Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Attention on Sentence Snippets Incongruity for Humor Assessment

Researches on humor identification can advocate a better understanding of human language. Many studies focused on the categorical classification problem of humor, which is less sensible to the intermediate level funny content. Previous work captured the incongruity between words but not sentence snippets. In this paper, a novel method is proposed to exploit snippet-level incongruity features from different aspects, combined with the sentence snippets representations to predict funniness scores. The experiment result shows that this model outperforms most of the competitive methods.
Motivators and Barriers for Buying Intention of Upcycled Fashion Products in China

This study examines determinants of the consumption behavior of upcycled fashion products in China. Theoretical and empirical evidence from the upcycled fashion consumption and related literature are used to develop a model to explain consumers’ buying intention toward upcycled fashion products. Environmental consciousness, consumer knowledge of upcycled fashion fabrics, and perceived risks of upcycled fashion products are proposed as key factors (i.e., motivators and barriers) of behavioral intention toward the purchase upcycled fashion products. Hypothesized antecedents of buying intentions toward upcycled fashion are included in the theoretical model, which was tested using structural equation modeling analysis on data from a sample of 397 consumers in China. Environmental consciousness encompassed two factors and was therefore divided into environmental concerns and importance of environmentally conscious behavior. Perceived risks at the time of purchasing upcycled fashion products showed three factors: social, financial, and performance risk perceptions. After examining the impact of environmental consciousness and perceived risks on purchase intention toward upcycled fashion products, this study found that both factors had statistically significant effects on purchase intention. In addition, the study revealed that knowledge of upcycled fashion materials was mediated in the relationship to explain the impacts of Chinese consumers’ perceived importance of conscious behavior and perceived risks of upcycled fashion products on their intention to purchase upcycled fashion products. In other words, to increase the purchase intention toward upcycled fashion products, it is necessary to raise Chinese consumers’ environmental knowledge of upcycled fashion materials, while improving the importance of conscious behaviors and reducing the perceived risk. The implications of the findings for public policy and as guidelines for future research are outlined and discussed.
Neural networks‐based sliding mode tracking control for the four wheel‐legged robot under uncertain interaction

When considering the accuracy of tracking control, physical interaction such as structural uncertainties and external dynamics is the main challenge in actual engineering scenarios, especially for the complex robot system. In this article, a neural network‐based sliding mode tracking control scheme (SMCR) is presented for the developed four wheel‐legged robot (BIT‐NAZA) under the uncertain interaction. First, a non‐singular fast terminal function based on the kinematic model is proposed for path tracking, which improves the motion quality during the approach movement and the sliding mode movement. At the same time, it can reduce the influence of uncertain disturbances on the premise of ensuring the path tracking control accuracy via neural networks. Finally, some demonstrations using the autonomous platform of the BIT‐NAZA robot are employed to evaluate the robustness and effectiveness of the hybrid algorithm.
Point cloud segmentation based on Euclidean clustering and multi-plane extraction in rugged field

In this paper, a novel method for point cloud segmentation based on Euclidean clustering and multi-plane extraction is proposed. To cope with overhanging objects, such as tree branches, a hybrid elevation map assisted by Euclidean clustering is designed. By clustering the 3D point clouds falling into the grid cell, the obstacles above a free space are checked and the corresponding traversable regions below are identified. Furthermore, the time consumption is reduced for segmentation by using the multi-resolution grid method. In addition, the multi-plane extraction method based on random sample consensus is well adapted to non-flat terrain. In the simulation, a variety of virtual environments are built on the Gazebo platform to demonstrate the performance of the proposed algorithm. Moreover, it is also evaluated in outdoor environments. The results show that the accuracy as well as efficiency of point cloud segmentation achieves superior performance over existing approaches.
Employer Engagement and Active Labour Market Policies. Evidence from a Norwegian Multi-Method Study

Using Work Training in Norway as a case, this article provides insight into motivation and structural factors that impact employer engagement with active labour market policies (ALMP) targeting young people. Drawing on mixed-methods data, we find a substantial proportion of Norwegian employers engage in Work Training. Both social responsibility and the economic interests of the company influence employers’ motivation for committing to Work Training. The findings reveal that the structural factors of business size and sector are crucial determinants of employer behaviour when it comes to hiring Work Training candidates. Although improved outreach activities by local job centres may be important, the article argues that efforts towards opening up sectors closed by sector-specific regulations on hiring, and increased awareness of structural constraints, are similarly important.
Extending tracking range through structured back focal plane interferometry

vBack Focal Plane interferometry (BFPI) is a widely used technique in particle tracking, providing high-speed, highresolution measurements. We present Structured Back Focal Plane Interferometry (SBFPI), a modification to BFPI utilizing structured beams and structured detectors [1]. Utilising Conical Wavefront Gaussian Beams and Annular Quadrant Photodetectors, SBFPI significantly increases tracking range while maintaining sensitivity and robustness to aberrations. We studied the variation in detection range and sensitivity over our parameters. A maximum increase in axial and lateral tracking range of 4.25-fold and 1.83-fold was found respectively, concomitant with sensitivity decreases of 53% and 61%. We also found parameter combinations with smaller range improvements but which retain sensitivity, in particular a 2.31 fold axial range increase with a 22.4% reduction in sensitivity, and these can be tuned to each experiment. We also studied the effect of aberrations on signal integrity.
Designing the Participation on Local Development Planning: From Literature Review to Adaptive Framework for Practice

This exploratory review of the literature provides a comprehensive overview of the settings that are available to the planner when managing participatory strategic planning of spatial socio-economic development on the local level. We contextualize individual potential configurations of participation in local development planning practice, documented in a number of case studies from different parts of the world, in order to reflect the multidimensionality of the participatory planning process. These reflections are used to build a participation plan model, which aimed to help local planners, especially local governments, to optimize the participation of local stakeholders, according to the specifics of the local environment. The paper evaluates the options of planners to manage the participation from perspective of the organization of participation, the determination of its scope, selection of stakeholders, methods and techniques of communication, decision-making and visualization, as well as the deployment of resources, or the possibility of promotion and dissemination of information. As a practical implication of this review, we compose a participation matrix, which is intended to be an auxiliary tool for planners to establish own locally-specific participation plans and that can serve as tool for education, or life-long learning of planners.
Development of wolfram mathematica application-assisted learning module on derivative in high school

One of the benefits of studying derivatives is determining the best way to solve a problem. The available textbooks seem monotonous and do not allow students to understand the derivative concepts presented actively. This study aims to develop teaching materials in learning modules in the Function Derivative material assisted Wolfram Mathematica application using the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). Data obtained from experts and students were analyzed using descriptive quantitative. Experts assess that the learning module made through the ADDIE stage is very eligible for students. Students also assess that the module is very suitable for use. This research and development still require a further assessment at the evaluation stage with summative types to obtain a maximum final product.
Professional liability insurance contracts for auditors: differential pricing and the audit quality effect

ABSTRACT In recent years, the Chinese government and the public accounting profession have advocated the audit practitioners’ use of professional liability insurance (PLI). As a tool to divert audit firms’ business risk, PLI contracts could decrease auditors’ diligence in conducting audits, which might harm audit quality. Insurance companies might perceive the transfer of audit risks, thus having an incentive to monitor risky audit firms to mitigate potential economic losses related to audit failures. We use proprietary PLI contract data and find that insurance companies charge smaller audit firms a significantly higher price and show a lower tendency to offer favourable indemnity clauses. The difference-in-differences analysis reveals that the magnitude of audit adjustments significantly increases after small audit firms purchase PLI and the effect is dominated by income-decreasing audit adjustments. Our evidence supports the notion that insurance contracts play a governance role for audit intermediaries with a higher risk profile.
Empirical Study on the Impact of Evaluation of Intangible Assets on the Market Value of the Listed Companies

The accelerated pace of economic development, the digital revolution and the internationalization of business has meant for some entities the creation or acquisition of intangible assets (IA), which have become increasingly important for the economic prosperity and for determining the global value of a company, also becoming an important incentive in creating added value. The aim of this paper is focused on analyzing the impact of internally generated intangible assets on the market value of the companies. In order to achieve this aim, we conducted an empirical study involving a sample of 180 NASDAQ and NYSE listed entities between 2007 and 2016. The sample has obtained by applying the inclusion and exclusion criteria on the 500 large-capitalization companies (S&P 500 Index). Making use of regressive techniques, the authors undertook an econometrical model to test whether the impact of intangible assets on the market value of the entities increases when are provided complete, clear and easy-to-understand accounting information about the intangible assets value, which aid business to properly estimate corporate value ratio and reduce implicit bias, due to mainly taking into account those reported values when measuring an entity’s value. The results revealed an impact of the value of the reported and unreported IA on the market value of the entities, for manufacturing companies relative to service companies, which generates an added value on the capital market and implicates a close linkage of disclosure compliance and the associated industry sector. The proposed model can be an inspiration for the legislator to change the structure of financial reporting, or anticipated a valuable informational source for increasing the quality of integrated reporting of economic entities.
Uncovering information diffusion patterns in different networks using the L-metric

ABSTRACT Information diffusion is an important branch of online social network analysis. In this paper, we construct a new metric, the proportion of leaf nodes in a diffusion tree (L-metric), to quantify information diffusion patterns, and we study the impact of the network category and information content on these patterns. Simulation-based experimental studies of real-world social networks show that information diffusion exhibits different patterns in different networks, and niche information does not typically propagate easily in any type of network. These conclusions provide a new perspective for further research on management decisions with regard to online social networks.
Mirau-type full-field optical coherence tomography

Dynamic-focusing optical coherence tomography (OCT) can provide ~1-μm isotropic resolution in extended depth of field, and Mirau design is preferred because of lower weight. In previous works, we reported a Mirau-type OCT based on high-radiance spatially-incoherent source. However, the illumination intensity is limited by the etendue. Besides, coherent artifacts increases with the partially coherent illumination scheme. In this report, we introduce a method to narrow illumination linewidth to 5 μm and reduce coherence area to 1 μm2. With spatially incoherent illumination, optimized throughput and low-weight design, low-speckle B-scan can be acquired within 0.25 second.
A Project Tracking Tool for Scrum Projects with Machine Learning Support for Cost Estimation

Cost estimation in software development is very important because it not only gives an idea to all stakeholders on how long it takes to complete the product under development, but it also mandates tracking development activities so that the project does not overrun on time or budget. Several cost estimation models have been reported in the literature for software development using traditional life cycle models but there are only a few ad hoc methods for software projects that used agile methods. This paper describes the design and implementation of a project tracking tool for software projects that are developed using the agile method Scrum. The users of the tool can closely monitor the progress of user stories, sprint tasks and test cases inducted into a scrum board. The tool also supports cost estimation of the project based on user stories and sprint tasks. For every user story, the tool provides a measure of hardship to implement in terms of story points, and for every sprint task, it gives the anticipated completion time. The tool uses machine learning support for continuous monitoring of eﬀorts based on sprint tasks. The eﬀectiveness of the tool has been tested using three diﬀerent graduate course projects.
Knowledge models from PDF textbooks

ABSTRACT Textbooks are educational documents created, structured and formatted by domain experts with the primary purpose to explain the knowledge in the domain to a novice. Authors use their understanding of the domain when structuring and formatting the content of a textbook to facilitate this explanation. As a result, the formatting and structural elements of textbooks carry the elements of domain knowledge implicitly encoded by their authors. Our paper presents an extensible approach towards automated extraction of knowledge models from textbooks and enrichment of their content with additional links (both internal and external). The textbooks themselves essentially become hypertext documents where individual pages are annotated with important concepts in the domain. The evaluation experiments examine several aspects and stages of the approach, including the accuracy of model extraction, the pragmatic quality of extracted models using one of their possible applications— semantic linking of textbooks in the same domain, the accuracy of linking models to external knowledge sources and the effect of integration of multiple textbooks from the same domain. The results indicate high accuracy of model extraction on symbolic, syntactic and structural levels across textbooks and domains, and demonstrate the added value of the extracted models on the semantic level.
Organisational justice and psychological contract, Discovering role of motivation within

Empirical evidences suggest that Psychological contract fulfillment at an organisation has symbiotic benefits for employer and employee. The current study investigates if Organisation Justice is a predictor of Psychological Contract and further if motivation has a mediating role to play in it. With a sample of 144 employees of North India, evaluated on Organisational Justice Scale (Colquitt, 2001), Psychological Contract Inventory (Rousseau, 2000) and Work Motivation Questionnaire (Agarwal, 1990), the study found that Organisational Justice is a predictor of Psychological Contract, with work motivation being a mediator. The sample showed a high positive correlation between psychological contract and perceived obligation fulfillment of both employer and employee.
Diffuse reflectance spectroscopy based blood oxygenation monitoring: a prospective study for early diagnosis of diabetic foot

Diabetic foot is a serious chronic complication of diabetes mellitus affecting 15 % diabetic patients during their lifetime. Approximately 85 % lower-limb amputations are preceded by an untreated diabetic foot. Several techniques are available to diagnose foot ulceration by monitoring average blood oxygenation state of the diabetic foot. However, these techniques couldn’t resolve relative local blood volume fraction of reduced/-oxyhemoglobin within the bulk of highly scattering tissue media. Therefore, the aim of this study is to extract localized blood volume fraction of reduced/- oxyhemoglobin from vascular beds of human foot. In this study, we investigated the ability of diffuse reflectance spectroscopy to quantitatively measure localized blood volume fraction of reduced hemoglobin (RHb), oxyhemoglobin (HbO2), and oxygen saturation (SO2) from various sites of the human foot sole. The preliminary investigation shows that the proposed approach can reliably determine the local volume fractions of RHb, HbO2 and SO2 in four different sites namely great toe, ball of great joint, 5th metatarsal, and calcaneum of the human foot sole. In addition, it also concludes that each part of the foot has different levels of blood volume fraction. Thus, the preliminary results suggest that this method may be used as a diagnostic tool for monitoring blood oxygenation parameters of ulcerated diabetic foot. It may help in to reduce the health-care cost and improve the quality of life of diabetic patient.
Litsea martabanica (Kurz) Hook. f. (Lauraceae): A New Addition to the Flora of Vietnam

Vietnam National Museum of Nature (VNMN), Vietnam Academy of Science and Technology, No.18, Hoang Quoc Viet Road, Cau Giay District, Ha Noi City, Vietnam. ngocanh@vnmn.vast. vn (author for correspomdence); Graduate University of Science and Technology (GUST), Vietnam Academy of Science and Technology, No.18, Hoang Quoc Viet Road, Cau Giay District, Ha Noi City, Vietnam; Institue of Ecology and Biological Resources (IEBR), Vietnam Academy of Science and Technology, No.18, Hoang Quoc Viet Road, Cau Giay District, Ha Noi City, Vietnam. Central Botanical Garden of the National Academy of Sciences of Belarus, Surganova Street 2v, Minsk 220012, Belarus
Weibo Text Classification Based on Knowledge Graph

As a platform for sharing and communication, Weibo can produce a large amount of short text data every day. Because the Weibo text is short and the text features are sparse, it contains less information, serious colloquialization and weak anti-noise ability, so it is difficult to achieve the desired results by using the traditional text classification method to classify Weibo text. This paper proposes a Weibo text classification method based on knowledge graph, which uses knowledge graph to expand text semantics and enrich text features on the basis of the original Weibo text. Then the TextCNN model is used to classify Weibo texts with extended semantics. The experimental results show that the classification accuracy of this method is better than that of Weibo text classification directly.
Chemische und elektrochemische Methoden zur Oberflächenbearbeitung von galvanogeformten Nickel-Mikrostrukturen

Im Rahmen dieser Arbeit wurden drei verschiedene (elektro-) chemische Verfahren sowie die Verfahrenskombination Lappen und Elektropolieren zur Oberflachenbearbeitung von LIGA-Nickel-Mikrostrukturen in Hinblick auf die Verringerung der Rauheiten und die Reduzierung der Schichtdickeninhomogenitat untersucht. Des Weiteren wurde auf die Problematik der Rauheitsmessung der in ihrer Messlange begrenzten Mikrostrukturen eingegangen und eine Losung mittels der spektralen Leistungsdichte erarbeitet.
Uniform performance of mammal detection methods under contrasting environmental conditions in Mediterranean landscapes

Monitoring local occupancy and the regional distribution of wild mammals is essential to guide species management and set conservation priorities. However, variables such as weather, substrate hardness, or habitat characteristics may indirectly affect the performance of the methods employed for monitoring mammal occurrence. Little information exists about the in ﬂ uence of spatio-temporal factors on the performance of survey methods and its implications for mammal monitoring. Using data from a heterogeneous region in the Guadiamar River basin, SW Spain, which encompass forest, agricultural, and mosaic landscapes, we (1) explore whether four widely used detection methods, namely camera traps, scent stations, track surveys, and scat surveys, differ in ef ﬁ ciency; (2) test the hypothesis that spatio-tempo-ral factors do not affect method ef ﬁ ciency; and (3) examine the effect of landscape on the replication effort needed to detect target species. After controlling for variation in mammal occurrence across space and over time, the interaction between spatio-temporal factors and detection methods was not signi ﬁ cant. Likewise, we found a negligible in ﬂ uence of landscape type on the replication effort needed to detect species actually present. When compared to camera traps, scent stations, and scat surveys, track surveys were the most ef ﬁ cient and fastest methodology for surveying mammals in our study landscapes. Monitoring programs of mammal occurrence are often applied to broad and heterogeneous regions and/or during extended periods. Therefore, survey methods should describe not only spatio-temporal variation in mammal abundance or activity but also maintain high detection ef ﬁ ciency in a variety of environmental conditions. The detection ef ﬁ ciency of each survey method changed little regardless of considerable environmental variation, making more reliable the marked differences between methods in their ability to detect target species. We recommend accounting for the effect of spatio-temporal factors as potential sources of variation in order to test whether our results can be generalized and to increase the quality of large-scale monitoring of mammal occurrence.