators at the LHC and the possibility of falsifying some of the baryogenesis scenarios in the context of some simplified UV complete scenarios.
BIOLOGICAL STUDIES IN THE VICINITY OF

and uptake rates were determined in the vicinity of a shallow-sea tidal mixing front in the western Irish Sea. Urea concentrations, while patchy, were similar throughout the year and showed no significant patterns of distribution and no relation to stratification of the water column. Urea uptake rates, on the other land, showed a consistent and strong relationship to stratification, both vertically arnd horizontally, fastest rates being found in the less dense water on the stratified side of the front and above the pycnocline. Large differences between waters above and below the pycnocline were found during months of strong stratification. Similar differences occurred between the stratified and mixed surface waters on each side of the front. From relatively low urea uptake rates in March, when stratification was weak, extremely high rates were observed inJune and thereafter decreased attaining another minimum at the end of September when stratification was weakening. Urea uptake indices (uptake per unit of chlorophyll a) were also highest in the surface stratified waters and followed a similar vertical, horizontal and seasonal distribution pattern as that of urea uptake rates. The seemingly unchanging urea concentrations throughout the year and its extremely fast uptake by micro-organisms indicate a rapid flux of this nitrogenous compound in the surface of the stratified waters. The possible routes of urea regeneration are discussed. Budget calculation indicate that urea was an important source of nitrogen for phytoplankton in the surface stratified waters when oxidized forms of nitrogen such as nitrate were depleted and that the rapid flux of reduced nitrogen in the form of urea may be a major factor in sustaining high productivity associated with the frontal system.
Global distribution and conservation of avian diet specialization

Ecologically specialist species are more prone to extinction than generalist species, yet the global distribution and conservation of ecological specialism is poorly understood. Here, we show that the global distribution of avian dietary specialization is roughly congruent with overall bird species richness for resident and breeding species, as well as for non‐breeding species. However, some areas harbour a higher number of diet specialist birds than expected given overall species richness (e.g. the Amazon, Gabon and Cameroon in Central Africa, extensive parts of Indonesia and some parts of northern Eurasia, Baltic cost and Mediterranean areas for resident and breeding birds, and tropical zone and south part of subtropical zone in South America for non‐breeding birds). These areas represent hotspots of avian specialization that need to carefully be considered in conservation strategies. We found that overall, 49.6% of resident and breeding species and 45.5% of non‐breeding diet specialist species are adequately represented by the global protected area system, but that this percentage is lower for the most threatened species. Policies that modify conservation planning approaches to include measures of specialization alongside other more traditional metrics of biodiversity could improve the protection of biodiversity in the face of rapidly accelerating anthropogenic threats.
A chip-sized piezoelectric receiver for low-frequency, near-field wireless power transfer: design, modeling and experimental validation

This work presents the design, modeling and characterization of a chip-sized piezoelectric receiver for low-frequency, near-field wireless power transmission. Utilizing a laser micro-machined titanium suspension, one NdFeB magnet, and two PZT-5A piezo-ceramic patches, the receiver operates at its torsion mode mechanical resonance. Two unimorph piezo-ceramic transducers are designed to maximize the power density of the receiver while maintaining a low mechanical resonant frequency for low-frequency electrodynamic wireless power transmission. An equivalent lumped-element circuit model is used to model the system performance. A prototype device is fabricated, assembled and tested, and the experimental results are compared with the system model. The 0.08 cm3 device generates a maximum of 360 μW average power at 1 cm distance from a transmitter coil operating at 724 Hz and below human head and torso exposure limits. This data corresponds to 4.2 mW cm−3 power density. Overall, this volume-efficient design offers a low-profile and compact footprint for potentially wirelessly charging wearable and bio-implantable devices.