Miracle-dz/UniFAR-FTUs huggingface dataset:
Sense-making Analysis: A Framework for Multi-Strategy and Cross-Country Research

While sense-making is a frequently used concept in everyday discourse and in several social science research areas, discussions about how the concept translates into methodology are currently scarce. This paper introduces a framework for analyzing how actors in different cultural contexts make sense of global concepts. By this we refer to expressions that are used and expected to find a common ground worldwide, yet are equivocal in their multiple meanings and connotations. The paper discusses methodological considerations of such a sense-making analysis. The paper cites examples from a mixed-methods, cross-country, sense-making analysis of societal transformations toward sustainability—a concept promoted by the United Nations 2030 Agenda. We identify three steps in a comprehensive sense-making analysis: 1) mapping relevant societal arenas for sense-making; 2) vertical analyses; and 3) horizontal analyses. We outline how different datasets can be approached vertically, focusing on the use of framing, metaphors, categorizations, and stories. This forms the basis for the horizontal analysis of societal narratives and recurrent themes across the different data sources. By presenting comprehensive vertical and horizontal analyses, researchers and state and non-state actors can gain insight into the broader varieties of sense-making that can enrich scientific analysis, enhance transparency and effectiveness in international relations, and support transnational governance and civil society collaborations.
Adoption of Supply Chain Model to Improve Terminal Device Distribution at Mobifone: Evidence from Vietnam

: Purpose: This research explores and clarifies the distribution of terminal devices at Mobifone company (MBC). From the theory of supply chain (SC), the nature and performance of the SC, and the principles of SC construction and operation, the article conducts research on how to complete the construction of SC's terminal device at MBC aims to help MBC leaders identify the advantages and limitations in their existing SC as well as MBC's distribution. From that, MBC managers have the property strategy in investing resources to continue improving the distribution of terminal devices in their SC. Methodology/Approach: A qualitative method with specialized technical expertise and group discussion helps design a questionnaire surveying 132 head store managers at MBC. Finally, using descriptive statistical techniques, primary data is processed on SPSS 20.0 software to measure the factors related to terminal SC construction at MBC. Findings: The findings show that the core activities of the construction of SC's terminal device at MBC are quite suitable. However, it still has some outstanding limitations; there is no department in charge of the overall planning. From the theory of supply chain (SC), the nature and performance of the SC, and the principles of SC construction and operation, the article researches how to complete the construction of SC's terminal device at Mobifone Company (MBC) aims to help MBC leaders identify the advantages and limitations in their existing SC as well as MBC's distribution. Originality/Value: There have been many studies on the supply chain, but most studies only on the relationship of the chain or the chain's effectiveness in many different industries. However, research on the supply chain structure model in the retail sector about terminal equipment in the telecommunications industry has not. Summing up to work out a joint plan across the SC to connect each actor in the SC into a cohesive link to make the SC operation smooth and continuous.
A FRACTAL MODEL FOR PREDICTING THE EFFECTIVE THERMAL CONDUCTIVITY OF ROUGHENED POROUS MEDIA WITH MICROSCALE EFFECT

The effective thermal conductivity (ETC) of roughened porous media (RPM) is of interest in a number of applications of heat transfer. In this work, a fractal analytical model for the ETC of RPM with microscale effect is proposed. The proposed fractal model is expressed in terms of relative roughness, the molecular mean free path, porosity, fractal dimensions (pore area fractal dimension and tortuosity fractal dimension), maximum pore diameter, capillary straight length, and the thermal conductivity of the solid matrix and gas. It is observed that the dimensionless ETC of RPM decreases with increasing relative roughness, pore area fractal dimension and tortuosity fractal dimension. Besides, it is found that the dimensionless ETC of RPM increases with thermal conductivity ratio of gas phase over solid phase. In addition, it is found that the dimensionless ETC of RPM is slightly dependent on the relative roughness and tortuosity fractal dimension when [Formula: see text]. The determined dimensionless ETC of RPM is in good agreement with experimental data and existing models reported in the literature. With the proposed fractal model, the physical mechanisms of heat transport through RPM with microscale effect are better elucidated. Every parameter in the fractal analytical model has clear physical meaning, with no empirical constant.
A review of action recognition based on Convolutional Neural Network

At present, the development of video action recognition is very rapid in many fields, such as video understanding, intelligent monitoring, and human-computer interaction. However, there are some challenges in the development of action recognition, and researchers have tried to put forward some explorations. Convolutional neural network (CNN) is applied to action recognition, which improves the performance of action recognition. It is divided into 3 methods in this paper. In addition, C3D, Two-stream and I3D, three classic CNN algorithms, are reproduced. And their recognition rates are 72%, 78.0% and 97.6% respectively on the UCF101 dataset.
Material ratio curve of 3D surface topography of additively manufactured parts: an attempt to characterise open surface pores

Surface topography of additively manufactured components often contains 3D features, e.g. particles, open surface pores. X-ray computed topography can capture these features, allowing measurement data to be used for 3D surface texture characterisation. On the basis of the newly developed 3D surface texture parameters, this paper investigates material ratio curves of the surfaces produced by additive manufacturing processes, i.e. selective laser melting and high speed sintering. The material ratio curves of these surfaces vary in their shapes, depending on the specific process and associated process parameters, as well as surface orientations. Re-entrant topography features can result in recess shapes on the material ratio curve at the surface heights where these features locate. This unique characteristic makes the material ratio curve an effective analysis tool to differentiate various AM surface topographies, allowing surface texture to be linked with process control and functional assessment. Furthermore, Vvv (valley void volume) is identified as a useful volume parameter to characterise the open surface pores of AM surfaces. The material ratio Mr2 for the determination of Vvv is discussed with the consideration of three options to address the open surface pores. The secant scanning approach proposed by ISO 13565-2 and the manual set ratio at the first sharp drop of the material ratio curve were found to be able to achieve reasonable results for the AM open surface pore characterisation.
Modeling Of Generator Neutral Grounding Through Distribution Transformator Using Lab View Graphical User Interface

Computation of the generator neutral grounding system through a distribution transformer can be done through manual calculations. A lot of data is used in calculations so that the possibility of recurring calculations. This is very difficult and causes a large difference in the calculation results. Therefore, a computer-based computing system is needed to overcome problems like this. Several papers have been developed on the calculation of the voltage capacity through medium grounding, the length of the electrodes attached to the ground of the generator, one-phase faults to the ground, and zero sequence current disturbances. Therefore, this paper discusses modeling using the LabView Graphical User Interface (GUI) application to create it easier to design neutral grounding for equipment. As an implementation, modeling using Std. C62.92. 2TM-2017 data and the results of the generator neutral grounding design can be easy, faster, and more accurate.
Physicochemical properties of phosphate butyrate arenga starches from dual modifications

Native arenga starch has infirmity physicochemical properties so that its use is limited to functional food. Dual modification is a starch processing to improve physicochemical properties of starch. The objective is to determine the optimum concentration of sodium trimetaphosphate (STMP) based on the physicochemical properties of the phosphate butyrate arenga starch (PBAS) from dual modification of butyrylation and phosphorylation. The method of making PBAS is using butyric anhydride 5% (w/v) and STMP concentration variation consisting of 2%, 4%, 6%, 8%, 10% and 12% (w/w) of the starch weight repeated three times and native arenga starch as a comparison. Physicochemical properties analyzed were percent butyryl, degree of substitution (DS), phosphate content, binding of butyrate phosphate with fourier transform infrared (FTIR), water, starch, amylopectin, amylose and ash contents. The results showed that the optimal STMP concentration range of 4-6% based on percent butyryl, DS and phosphate content that produce PBAS suitable for functional food ingredients. Binding of the functional group of PBAS formed a new peak in the FTIR spectra at wave number 1365.60 cm-1 which indicates the presence of phosphate (P=O) groups of STMP on starch molecules. The water content of PBAS decreased with increasing STMP concentrations. The amylose, amylopectin and ash contents of PBAS were changed after the process of butyrylation and phosphorylation. PBAS is potential as a functional food ingredient due to its butyrate and phosphate contents.
Land Tenure Security and Health Nexus: A Conceptual Framework for Navigating the Connections between Land Tenure Security and Health

The rise of urban populations has rendered cities in both developed and developing countries vulnerable to poor health and diseases that are associated with urban living conditions and environments. Therefore, there is a growing consensus that while personal factors are critical in determining health, the urban environment exacerbates or mitigates health outcomes, and as such the solution for improving health outcomes in urban settings can be found in addressing socio-environmental factors that shape urban environments. Land tenure security is a social environmental factor of health that has been understudied by urban geographers despite its obvious role in shaping urban environments, housing conditions, and health. We interpret literature and infer possible pathways through which land tenure security connects to health and propose a land tenure security and health nexus conceptual framework for modeling and investigating the extent of this connection. Based on a narrative review of literature, this inter-disciplinary paper shows that land tenure security can influence health outcomes via four pathways—infrastructure access, environmental justice, psycho-ontological security, and social cohesion. Going forward, a subsequent investigation can focus on developing an index of land tenure security health insults, based on which an empirical investigation of the relationship between land tenure security and health disease is possible.
Structural complexity of Y6BO12 fluorite-related ternary oxides

Oxides with generic stoichiometry M7O12 occupy, in a generic phase diagram, an intermediate place between fluorite and bixbyite structure types. Their structure is derived from the ideal fluorite structure, and it is characterized by a more or less pronounced ordering of the O vacancies within the average fluorite sublattice. We believe that ternary oxides with this kind of formula provide interesting degrees of flexibility for understanding the structural characteristic of these structures in the context of fission product stabilization in nuclear fuels and in the field of actinide waste forms as well. We would like to discuss the structural characteristics of the chemical bonds in ternary systems consisting of trivalent and hexavalent cations. Eventually, in compounds with generic formula Y6B+6O12, the B cation can be either a transition metal (W, Mo) or hexavalent uranium. We believe that studying the polyhedron of the sevenfold coordinated Y ion is particularly interesting to understand the flexibility of the chemical bonds: it is often described in the literature as a mono-capped trigonal prism, with bond lengths exhibiting an extremely large dispersion, ranging for instance from 2.19 to 2.70 Å in Y6WO12. We would discuss the implications of this large dispersion of distances on the chemical bond characteristics and compare DFT models with established experimental knowledge on pristine and irradiated specimens.
Image Accessibility for Screen Reader Users: A Systematic Review and a Road Map

A number of studies have been conducted to improve the accessibility of images using touchscreen devices for screen reader users. In this study, we conducted a systematic review of 33 papers to get a holistic understanding of existing approaches and to suggest a research road map given identified gaps. As a result, we identified types of images, visual information, input device and feedback modalities that were studied for improving image accessibility using touchscreen devices. Findings also revealed that there is little study how the generation of image-related information can be automated. Moreover, we confirmed that the involvement of screen reader users is mostly limited to evaluations, while input from target users during the design process is particularly important for the development of assistive technologies. Then we introduce two of our recent studies on the accessibility of artwork and comics, AccessArt and AccessComics, respectively. Based on the identified key challenges, we suggest a research agenda for improving image accessibility for screen reader users.
Consumer roles of small mammals within fragmented native tallgrass prairie

Grassland ecosystems globally are being negatively impacted by changes in climate, disturbance regimes, nutrient ﬂ ux, and consumer guilds. Changes in the trophic ecology of consumers can sub-stantially in ﬂ uence local resources, contributing to shifting diversity, community turnover, and other processes of ecosystem change. Small mammals are diverse and abundant within grasslands and yet the impact of changing ecosystems on small mammals and the role of these mammals as consumers are still both under-studied. We assessed small mammal resource use within grassland and woodland vegetation types that have resulted from landscape-scale experimental disturbance through ﬁ re treatments within the tallgrass prairie ecoregion of the North American Great Plains. We predicted that resource use would vary signi ﬁ cantly among grassland vs. woodland communities, in turn reducing the role of small mammals in contributing to future maintenance of native prairies. We sampled ﬁ ve dominant species of rodents across three years and multiple habitats. Using stable isotope analysis, we investigated isotopic niche area and overlap to infer variation in diet, both within and among species. Resource use shifted in bivariate isotopic space seasonally but not across years when combining all species and habitats. Inferred spring diet (based on fur samples) was highly diverse and overlapping. Summer isotopic values (based on liver tissue) in woody habitat treatments were narrower and overlapped less than within grassland habitats. Consumers generally shifted from C 4 herbivory to C 3 herbivory, or greater omnivory, when analyzing grassland, shrubland, and woodland habitats respectively. Within the tallgrass prairie ecosystem, small mammal populations in herbaceous-dominated habitats use a broader variety of resources than small mammals in prox-imate woody-dominated habitats. As native grasslands experience woody encroachment, small mammal assemblages experience turnover of dominant species and associated changes in diet. Ecosystem changes such as cessation of frequent ﬁ re resulting in more woody habitats may include reduced roles by native small mammals as consumers/dispersers/propagators of native grassland plants.
Wavefront compensation for spatial light modulators based on Twyman-Green interferometry

Spatial light modulators (SLM) based on liquid crystal on silicon (LCOS) are widely used for phase-related applications. The inherent aberrations such as curvature and liquid crystal thickness variation that are caused by the fabrication process may need to be compensated. Measuring the pixel dependent phase response, by means of a Twyman-Green interferometer at 640 nm, enables high precision calculation of compensation functions, leading to a wavefront flatness in the order of λ/11 (peak-to-peak). In this work we present the performance of the measurement setup, the 2D phase response of multiple LCOS panels and the results of active compensation of major aberration effects.
RoBERTa-IAN for aspect-level sentiment analysis of product reviews

Accurately mining the emotional information contained in product reviews is of great significance to product sales. Existing research on sentiment analysis of product reviews often ignores the importance of modelling aspect words and context separately. Therefore, this paper proposes a sentiment analysis model for product reviews based on RoBERTa-IAN. Firstly, the context and aspect words of product reviews are transformed into low dimensional vectors through the RoBERTa pre-training model. Then, the low dimensional vector is used as the input of Bi-GRU model to extract semantic features and get the hidden representation. Finally, the attention matrices of context and aspect words are obtained by using the Interactive Attention Networks (IAN), which are used as the input of sentiment classification layer to analyse and classify the sentiment polarity of product reviews. The experimental results on the real commodity Chinese dataset show that the accuracy of RoBERTa-IAN has reached more than 90%.
Malicious Domain Name Detection Based on Doc2vec and Hybrid Network

In traditional malicious domain name detection algorithms, machine learning detection methods take a long time to extract features and the extraction methods are more complex; deep learning detection methods are easy to lose the semantic features of the entire domain name, and the detection results of a single neural network for different sample data sets are unstable . In response to the above problems, a malicious domain name detection method based on Doc2vec and hybrid network was proposed, and a new DLR (Doc2vec-LSTM-RNN) detection model was constructed. The word vector is constructed using the Doc2vec algorithm optimized on the basis of the Word2vec algorithm, which retains the semantic information of the domain name as a whole; and mixes the bidirectional LSTM network and the bidirectional RNN network in series to carry out deep-level feature extraction and enhance the robustness of the detection model; finally the Softmax function is used to output the classification result. Experimental data shows that this method has excellent performance in malicious domain name detection. Compared with traditional machine learning and deep learning detection methods, it has higher detection accuracy.
Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm

This work presents an alternative to the conventional photovoltaic maximum power point tracking (MPPT) methods, by using an opposition-based learning firefly algorithm (OFA) that improves the performance of the Photovoltaic (PV) system both in the uniform irradiance changes and in partial shading conditions. The firefly algorithm is based on fireflies’ search for food, according to which individuals emit progressively more intense glows as they approach the objective, attracting the other fireflies. Therefore, the simulation of this behavior can be conducted by solving the objective function that is directly proportional to the distance from the desired result. To implement this algorithm in case of partial shading conditions, it was necessary to adjust the Firefly Algorithm (FA) parameters to fit the MPPT application. These parameters have been extensively tested, converging satisfactorily and guaranteeing to extract the global maximum power point (GMPP) in the cases of normal and partial shading conditions analyzed. The precise adjustment of the coefficients was made possible by visualizing the movement of the particles during the convergence process, while opposition-based learning (OBL) was used with FA to accelerate the convergence process by allowing the particle to move in the opposite direction. The proposed algorithm was simulated in the closest possible way to authentic operating conditions, and variable irradiance and partial shading conditions were implemented experimentally for a 60 [W] PV system. A two-stage PV grid-connected system was designed and deployed to validate the proposed algorithm. In addition, a comparison between the performance of the Perturbation and Observation (P&O) method and the proposed method was carried out to prove the effectiveness of this method over the conventional methods in tracking the GMPP.
Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model

Remote sensing data of canopy cover and leaf area index are used together with the AquaCrop model to optimize irrigation water use efficiency for tomato and maize fields across Italy, which differ in climate, soil types and irrigation technique. An optimization irrigation strategy, “SIM strategy”, is developed based on crop stress thresholds and then applied to all the analyzed fields in different crop seasons, evaluating the effect not only on irrigation volume and number of irrigations but also on crop yield and canopy cover, and on the drainage flux which represents the main water loss. Irrigation volume reduction is found to be between 200 and 1000 mm, mainly depending on the different soil types within the climate, irrigation technique and crop type. This is directly related to the drainage flux reduction which is of a similar entity. The SIM strategy efficiency has then been quantified by different indicators, such as the irrigation water use efficiency (IWUE) which is higher than with the observed irrigations (around 35% for tomato fields in Southern Italy, between 30 and 80% for maize in Northern Italy), and the percolation deficit and irrigation efficiency. The AquaCrop model has been previously calibrated against canopy cover and leaf area index (LAI) data, producing errors between 0.7 and 5%, while absolute mean errors (MAE) between 0.015 and 0.04 are obtained for soil moisture (SM). The validation of the AquaCrop model has been performed against evapotranspiration (ET) ground-measured data and crop yields producing MAE values ranging from 0.3 to 0.9 mm/day, and 0.9 ton/ha for maize and 10 ton/ha for tomatoes, respectively.