Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review of the Utilisation of Recycled Waste Material as an Alternative Modifier in Asphalt Mixtures

The possibility of using waste materials in road construction is of great interest as their utilisation may contribute to reducing the problems of hazard and pollution and conserve natural resources. Thus, there is an urgent need to find a sustainable method for using waste materials as a substitute in the standard asphalt binders. There are several concerns about the physical and chemical properties and mechanical performance of asphalt pavements incorporated with waste material in the effort to reduce permanent deformation of the road surface. This review article presents a brief discussion of the asphalt mixtures modified with waste material, and the recycled materials used as a modifier in the asphalt mixture. The present paper summarises the use of crumb rubber, crushed concrete, steel slag, glass fibre and plastic waste in asphalt mixtures. The use of waste materials as a modifier in asphalt mixture resulted in improved asphalt pavement performance. Results advocate that rubberised asphalt mixture with desired properties can be designed as an additive with a friendly environmental approach in construction materials. The researches that adopted the influence of usage, recycle waste material to improve the performance of the asphalt of the road are still limited compared to other construction fields. Doi: 10.28991/cej-2020-SP(EMCE)-05 Full Text: PDF
Three Birds with One Stone: K2SiF6:Mn4+ Single Crystal Phosphors for High‐Power and Laser‐Driven Lighting

Narrow‐band red‐emitting fluoride phosphors play a crucial role in lighting and backlight displays, whereas the stability issue is a major challenge. Here, highly stable K2SiF6:Mn4+ (KSFM) single crystal phosphors with tunable sizes (20–1000 µm) are grown by a facile saturated crystallization method. The small specific surface area together with the unique Mn4+‐rare interface layer in KSFM single crystals enables the simultaneous fulfillment of high external quantum efficiency, excellent moisture, improved thermal quenching, and dissipation for high‐power and laser‐driven lighting applications. As a prototype, a warm white laser diode device with a high luminous flux of 202.7 lm and correlated color temperature of 3277 K, as well as a color rendering index of 87.9 is presented. This work provides new insights into the development of highly efficient and stable materials for advanced lighting applications.
Symmetry-Aware 6D Object Pose Estimation via Multitask Learning

Although 6D object pose estimation has been intensively explored in the past decades, the performance is still not fully satisfactory, especially when it comes to symmetric objects. In this paper, we study the problem of 6D object pose estimation by leveraging the information of object symmetry. To this end, a network is proposed that predicts 6D object pose and object reflectional symmetry as well as the key points simultaneously via a multitask learning scheme. Consequently, the pose estimation is aware of and regulated by the symmetry axis and the key points of the to-be-estimated objects. Moreover, we devise an optimization function to refine the predicted 6D object pose by considering the predicted symmetry. Experiments on two datasets demonstrate that the proposed symmetry-aware approach outperforms the existing methods in terms of predicting 6D pose estimation of symmetric objects.
Configuring the Evolving Role of eWOM on the Consumers Information Adoption

Electronic word-of-mouth (eWOM) is reckoned to be one of the underlying factors that augments online retailing. The information adoption protocols have been revamped due to the extensive online information; consequently, adding a significant influence on the online purchase behaviors. Consumer review websites, shopping platforms, blogs and discussion forums are some of the leading eWOM platforms, as emphasized in prior literature. The current study, however, focuses on eWOM on the social media platforms, as the consumers’ online decision-making process is confined to the adoption of information in the first phase. The study examines the effects of the antecedents of eWOM and multiple mediators (i.e. perceived risk, argument quality, information usefulness and trust inclination) on the consumers information adoption. The study used survey-based data and structural equation modelling (SEM) technique to determine the causality among the constructs. Future directions provide concrete managerial and theoretical implications as highlighted in the study.
Cross-Border E-Commerce Personalized Recommendation Based on Fuzzy Association Specifications Combined with Complex Preference Model

Since cross-border e-commerce involves the export and import of commodities, it is affected by many policies and regulations, resulting in some special requirements for the recommendation system, which makes the traditional collaborative filtering recommendation algorithm less effective for the cross-border e-commerce recommendation system. To address this issue, a simple yet effective cross-border e-commerce personalized recommendation is proposed in this paper, which integrates fuzzy association rule and complex preference into a recommendation model. Under the constraint of fuzzy association rules, a hybrid recommendation model based on user complex preference features is constructed to mine user preference features, and personalized commodities recommendation is realized according to user behavior preference. Compared with the traditional recommendation algorithm, the improved algorithm reduces the impact of data sparsity. The experiment also verifies that the improved fuzzy association rule algorithm has a better recommendation effect than the existing state-of-the-art recommendation models. The recommendation system proposed in this paper has better generalization and has the performance to be applied to real-life scenarios.
Local gradient Bernoulli–Euler beam model for dielectrics: effect of local mass displacement on coupled fields

The size-dependent behaviour of a Bernoulli–Euler nanobeam based on the local gradient theory of dielectrics is investigated. By using the variational principle, the linear stationary governing equations of the local gradient beam model and corresponding boundary conditions are derived. In this set of equations the coupling between the strain, the electric field and the local mass displacement is taken into account. Within the presented theory, the process of local mass displacement is associated with the non-diffusive and non-convective mass flux related to the changes in the material microstructure. The solution to the static problem of an elastic cantilever piezoelectric beam subjected to end-point loading is used to investigate the effect of the local mass displacement on the coupled electromechanical fields. The obtained solution is compared to the corresponding ones provided by the classical theory and strain gradient theory. It is shown that the beam deflection predicted by the local gradient theory is smaller than that by the classical Bernoulli–Euler beam theory when the beam thickness is comparable to the material length-scale parameter. The obtained results also indicate that the piezoelectricity has a significant influence on the electromechanical response in a dielectric nanobeam. The presented mathematical model of the dielectric beam may be useful for the study of electromechanical coupling in small-scale piezoelectric structures.
Performance analysis of randomized arbitration interframe space tuning algorithm for enhanced distributed channel access in IEEE 802.11p based vehicular network

The Internet of Vehicle (IoV) aims to provide efficient vehicular communication by enhancing connectivity and user safety. IEEE 802.11p, a medium access control protocol, plays a vital role in the IoV protocol stack, which uses the enhanced distributed channel access (EDCA) method for channel contention. To deal with safety and nonsafety vehicular applications, EDCA adopts four access categories (AC), and each AC manages the channel access based on the priority of packets along with the contention window size and arbitration interframe spacing number (AIFSN). However, these contention parameters are fixed for each AC, and it does not account the real‐time network traffic. Hence, the fine‐tuning of AIFSN values and maintaining strict priority are challenging tasks for the highly dynamic vehicular network. To address these issues, this article proposes a novel probabilistic approach, namely, the randomized AIFSN tuning (RAT) algorithm for EDCA. It updates AIFSN value for every retransmission based on the vehicle density and contention intensity by preserving the strict priority behavior of the AC queues. A three‐dimensional Markov model is developed to analyze the proposed algorithm in terms of collision probability and throughput. The proposed RAT algorithm is simulated using the NS3 network simulator along with simulations for urban mobility (SUMO) for the real‐time traffic, and results are compared with other related algorithms in terms of packet loss, goodput, packet delivery ratio, and delay of each AC queue. These results reveal that the proposed RAT algorithm outperforms related algorithms under varying vehicle density.
Automated extended depth of focus digital holographic microscopy using electrically tunable lens

A combination of electrically tunable lens with a microscope objective lens (MO) for multifocal plane imaging capability is proposed. The method aims at extending the depth of focus of the MO by changing its axial range and field of view. The combination is implemented in a common path off-axis digital holographic microscopy configuration experimentally and it achieves an axial scanning range of 363.5 μm. It utilizes image plane holography to obtain in-focus images throughout the axial range. The proposed method demonstrates its application in quantitative phase imaging of the USAF 1951 test chart and flowing red blood cells at different axial depths. An axial depth variation of 0.76 μm–0.81 μm is obtained between two consecutive focused planes. The results validate and postulate the advantage of the proposed method over traditional extended depth-of-focus algorithms. The quantitative and qualitative results exploit the possibility of using the proposed method further for localization and tracking of flowing microscopic samples.
The clinical efficacy of orlistat in the treatment of obesity

Background: The prevalence of obesity is gradually increasing worldwide and reaches an epidemic extent. Currently, treatment of obesity with pharmacological options has gained importance due to the frequent failure of lifestyle changes. Anti-obesity medications have an unfortunate history that make many clinicians uncomfortable with their prescription. In this study, we aimed to examine the effect of orlistat on weight loss and glycaemic parameters.Methods: Forty patients under orlistat treatment between November 2017 to October 2018 were recruited and their weight, body mass index (BMI), glucose, insulin, and the homeostatic model assessment of insulin resistance (HOMA-IR) values were recorded before and after treatment. Patients aged >18 years with BMI≥40 kg/m2 were enrolled to the study while having the diagnosis of diabetes mellitus, those with gastrointestinal diseases, who were pregnant or in lactation period, using drugs that have an effect on weight, and who did not come their follow-up after 12 weeks were excluded.Results: Thirty-four patients were female, 6 were male, and the mean age was 42.75±10.60 years. The mean height found as 161.10±8.98 cm. Before treatment, the mean weight was 120.62±16.56 kg, BMI was 46.43±4.61 kg/m2, and HOMA-IR was 5.84±3.58. After 12 weeks, it was observed that the mean weight decreased to 112.67±16.21 kg, BMI to 43.35±4.55 kg/m2, and HOMA-IR to 3.73±2.38. There was a statistically significant difference in these parameters compared to the pre-treatment values.Conclusions: Given the lack of non-surgical treatments, orlistat can provide significant benefits in the current clinical practice when combined with the appropriate diet.
African Humid Period Precipitation Sustained by Robust Vegetation, Soil, and Lake Feedbacks

The African Humid Period (∼11,000–5,000 years before present) was the most recent of several precessionally paced wet intervals during which an increase in the Northern Hemisphere summer incoming solar radiation intensifies the West African Monsoon leading to dramatic changes over northern Africa. However, insolation anomaly alone is not sufficient and feedbacks are essential for further amplification of the monsoon. The most significant feedbacks derive from the land surface, arising from changes to vegetation, soil properties, and distribution of surface water. We show that in contrast to previous studies that have explored the individual impacts of these feedbacks, a modern climate model yields a much greater increase in precipitation in response to their collective effect. Agreement with proxies is improved while the desert‐steppe transition is pushed further northward than in any previous study. In the West African Sahel, intensities of summer daily mean and extreme precipitation increase by 150% and 90%, respectively.
New Prothrombin Mutation (Arg596Trp, Prothrombin Padua 2) Associated With Venous Thromboembolism

Objective—Two different prothrombin variants, p.Arg596Leu and p.Arg596Gln, conferring antithrombin resistance to patients with venous thromboembolism have been recently reported. Here, we describe a novel substitution affecting Arg596 of prothrombin molecule (Arginine596 to Tryptophan or p.Arg596Trp or Arg221aTrp in the chymotrypsinogen numbering system or prothrombin Padua 2) in 2 Italian families with venous thromboembolism. Approach and Results—Prothrombin Padua 2 has been characterized either in plasma of carriers or using Arg596Trp recombinant prothrombin. Routine coagulation tests, thrombin generation, and antithrombin resistance tests were performed, as well as measurement of the levels of thrombin–antithrombin complexes. All carriers were heterozygotes and presented with a mild reduction of the prothrombin activity. Thrombin generation in carriers showed only a markedly prolonged decay. This finding was confirmed in plasma reconstituted with Arg596Trp recombinant prothrombin mimicking a homozygous.
Multiphase SVPWM Strategy Analysis and Implementation of Seven-Phase Permanent Magnet Synchronous Motor

The multiphase motor drive systems have become a focus in many application areas such as ship electric propulsion, urban mass transit, aerospace, and weapon equipment, as they are characterized by high power density, low torque pulsation as small torque ripple, large output power, strong fault tolerance, and high reliability. However, with the increase of the phase number of the motor, the current harmonic component increases correspondingly, which leads to the decrease of the control performance compared with the three-phase system. In order to overcome this challenge, implementation method of driving control technology for seven-phase permanent magnet synchronous motor (PMSM) based on SVPWM algorithm is discussed thoroughly in this paper. Simulink and experiments have been developed to check its practical feasibility. The results show that the near-six vector SVPWM algorithm (NSV-SVPWM) achieves better performance than other methods.
Conserved quantities along with Painlevé analysis and optical solitons for the nonlinear dynamics of Heisenberg ferromagnetic spin chains model

In this paper, we will investigate a famous model of nonlinear sciences namely [Formula: see text]-dimensional nonlinear spin dynamics of Heisenberg ferromagnetic spin chains (HFSC) model for the evaluation of optical travelling waves by implementing unified method (UM). We will extract dark as well as bright solitary waves along with elliptic waves. We will draw conserved quantities of our governing model by utilizing dilation symmetry. At the end, the integrability of nonlinear spin dynamics of HFSC model with the help of Painlevé test will also be studied in this paper.
Platform Spaces: When culture and the arts intersect territorial development and social innovation, a view from the Italian context

ABSTRACT This contribution intends to overview and frame a conceptual model for Cultural and Creative Enterprises (CCEs) that we call Platform Spaces. The paper contextualizes and discusses the main issues and challenges facing the CCE sector, identifying the need for more complex concepts better able to distinguish new policies and approaches being experimented with in Italy and across Europe. As Italy is currently experiencing a particularly rich period regarding the development of cultural creative activities based largely on social innovation, both in terms of organization management and relation with territorial development, it is an ideal context in which to explore the emergence of this new model. The paper describes three diverse examples of Platform Spaces based on multi-stakeholder cooperation mechanisms, arts and culture, and the engagement of local communities to not only ensure the accessibility of their activities but also to meet territorial development goals. With this analysis, the paper discusses a new conceptual framework that can be relevant both in theory and in practice, identifying policy recommendations to address territorial development approaches for Platform Spaces.
Optimal Outage Management Model Considering Emergency Demand Response Programs for a Smart Distribution System

In this paper, a novel smart outage management system considering Emergency Demand Response Programs (EDRPs) and Distributed Generations (DGs) denoted as SOMSDGsEDRPs is proposed. The EDRPs are provided to decrease the cost of load shading in a time of emergency. The objective function of the problem is proposed to minimize the load shading cost, the DG dispatch cost, the demand response cost and the repair dispatch time for crews. The SOMSDGsDERPs solves an optimization problem that is formulated as Mixed Integer Linear Programming (MILP) taking into account the grid topology constraints, EDRP constraints, DG constraints and crew constraints. The MILP formulation was demonstrated in the GAMS software and solved with the CPLEX solver. The proposed method was tested on the IEEE 34 bus test system as well as an actual Iranian 66 bus power distribution feeder. The results show that the EDRPs and DGs can be effective in decreasing the outage cost and increasing the served load of the distribution power system in a crisis time.
Frequency-tagging visual background information enables multi-target perceptual filling-in to be distinguished from phenomenally matched replay

Perceptual filling-in (PFI) occurs when a physically-present visual target disappears from conscious perception, with its location filled-in by the surrounding visual background. Compared to other visual illusions, these perceptual changes are crisp and simple, and can occur for multiple spatially-separated targets simultaneously. Contrasting neural activity during the presence or absence of PFI may complement other multistable phenomena to reveal the neural correlates of consciousness (NCC). We presented four peripheral targets over a background dynamically flickering at 20 Hz, to entrain neural populations responding to the background. While participants reported on target disappearances/reappearances via button press/release, we tracked neural activity associated with PFI using steady-state visually evoked potentials (SSVEPs) recorded in the electroencephalogram. Behaviorally, we found that as the number of filled-in targets increased, the duration of target disappearances also increased, suggesting faciliatory interactions among targets located in separate visual quadrants. We found background SSVEPs closely correlated with subjective report, and increased with an increasing amount of PFI. Unexpectedly, we found distinct spatiotemporal correlates for the SSVEP harmonics. Prior to PFI, the response at 40 Hz preceded the response at 20 Hz, which we tentatively link to an attentional effect. There was no difference between harmonics for physically removed stimuli. These results demonstrate that PFI can be used to study multi-object faciliatory interactions, and because there are distinct neural correlates for endogenously and exogenously induced changes in consciousness, it is ideally suited to study the NCC. Significance statement Perceptual filling-in (PFI) is a transient illusory disappearance of visual objects from consciousness. By holding the object constant, we can contrast neural activity during periods with and without PFI to isolate the neural correlates of conscious perception. Unlike traditional visual illusions, PFIs are subjectively crisp and simple, and can happen simultaneously at different spatial locations. By frequency-tagging the background display, we demonstrate graded neural correlates for graded changes in consciousness, and provide evidence to differentiate between the perceptual processes evoked during PFI from those evoked by the physical removal of the same peripheral stimuli.
Femur Properties of Embryo in the Layer Hybrid and Pure Breeds

I Department of Animal Breeding and Husbandry, Faculty of Veterinary Medicine, Ankara University, Ankara, 06110, Turkey. II Department of Mechanical Engineering, TOBB University of Economics and Technology, Ankara, 06560, Turkey. III Department of Micro and Nanotechnology, TOBB University of Economics and Technology, Ankara, 06560, Turkey. IV Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Ankara University, Ankara, Turkey 06110, Turkey. V Department of Animal Nutrition & Nutritional Diseases, Faculty of Veterinary Medicine, Ankara University, Ankara 06110, Turkey.
MStream: Fast Anomaly Detection in Multi-Aspect Streams

Given a stream of entries in a multi-aspect data setting i.e., entries having multiple dimensions, how can we detect anomalous activities in an unsupervised manner? For example, in the intrusion detection setting, existing work seeks to detect anomalous events or edges in dynamic graph streams, but this does not allow us to take into account additional attributes of each entry. Our work aims to define a streaming multi-aspect data anomaly detection framework, termed MStream which can detect unusual group anomalies as they occur, in a dynamic manner. MStream has the following properties: (a) it detects anomalies in multi-aspect data including both categorical and numeric attributes; (b) it is online, thus processing each record in constant time and constant memory; (c) it can capture the correlation between multiple aspects of the data. MStream is evaluated over the KDDCUP99, CICIDS-DoS, UNSW-NB 15 and CICIDS-DDoS datasets, and outperforms state-of-the-art baselines.
Robot-Safe Impacts with Soft Contacts Based on Learned Deformations

Safely generating impacts with robots is challenging due to subsequent discontinuous velocity and high impact forces. We aim at increasing the impact velocity – the robot’s relative speed prior to contact – such that impact-tasks like grabbing and boxing are made with the highest allowable speed performance when needed. Previous works addressed this problem for rigid bodies’ impacts. This letter proposes a control paradigm for generating intentional impacts with deformable contacts that incorporates hardware and task constraints. Based on data-driven learning of the shock-absorbing soft dynamics and a novel mapping of joint-space limits to contact-space, we devise a constrained model-predictive control to maximize the intentional impact within a feasible, robot-safe level. Our approach is assessed with real-robot experiments on the redundant Panda manipulator, demonstrating high pre-impact velocities (up to 0.9 m/s) of a rigid end-effector on soft objects and an end-effector soft suction-pump on rigid or deformable objects.