Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Antioxidant Enzymes in Natural and Commercial Honey

Honey is popular all over the world and used commonly in medicines and food. This study was designed to compare the natural and commercial honey for their antioxidant enzymes. In this study, 11 different honey samples were collected from different areas of Balochistan. The activity of different antioxidants like superoxide dismutase, peroxidase and catalase enzymes were measured and compared by standard curves of pure enzymes moreover, protein content was also determined by using Bradford Assay. Results showed that highest protein content was found in one of the natural honey samples (4.42 ± 0.02 U/mg) enzymes like superoxide dismutase showed highest activity of (4.93 ± 0.06 U/mg) secondly peroxidase activity of (0.34 ± 0.02 U/mg) and third catalase activity of (0.22 ± 0.01 U/mg) in different natural honey samples. The current study demonstrated that higher concentration of protein content and antioxidant enzymes were found in natural honey which means they are good source of antioxidants. Therefore, antioxidant enzymes can be used as markers for determining the purity and quality of honey.
Marathi SentiWordNet: A lexical resource for sentiment analysis of Marathi

Sentiment analysis (SA) is information retrieval and computational linguistics that expresses sentiment about a specific document. Recently, research on SA has received greater interests due to the vast expansion of internet data. The comments and reviews posted online creates difficulties to the researchers, because the comments posted are written in unstructured formats with informal expressions, languages and possibly mixed languages. Most of the works on SA have been focusing only on English language but with respect to Indian languages, few works are done, especially on Hindi, Telugu, Bengali, and so forth. SentiWordNet is a useful lexical resource for determining the sentiment of a document or piece of text. There is currently no lexical resource for the Marathi language used for sentiment analysis. Therefore, this proposed research presents SA in one of the languages of Indian origin, that is, Marathi. In this paper, a new method is proposed for the development of a Marathi SentiWordNet (M‐SWN), synset‐based expansion approach using Marathi WordNet, which consists of Positive, Negative, and Neutral Polarity score, mapped from Hindi‐SentiWordNet (H‐SWN). Finally, sentiment analysis of movie reviews is carried out using M‐SWN using Bi‐LSTM based SVM classifier model.
Influence of Neutron Irradiation on the Magnetic Properties of FeNiCrMoSiB Amorphous Alloys

The effects of neutron irradiation on the magnetic properties of FeNiCrMoSiB amorphous alloys are investigated by means of the temperature dependence of the spontaneous magnetization and the low field ac susceptibility. It is found that the irradiation leads to a decrease of the values of Curie temperature and the spin-wave stiffness constant. These findings are discussed in terms of the possible irradiation induced effects of structural and chemical changes in the amorphous alloys investigated. [Russian Text Ignored].
Advances in Visual Simultaneous Localisation and Mapping Techniques for Autonomous Vehicles: A Review

The recent advancements in Information and Communication Technology (ICT) as well as increasing demand for vehicular safety has led to significant progressions in Autonomous Vehicle (AV) technology. Perception and Localisation are major operations that determine the success of AV development and usage. Therefore, significant research has been carried out to provide AVs with the capabilities to not only sense and understand their surroundings efficiently, but also provide detailed information of the environment in the form of 3D maps. Visual Simultaneous Localisation and Mapping (V-SLAM) has been utilised to enable a vehicle understand its surroundings, map the environment, and identify its position within the area. This paper presents a detailed review of V-SLAM techniques implemented for AV perception and localisation. An overview of SLAM techniques is presented. In addition, an in-depth review is conducted to highlight various V-SLAM schemes, their strengths, and limitations. Challenges associated with V-SLAM deployment and future research directions are also provided in this paper.
Casimir-Based Control Beyond the Dissipation Obstacle

A prevailing trend in the stabilization of port-Hamiltonian systems is the assumption that the plant and the controller are both passive. In the standard approach of control by interconnection based on the generation of Casimir functions, this assumption leads to the dissipation obstacle, which essentially means that dissipation is admissible only on the coordinates of the closed-loop Hamiltonian that do not require shaping and thus severely restricts the scope of applications. In this contribution, we show that we can easily go beyond the dissipation obstacle by allowing the controller to have a negative semi-definite resistive structure, while guaranteeing stability of both the closed-loop and the controller.
Distributed MPC-Based String Stable Platoon Control of Networked Vehicle Systems

In this paper, the string stable platoon control problem of discrete-time networked vehicle systems is considered by using distributed model predictive control (MPC) based method. An optimization problem is established to minimize the cost function associated to the system trajectories. The last-step shifting method is applied to set the local optimal solution as the assumed solution and send it to the neighbor vehicles. By using the sum of the cost function as Lyapunov function, the stability of the closed-loop platoon system is studied. Comparing with existing results, the string stability, which is the unique characteristics of the platoon system, is guaranteed under the bidirectional-based structure as well as the predecessor-follower-based information flow structure. Finally, several simulations are presented to demonstrate the effectiveness of the proposed algorithms.
Fairness constraint efficiency optimization for multiresource allocation in a cluster system serving internet of things

Massive, diverse, and high‐frequency Internet of Things (IoT) applications pose challenges to the operation of cluster systems that serve it. Fair and efficient multidimensional resource allocation is of great significance to the sustainable operation of these systems. However, most of the existing cluster multiresource allocation optimization researches focus too much on the fairness of resource allocation and ignore the efficiency. The unbalanced use of multidimensional system resources reduces the effective utilization of system resources, which seriously affects the service quality of IoT applications. In this paper, we define the multiresource fair and efficient sharing optimization as a fairness‐constrained efficiency optimization problem, which is from dynamics, discrete resources, and heterogeneous perspectives according to the characteristics of cluster system in practical. Moreover, we present a dynamic efficiency‐aware multiresource fair allocation algorithm, DEF, which can improve the ability of the cluster system to serve diverse IoT applications. In the algorithm, large jobs schedule to the servers that expect the least remaining resources. Simulations performed using Google cluster‐usage traces show that DEF can improve system resource utilization and guarantee the fairness of sharing among users.
Multivariate Normal Approximation by Stein's Method: The Concentration Inequality Approach

The concentration inequality approach for normal approxima- tion by Stein's method is generalized to the multivariate setting. We use this approach to prove a non-smooth function distance for multivariate normal approximation for standardized sums of k-dimensional indepen- dent random vectors W = Pn=1 Xi with an error bound of order k 1/2 where = P n=1 E|Xi| 3 . For sums of locally dependent (unbounded) ran- dom vectors, we obtain a fourth moment bound which is typically of order Ok(1/ p n), as well as a third moment bound which is typically of order
Broadcast application of ground silicate rocks as potassium sources for grain crops

Abstract The objective of this work was to evaluate the agronomic and economic efficiency of phonolite rock (K2) and alkaline potassium-silicate rock (K3), ground and applied by surface broadcasting, as K sources for the soybean (Glycine max), corn (Zea mays), common bean (Phaseolus vulgaris), and upland rice (Oryza sativa) crops. Four experiments – one with each crop – were conducted in two crop years in a Typic Haplorthox in a randomized complete block design with four replicates. The treatments consisted of three sources (the KCl standard source, K2, and K3) and four rates (0, 0.5, 1.0, and 2.0 times the recommended for each crop) of K. The three sources increased similarly the leaf K concentration of soybean, corn, and common bean but had no effect on that of upland rice. The grain yield of all crops increased with the application of K2 and K3, as observed for KCl. The efficiency of the alternative K sources varies depending on the rate and crop. The K3 source is viable to be applied by broadcasting at the recommended K rate for all studied crops, while K2 is suitable only for soybean, corn, and common bean.
Order batching for picker routing using a distance approximation

In this paper we investigate the problem of order batching for picker routing. Our approach is applicable to warehouses (storage areas) arranged in the standard rectangular grid layout, so with parallel aisles and two or more cross-aisles. The motivation underlying our work is online grocery shopping in which orders may be composed of dozens of items. The approach presented directly addresses order batching, but uses a distance approximation to influence the batching of orders without directly addressing the routing problem. We present a basic formulation based on deciding the orders to be batched together so as to optimise an objective that approximates the picker routing distance travelled (both the distance travelled within aisles and the distance travelled within cross-aisles). We extend our formulation by improving the cross-aisle distance approximation for cases where we have more than one block in the warehouse. We also extend the aisle distance approximation and present constraints to remove symmetry in order to lessen the computational effort required. Once order batching has been decided we optimally route each individual picker using a previous approach presented in the literature. Publicly available test problems involving up to 30 orders are solved using our distance approximation formulation to proven optimality. We consider both single and multiple block warehouse configurations. Our results indicate that our distance approximation approach yields very good estimates of the underlying routing distance, and hence very good assignments of orders to batches.
EU Presidency Programmes as a Genre

Along with acting in political, economic and social arenas of the European Union, Latvia was also honoured to preside over the Council of Europe in 2015. This has resulted in the creation of the network of genres pertinent to this communicative event in both Latvian and English to reflect the discursive practices involved. In this view, the present cross-sectional empirical research aims at exploring the written genre of the European Union presidency programmes as one of fundamental documents to propose a set of tentative activities in various economically and socially significant spheres. The theoretical framework for analysis involved the fundamental principles of institutional discourse and the tenets of English for Specific Purposes and New Rhetoric Genre Schools. The exploration of the situational context involves the description of players, the discursive practices and the genre as a textual manifestation of this practice. The results of genre analysis highlight the centrality of the communicative aim and rigid generic macro-structure of a relatively novel genre, which relates to the colony of reporting genres performing the transactional language metafunction. The variation of optional moves occurs as allowed by the communicative aim, which contributes to genre integrity. The topicality of the study is determined by the scarcity of previous research on the genre in question and wide application of research findings.
Sensitivity analysis of a Venturi shaped structure for cross-flow turbines

Tidal energy is one of the world's most predicable renewable energy sources and therefore holds great potential to be a valuable building block for the decarbonisation of electricity production. This paper focuses on a Venturi shaped duct structure (shroud) to accelerate the flow speed at a vertical axis tidal turbine utilising the low static pressure created at the exit of the shroud. This concept is known as a Davidson Hill Venturi (DHV) turbine. By constructing the nozzle and diffusor using hydrofoils, initial demonstrations indicate increased system efficiency. However, owing to the potential number of geometric and structural hydrofoil variations, only a general description of the location of the hydrofoils is provided in order to facilitate modelling while allowing for future geometric variations to be devised. The conducted investigations focus on the influence of the nozzle and diffusor sections as the main geometry variations, identifying the length component in the orthogonal direction as the dominant parameter. By modelling multiple combinations of these variables it is clear that higher fluid velocities result in larger forces which must be supported by the devices structure. Small adjustments to the reference geometries hydrofoil placement and spacing provided improvements to the fluid flow. Thus, taking the slight alteration to the geometry as this papers main outcome, a further in a 3D-simulation study, including turbine interaction and rotation, is to be completed to fully characterise the systems benefits. The insights gained from this work will allow a reduction in computational costs for the detailed optimisation and study into the adaption of the concept for a wide range of (environmental) boundary conditions.
Note on the redistribution and dissipation of tidal energy over mid-ocean ridges

The redistribution and dissipation of internal wave energy arising from the conversion at mid-ocean ridges of the barotropic tide is studied in a set of numerical experiments. A two-dimensional non-hydrostatic model with 100 m horizontal and 10–25 m vertical resolution is used to represent the detailed processes near an idealised ridge. Conventional internal wave beams at the tidal frequency, , appear. At the ridge crest, strong tidal energy dissipation occurs that both mixes the fluid and generates strong near-inertial oscillations radiating in near-horizontal beams. Resonant triad interaction between the tidal and inertial motions in turn produces beams at and with high shear, thus effectively mixing fluid at considerable heights above the ridge crest.
The relationship between zooplankton occupancy and abundance in a floodplain is mediated by the hydrological regime

Abstract: Aim Positive relationships between occupancy and abundance are often found for different groups of organisms and ecosystem types. However, to our knowledge, no study has sought to assess this relationship considering a context in which a particular mechanism is the most likely explanation. In this study, in addition to the positive relationship with abundance, we tested the hypothesis that occupancy of zooplankton species should be greater during the flood season because in this period the hydrological connectivity is greater than in the dry season, facilitating passive dispersal between floodplain environments. Methods Our study was carried out at 52 sites - including lakes and rivers - on the Araguaia River floodplain. We used an analysis of covariance to test the effects of abundance and hydrological period on zooplankton occupancy. Results We found, as expected, a positive relationship between occupancy and abundance of zooplankton species in each hydrological period. Our results also indicated that, with the increase in abundance, species occupancies were higher in the flood than in the dry season. Conclusions The positive effect of the flood on zooplankton occupancy can be explained by the increase in water level that increases the hydrological connectivity and the potential for plankton passive dispersal.
Investigating the dimensions of students’ interaction in listening online learning environment amidst Covid-19 pandemic

The existence of the COVID-19 pandemic forces the Indonesian government to carry on online learning at all education levels, to keep the teaching and learning going on. For students, this ongoing online learning has brought about various impacts on their online learning success. One important factor determining online learning success is students’ interaction. Thus, paying more attention to whether an online learning environment has promoted the students’ interaction is crucial to creating successful online learning. This study aimed to investigate the dimensions of students’ interaction in the online listening learning environment. Moreover, this study also tried to explore how students perceived the interaction in the online listening learning environment. There were 78 students majoring in English Education as participants in this study. A convergent mixed-method was applied in this study, in which the results of the quantitative and qualitative data analysis were brought together. A modified questionnaire of OLLES (Online Learning Environment Survey) and a close-ended interview were carried out to gather the data. The results showed that the dimensions of interaction in the online listening learning environment had a statistically significant high rating. The interaction between the lecturer and the students placed the highest among all of the dimensions. Overall, all the dimensions of interaction in online listening learning were highly perceived by the students. The implications suggested that providing well-designed authentic materials, collaborative activities, and asynchronous models were needed to support the students’ online learning performance.
Data‐iteration cooperative adaptive cruise control of mixed heterogeneous vehicle platoons with unknown dynamic characteristics

This paper considers the cooperative adaptive cruise control (CACC) problem of mixed heterogeneous vehicle platoons composed of human‐driven and CACC vehicles with unknown dynamic characteristics and an alternative to CACC for platooning of the heterogeneous vehicle platoon is presented. Adaptive dynamic programming is firstly used to learn the dynamic characteristics of acceleration of vehicles from the sampled data. Then the data‐iteration optimal CACC controller is computed to ensure that each CACC vehicle can reach a desired inter‐vehicle distance and desired common velocity with no prior knowledge of the dynamics of vehicles in the mixed platoon. Moreover, the string stability of the mixed vehicle platoon is derived by establishing some sufficient conditions on the acceleration transfer function of adjacent vehicles. Two simulation experiments of a six‐vehicle mixed platoon are used to illustrate the effectiveness of the proposed CACC method.
Representing de Rham cohomology classes on an open Riemann surface by holomorphic forms

Let X be a connected open Riemann surface. Let Y be an Oka domain in the smooth locus of an analytic subvariety of ℂn, n ≥ 1, such that the convex hull of Y is all of ℂn. Let 𝒪∗(X,Y ) be the space of nondegenerate holomorphic maps X → Y. Take a holomorphic 1-form θ on X, not identically zero, and let π :𝒪∗(X,Y ) → H1(X, ℂn) send a map g to the cohomology class of gθ. Our main theorem states that π is a Serre fibration. This result subsumes the 1971 theorem of Kusunoki and Sainouchi that both the periods and the divisor of a holomorphic form on X can be prescribed arbitrarily. It also subsumes two parametric h-principles in minimal surface theory proved by Forstneric and Larusson in 2016.
A time-stepping for incompressible Navier-Stokes Equations

In this work, a numerical solution of the unsteady incompressible Navier-Stokes equations is proposed. We describe a general solution strategy that has two basic building blocks, a fully implicit time integrator using a stabilized trapezoid rule with an explicit Adams-Bashforth method for error control, and a robust Krylov subspace solver for the spatially discretized system. In order to evaluate the performance of the method, the numerical results are compared with some previously published works or with others coming from commercial code like Adina system.
Sentiment- Emotion- and Context-Guided Knowledge Selection Framework for Emotion Recognition in Conversations

Emotion recognition in conversations (ERC) needs to detect the emotion of each utterance in conversations. However, it is difficult for machines to recognize the emotion of utterances like humans, partly because of the lack of commonsense knowledge. Despite existing efforts gradually incorporate knowledge in ERC, they can not adaptively adjust knowledge according to different utterances and their context. In this article, we propose a knowledge selection framework SKSEC (Select Knowledge in light of Sentiment Emotion and Context). In the SKSEC framework, first, external knowledge is eliminated by three Knowledge Elimination (KE) modules. More concretely, In word-level KE, the concept knowledge different from the sentiment corresponding to the word in utterances is randomly eliminated. In utterance- or context-level KE, If the similarity between the knowledge representation and the emotion label representation of the current utterance or its context is less than the preset threshold, the knowledge will be eliminated. Then we refine the weight of knowledge using two Graph ATtention (GAT) mechanisms. Specifically, In Sentics GAT, we employ a dimensional emotion model to measure words in utterances and their corresponding knowledge and adjust the weight of knowledge according to their emotional similarity. In Semantics GAT, the weight of knowledge is adjusted according to the semantic similarity between context and incorporated knowledge. Finally, we feed the selected knowledge to the most advanced models to evaluate the quality of knowledge. The experimental results show that the SKSEC framework can effectively improve the performance of the model by eliminating and refining external knowledge in different size and domain datasets.