Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Transfer Reference Point-Oriented MOEA/D Involving Local Objective-Space Knowledge

The decomposition-based evolutionary algorithm (MOEA/D) has attained excellent performance in solving optimization problems involving multiple conflicting objectives. However, the Pareto-optimal front (POF) of many multiobjective optimization problems (MOPs) has irregular properties, which weakens the performance of MOEA/D. To address this issue, we devise a dynamic transfer reference point-oriented MOEA/D with local objective-space knowledge (DTR-MOEA/D). The design principle is based on three original and rigorous mechanisms. First, the individuals are projected onto a line segment (two-objective case) or a 3-D plane (three-objective case) after being normalized in the objective space. The line segment or the plane is divided into three different regions: 1) the central region; 2) the middle region; and 3) the edge region. Second, a dynamic transfer criterion of the reference point is developed based on the population density relationships in different regions. Third, a strategy of population diversity enhancement guided by local objective-space knowledge is adopted to improve the diversity of the population. Finally, the experimental results conducted on 16 benchmark MOPs and eight modified MOPs with irregular POF shapes verify that the proposed DTR-MOEA/D has attained a strong competitiveness compared with other representative algorithms.
Understanding Nesterov's Acceleration via Proximal Point Method

The proximal point method (PPM) is a fundamental method in optimization that is often used as a building block for designing optimization algorithms. In this work, we use the PPM method to provide conceptually simple derivations along with convergence analyses of diﬀerent versions of Nesterov’s accelerated gradient method (AGM). The key observation is that AGM is a simple approximation of PPM, which results in an elementary derivation of the update equations and stepsizes of AGM. This view also leads to a transparent and conceptually simple analysis of AGM’s convergence by using the analysis of PPM. The derivations also naturally extend to the strongly convex case. Ultimately, the results presented in this paper are of both didactic and conceptual value; they unify and explain existing variants of AGM while motivating other accelerated methods for practically relevant settings.
Flavonoids: A Group of Potential Food Additives with Beneficial Health Effects

Recently, there has been an increasing interest in health-promoting products which are also natural and safe for consumption because the consumer market has been searching for a healthy lifestyle. This global market trend has driven the food industry to invest in developing innovative products containing bioactive components. Flavonoids are a group of phenolic compounds of low molecular weight, consisting of 15 carbon atoms. Their alterations in the heterocyclic ring’s substitution pattern generate six subclasses: flavonols, flavanols, flavones, flavanones, isoflavones and anthocyanins. Also, different studies have reported that diets rich in flavonoids provide numerous benefits associated with health-promoting effects by reducing the risk of development of chronic diseases such as cardiovascular diseases, diabetes type II and some types of cancers. These effects have been related to their biological properties which also include other activities such as colorant effects (e.g., anthocyanins), transforming them into potential food additives with desirable capacities. Therefore, this review aims to revise the classes of flavonoids and their main biological properties as well as the most used extraction techniques applied for obtaining these compounds, their bioavailability and the application to formulate new natural food additives.
Single phase shunt active power filter with simplified ADALINE neural network

Shunt active power filter is known as powerful tool to compensate current harmonics. Previous development of its controller was by using modified ADALINE algorithm for harmonics extraction, which somehow still having complex features. Therefore, this paper presents three major improvements to the algorithm in related to sine and cosine vectors, weight updating algorithm, and average square error. The proposed algorithm is designed and developed in shunt APF's controller, and the shunt APF is simulated in MATLAB/Simulink. The simulation results show significant improvement as compared to the previous algorithm.
Biogenic Synthesis of Bi-Metallic (Zn-Cu) Nanoparticles by Leaf Extract of Citrus Limon and Evaluation of its Antibiofilm Activity Against E. coli

The rapid hike in the usage of metallic as well as non-metallic nanoparticles demands their increased synthesis. In our study we synthesized bimetallic Zn-Cu nanoparticles using the greener route i.e. dry leaves powder of Citrus limon as it is environment-friendly, cost-effective, has a high surface area to volume ratio and hence superior over monometallic nanoparticles synthesized via physical or chemical approach. UTI is the most common nosocomial infection and the bacteria associated with it usually is E. coli. This pathogen forms biofilm and makes it difficult to treat the disease in less time. Hence, antimicrobial as well as antibiofilm activity of synthesized bimetallic nanoparticles was checked against E. coli. Our experimental procedure involved the preparation of ethanolic plant extract using dry leaf powder followed by synthesis of bimetallic nanoparticles. Particles were then characterized by using biophysical techniques such as FTIR, Powder-XRD and SEM-EDX. Next, we identified bacteria isolated from environment and hospital source and prepared their pure cultures. Lastly, we carried out the antibacterial and antibiofilm activity of synthesized nanoparticles against isolated E. coli. Particles showed the colour change from blue to green upon synthesis and were found to be a triclinic primitive type with an average particle size calculated to be 27.76nm as seen in PXRD. FTIR analysis gave characteristic peaks of functional groups. SEM-EDX confirmed successful doping and grain size of the particle. Bacteria isolated from samples showed pink rods in gram staining indicating gram-negative bacilli. Biochemical findings confirmed E. coli in samples. Characteristic zones of inhibition in range 12-18mm establish good antibacterial properties with MIC of synthesized nanoparticles <0.5mg/ml and crystal violet assay assure antibiofilm properties of Zn-Cu. The result of the study can be advantageous to develop an understanding of the development of nano-based medicine for biofilm-producing pathogens.
MSC-Net: Multitask Learning Network for Retinal Vessel Segmentation and Centerline Extraction

Automatic segmentation and centerline extraction of blood vessels from retinal fundus images is an essential step to measure the state of retinal blood vessels and achieve the goal of auxiliary diagnosis. Combining the information of blood vessel segments and centerline can help improve the continuity of results and performance. However, previous studies have usually treated these two tasks as separate research topics. Therefore, we propose a novel multitask learning network (MSC-Net) for retinal vessel segmentation and centerline extraction. The network uses a multibranch design to combine information between two tasks. Channel and atrous spatial fusion block (CAS-FB) is designed to fuse and correct the features of different branches and different scales. The clDice loss function is also used to constrain the topological continuity of blood vessel segments and centerline. Experimental results on different fundus blood vessel datasets (DRIVE, STARE, and CHASE) show that our method can obtain better segmentation and centerline extraction results at different scales and has better topological continuity than state-of-the-art methods.
Schild analysis of the interaction between parthenolide and cocaine on their effects on planarian motility suggests an orthosteric relationship

One of the best-characterized planarian behaviors induced by various compounds is the change in locomotor velocity. Previous work from our laboratory showed that the sesquiterpene lactone parthenolide and the local anesthetic cocaine, reduce planarian motility. Parthenolide reverses the cocaine-induced motility decrease and vice versa. However, the exact mechanism of the cocaine/parthenolide antagonism for this specific planarian behavior is still unknown. Here we report the results of a Schild analysis to determine whether the parthenolide/cocaine relationship is orthosteric or allosteric. Our results suggest an orthosteric relationship between these two compounds in the planarian Girardia tigrina. The simplest interpretation of our data is a shared binding site for cocaine and parthenolide. Still, we cannot rule out the possibility of distinct yet overlapping binding sites with the data available.
Students’ Perceptions on The Effectiveness of Islamic and Asian Civilization Mooc as A Blended Learning Course

Blended learning is an integration of face-to-face, online teaching and learning process whereby it has been developed to improve the conventional learning method. Massive Open Online Courses (MOOCs) platform in Malaysia has been designed purposely to incorporate the blended learning approaches. Therefore, this study aims to examine students' perceptions on the effectiveness of Islamic and Asian Civilization MOOC as a blended learning course. The study employed a quantitative approach through survey method and purposive sampling was chosen as the sampling technique. The study was conducted among first year students in 19 Malaysian public universities by using an online questionnaire. A total number of 1373 public university students from five different zones were involved as respondents. The results revealed that the respondents have good perception on the effectiveness of MOOC platform with a mean score of 4.07. In addition, the finding also shows a significant relationship between student's perceptions on the effectiveness and their acceptance of MOOCs. The students' perspective also delineates that blended learning courses will positively impact the students' knowledge, motivation and soft skill. This study highlights the importance of the students’ viewpoints in determining the effectiveness of a blended learning approach such as MOOCs.
Prevalence of KRAS, PIK3CA, BRAF and AXIN2 gene mutations in colorectal cancer and its relationship with dental agenesis: a systematic review

Introduction: The study of allelic and genotypic frequencies contributes to determining the distribution of genetic variants in different populations and their possible association with biomarkers. This knowledge could improve the decision-making process regarding the management of some diseases such as colorectal cancer (CRC), in which the detection of clinical biomarkers such as dental agenesis could be crucial in clinical practice. Objective: To evaluate the available scientific evidence on the prevalence of KRAS, PIK3CA, BRAF and AXIN2 mutations and their possible association with dental agenesis in people with CRC. Materials and methods: A systematic search was conducted in PubMed, EMBASE and Cochrane Library databases using the following search strategy: type of studies: observational studies reporting the prevalence of KRAS, PIK3CA, BRAF and AXIN2 mutations in people diagnosed with CRC and their possible association with dental agenesis; publication language: English and Spanish; publication period: 2010-2020; search terms: “Genes”, “RAS”, “Kras”, “PIK3CA”, “BRAF”, “AXIN2”, “Mutation”, “Polymorphism”, “Colorectal Neoplasms”, “Colorectal Cancer”, used in different combinations (“AND” and “OR”). Results: The initial search yielded 403 records, but only 30 studies met the eligibility criteria. Of these, 11, 5, 5 and 1 only reported the prevalence of PIK3CA, KRAS, BRAF and AXIN2 mutations, respectively; while 8 reported the prevalence of more than one of these mutations in patients with CRC. The prevalence of KRAS (p.Gly12Asp), PIK3CA (p.Glu545Lys), and BRAF (p.Val600Glu) mutations ranged from 20.5% to 54%, 3.5% to 20.2%, and 2.5% to 12.1%, respectively. There were no findings regarding the association between the occurrence of these mutations and dental agenesis. Conclusions: KRAS mutations were the most prevalent; however, there is no evidence on the association between dental agenesis and the occurrence of KRAS, PIK3CA and BRAF germline mutations in individuals with CRC.
Wave Analysis for Offshore Aquaculture Projects: A Case Study for the Eastern Mediterranean Sea

The investigation of wave climate is of primary concern for the successful implementation of offshore aquaculture systems as waves can cause significant loads on them. Up until now, site selection and design (or selection) of offshore cage system structures on extended sea areas do not seem to follow any specific guidelines. This paper presents a novel methodology for the identification of favorable sites for offshore aquaculture development in an extended sea area based on two important technical factors: (i) the detailed characterization of the wave climate, and (ii) the water depth. Long-term statistics of the significant wave height, peak wave period, and wave steepness are estimated on an annual and monthly temporal scale, along with variability measures. Extreme value analysis is applied to estimate the design values and associated return periods of the significant wave height; structures should be designed based on this data, to avoid partial or total failure. The Eastern Mediterranean Sea is selected as a case study, and long-term time series of wave spectral parameters from the ERA5 dataset are utilized. Based on the obtained results, the most favorable areas for offshore aquaculture installations have been identified.
Fault/Damage Tolerant Control of a Quadrotor Helicopter UAV using Model Reference Adaptive Control and Gain- Scheduled PID

In this paper, two useful approaches to Fault Tolerant Control (FTC) for a quadrotor helicopter Unmanned Aerial Vehicle (UAV) in the presence of fault(s) in one or more actuators during flight have been investigated and experimentally tested based on a Model Reference Adaptive Control (MRAC) and a Gain-Scheduled Proportional-IntegralDerivative (GS-PID) control. A Linear Quadratic Regulator (LQR) controller is used in cooperation with the MRAC and the GS-PID to control the pitch and roll attitudes of the helicopter. Unlike the MRAC, the GS-PID is used only to control the helicopter in height control mode. MRAC is used to control the helicopter in both height control as well as trajectory control. For damage tolerant control the MRAC is evaluated based on partial damage of one of propellers during flight. Finally, the experimental flight testing results of both controllers are presented for the fault tolerant control performance comparison in the presence of actuator faults in the quadrotor UAV.
Isolation of Shewanella putrefaciens GRD 03 from Fish and Explication of Biofilm Adherence Potency on Different Substrates

Foodborne pathogens are the main threat and cause of food poisoning. The majority of food infections have been related to the biofilm formation of foodborne pathogens in the food industry. Shewanella putrefaciens (KX355803, GRD 03), a Gram-negative pathogen isolated from mackerel fish, was identified and recognized as a food spoilage bacterium and a strong biofilm producer. The adhesion or attachment ability of Shewanella putrefaciens was determined on steel, plastic, glass, PVC and wood. NB (Nutrient broth), LB (Luria-Bertani broth), TSB (Tryptic soy broth) and BHI (Brain heart infusion broth) were enriched with glucose and shows optimum for bacterial adhesion. In the microtiter plate method (MTP), the strong attachment was observed at 48 and 72 hours of incubation and significant differences were obtained at p < 0.05. As the incubation period increases, the OD value (Optical density) of samples also increase. Biofilm formation is the major cause cross-contamination, and shows resistance to certain disinfectants, which leads to environmental stress tolerance. This study suggested with optimum biofilm production of isolate from fish by using glucose enriched media on different substrates, also comparing different growth media provide a detailed idea about biofilm-forming ability at different incubation time intervals.
Messaging Matters: Order of Experience with Messaging at a STEM-Based Museum Exhibit Influences Children’s Engagement with Challenging Tasks

Abstract This project examines how the order of messaging during parent–child interactions at a museum exhibit affects children’s engagement with the exhibit. Parents and 4-7-year-olds (N = 64) played at a circuit block exhibit. They were first given blocks with descriptive (e.g., “This is a battery.”) or discovery-prompting (e.g., “There is no wrong way to play.”) messages, and after 90 seconds, given more blocks with the other message type. Children who received discovery-prompting messages second – after being allowed to explore the affordances of the circuit blocks with the descriptive messages – played at the exhibit longer, and participated in more circuit-building challenges on their own. Parents were also sensitive to the order of the messaging; it related to the ways in which they interacted with their children at the exhibit. We conclude by considering how the timing of messages families receive at an exhibit relates to the way they engage with the exhibit. Supplemental data for this article is available online at https://doi.org/10.1080/10645578.2021. 2015948 .
Distributed Cluster Head Election (DCHE) Scheme for Improving Lifetime of Heterogeneous Sensor Networks

Due to environmental characteristics, limited power and processing capabilities of wireless sensor networks, it is essential to find new techniques that improve the flow of information in the network. The cluster head election among the sensor nodes is an effective technique in wireless sensor networks to increase the network efficiency, scalability and lifetime. In this paper, we have proposed and evaluated a distributed cluster head election scheme for heterogeneous sensor networks. The election of cluster heads is based on different weighted probability. The cluster’s member nodes communicate with the elected cluster head and then cluster heads communicate the aggregated information to the base station via single hop communication. Adopting this approach, our simulation results demonstrate that the proposed scheme offers a much better performance than the existing protocols in terms of stability and network lifetime.
Online Action Change Detection for Automatic Vision-based Ground Control of Aircraft

Classical action recognition algorithms require the user to pre-select the time window for the action by clipping the video or choosing the initial and final time frames. Recently, new deep learning algorithms have been developed to detect a key action from an untrimmed video. However, they are unsuitable for temporally segmenting continuous action sequences and are too computationally expensive for implementation on autonomous systems. This paper presents a fast and accurate online action change detection framework. Given a streaming RGB video, the algorithm is used to detect any changes in the sequence. If a new action is discovered, the action recognition module will be applied to classify the action. Compared to existing methods, this two-stage approach reduces computational cost by not applying the recognition algorithm on every time window and improves classification accuracy by locating the starting time step of each action. In a simulated airport environment created using Unreal Engine TM, the framework is demonstrated and validated by detecting and recognizing sequential gestures from a ground crew, who sends gesture commands to control the movement of an autonomous aircraft. A hybrid optimal controller is developed to combine the visual information obtained from the framework and prior information, such as airport map and reference lines, to control the aircraft to safely navigate to a terminal gate.
OPTIMIZED AQUIFER MANAGEMENT, USING LINEAR PROGRAMMING. AN APPLICATION TO THE AGIA VARVARA AQUIFER, DRAMA, GREECE

ABSTRACT The present research analyzes the behavior of Agia Varvara aquifer in Drama, Greece. A comprehensive and complete simulation-management combination model is applied, capable of calculating the water mass balance of the aquifer and defining the optimal management solution. In order to simulate the aquifer, a finite difference model is used. By applying this model and the Response Matrix Method, the management of the aquifer is achieved. Once the simulation of the aquifer is finished, the Linear Programming analysis is performed to obtain the optimal values of piezometric heads and flow rates, imposed to the system on monthly basis, in order to meet the demand of water at the lowest cost. The resulting piezometric heads are compared with the initial ones, enabling scenarios about the maximum and minimum drawdown, and providing the critical months of irrigation. The Linear Programming is used to facilitate the operation of systems, maximizing the total amount of pumped water, under a given set of constraints.
Predicting Mobile Cross-Platform Adaptation Using a Hybrid Sem-ANN Approach

Owing to constant changes in user needs, new technologies have been introduced to keep pace by building sustainable applications. Researchers and practitioners are keen to understand the factors that create an attractive user interface. Although the use of cross-platform applications and services is increasing, limited research has examined and evaluated cross-platforms for developing mobile applications for different operating systems. This study evaluates crossplatform features, identifying the main factors that help to create an attractive user adaptation when building sustainable applications for both Android and iOS. Flutter and React Native were selected so end-users could test their features using the cross-platform usability assessment model. Usability, satisfaction, and navigation were tested to measure the cross-platform adaptation and end-user experience. The data were analyzed using hybrid structural equation modeling (SEM) and artificial neural network (ANN) approaches. The study results show that usability and navigation both have a positive effect on adaptation on Flutter and React Native, while satisfaction only has an effect on Flutter. The navigation variable was also the most significant predictor of adaptation for both models. This study has several implications and makes contributions to the research field, to developers, and to end-users.