Miracle-dz/UniFAR-FTUs huggingface dataset:
The Potentials of Machine Learning and Big Data in Entrepreneurship Research-The Liaison of Econometrics and Data Science

While the potential data landscape in econometric research is undergoing dramatic changes, terminologies such as ? Big Data? and the associated discipline of ? Data Science? and ? Machine Learning? techniques have so far received little attention among econometricians. In this chapter, we illustrate the potentials for quantitative entrepreneurship research to benefit from the availability unprecedentedly rich datasets and non-traditional data sources such as text, audio, or image data. However, we also highlight that such datasets are in need of new approaches. Both computational and epistemological. We proceed with introducing the Data Science approach to quantitative analysis which is geared towards optimizing the predictive performance, contrast it with standard practices in econometrics which focus on producing good parameter estimates. This chapter also introduces to machine learning techniques such as out of out-of-sample model verification, variable selection, and generalization procedures, and finally the popular model classes of regression trees, artificial neural networks, and vector space models. We provide guidance on how to apply these techniques for quantitative research in entrepreneurship and point towards promising avenues of future research which could be enabled by the use of new data sources and estimation techniques. The Potentials of Machine Learning and Big Data in Entrepreneurship Research∗ – The Liaison of Econometrics and Data Science –
The Relevance of Accounting Information in the Process of Valuation of Companies in the New and Old Economy – An Analysis of Asset Investments and their Effects on the Value Relevance of Earnings and Book Value

Brazilian accounting principles permit companies to capitalize expenditures on research and development, specifically as deferred charges. Therefore, the objective of this article is to analyze the effects of (deferred) investments on the value-relevance of the earnings and net equity of companies operating in the so-called new and old economies, with the sectors of the old economy chosen as comparison. The more specific objective is to examine: (i) the explanatory power of earnings and net equity; (ii) the incremental explanatory power of deferred charges, in which the stock price is a function the net earnings plus net equity less deferred charges. This study does not seek to refute or prove a specific model, but rather only to gather evidence to permit accepting or rejecting the hypotheses formulated and to offer a response to the research question. The results show that accounting information, for both sectors, is relevant to value the price of shares. However, the results on the explanatory power of deferred charges run counter to the expected results.
Corporate Political Connections and Innovation : An Attention-Based View Perspective

This study adopts an attention-based view to analyze the role of political connections in corporate innovation. Prior studies have shown that political connections enhance firm performance through access to resources, but less attention has been paid to the costs of maintaining such connections. Drawing upon an attention-based view of firms, this study argues that building political connections divert CEOs’ attention from corporate innovation activities. This work exploits one regulatory change associated with a reduction in political connections in Chinese publicly listed firms in 2013. Using a sample of Chinese listed firms from 2008 to 2016, I employ a propensity score matching and a difference-in-differences research designs and finds that firms have higher innovation outputs subsequent to this regulatory shock (i.e. reduced political connections). This work provides a novel perspective on political connections and innovation.
A feasibility study of template-based subject-specific modelling and simulation of upper-airway complex

The upper-airway complex is involved in a number of life-sustaining functions, such as swallowing, speech, breathing and chewing. Disorders associated with these functions can dramatically reduce the life quality of the suffers. Biomechanical modelling is a useful tool that can bridge the gap between the human knowledge and medical data. When tailored to individual patients, biomechanical models can augment the imaging data, to enable computer-assisted diagnosis and treatment planning. This thesis introduces a model-registration framework for creating subjectspecific models of the upper-airway complex based on 3D medical images. Our framework adapts a state-of-art comprehensive biomechanical model of head and neck, which represents the generic upper-airway anatomy and function. By morphing this functional template to subject-specific data, we create upper-airway models for particular individuals. In order to preserve the functionality of the comprehensive model, we introduce a multi-structure registration technique, which can maintain the spatial relationship between the template components, and preserve the regularity of the underlying mesh structures. The functional information, such as the muscle attachment positions, joint positions and biomechanical properties, is updated to stay relevant to the subject-specific model geometry. We demonstrate the functionality of our subject-specific models in the biomechanical simulations. Two illustrative case studies are presented. First, we apply our modelling methods to simulating the normal swallowing motion of a particular subject based on the kinematics (of the airway boundary, jaw and hyoid) extracted from dynamic 3D CT images. The results suggest that our model tracks the oropharyngeal motion well, but has limited ability to reproduce the hyolaryngeal movements of normal swallowing. Second, we create two speaker-specific models based on 3D MR images, and perform personalized speech simulations of the utterance /@-gis/. The models reproduce the speech motion of the tongue and jaw recorded in tagged and cine MRI data with sub-voxel tracking error, predict the muscular coordinating patterns of the speech motion. This study demonstrates the feasibility of using template-based subject-
Detection of phytochemicals and in vitro propagation of Banana (Musa variety Gaja Bantal)

The present experiments were conducted to evaluate the phytochemicals present in the sap and stem samples of a Musa variety, Gaja Bantal. Attempts has also taken to study various effects of plant hormones such as cytokinin (BAP) and auxins (IAA and NAA) on shoot proliferation and root induction during its in vitro micropropagation. Results from various experiments showed that the sap as well as stem extraction contain high phenolic and flavonoid content. Due to heavy phenolic content lethal browning of explants was observed during different stages of in vitro propagation Gaja Bantal. While both the samples (Sap and Stem) contain alkaloids, Saponin was slightly detected only in the stem sample. During micropropagation of Gaja Bantal it was observed that media containing high concentration of BAP (8 mg/l) had better respond in initial culture while low concentration of BAP (3 mg/l) had high bud formation in multiplication stage. Gaja Bantal explants grown on multiplication medium supplied with 3 mg/l BAP + 0.5 mg/l IAA had highest numbers of shoot buds. In rooting culture the media containing 1 mg/l IAA as well as media containing 1 mg/l NAA found to be more effective in root induction.
A MultiView Texture Fusion Approach for High Quality 3 D Face Modelling

This paper presents an accurate means for the 3D face texture mapping based on a multiple-view 3D scanning system. Given a reconstructed 3D mesh model and a set of calibrated images, a high-quality texture mosaic of the surface can be created by the proposed method. The proposed method aims to avoid noticeable seams, color discontinuity and ghosting problems. The method performs in two steps, i.e. occlusion areas filtering and the fusion of different texture images. The filtering is performed to identity invisible areas from the camera viewpoint and leaves them not textured. To perform the occluded areas filtering, we combine the geometrical features of the objects and the visual range of the camera. Experimental results showed that, texture mapping quality and precision can be improved in comparison with conventional means. Introduction 3D reconstruction is an important research topic in both computer vision and computer graphics domains. It is a technology to study how to obtain the three-dimensional information of objects in real world via the passive or active optical means. 3D shape reconstruction and texture reconstruction from photographs are the two major aspects in the modeling of real objects. There have been a lot of techniques which can generate image-based 3D models with high accuracy [1]. However, existing texture mapping methods are usually lack of precision, especially for the texture images captured with various viewpoints or the change of lighting conditions [2]. In the past decades, many sophisticated texture generation approaches have been proposed. Early works have focused on different weighting heuristics to average overlapping textures. According to the weighting function, these approaches can be generally categorized as Weighted Blending [3], Multi-Band Blending [4] and Super-Resolution Maps [5] methods. Underlying principle of these methods is to attach a color attribute to each vertex. Then blend the color intensities from multiple views by calculating the weights of all visible views for each vertex. Some other methods generate a texture map by collecting all texture patches together. The combination of texture patches has much in common with the stitching and texture synthesis of planar images. Graph cut optimization and gradient-domain techniques [6] are often used to improve the performance over intensity blending. Instead of blending the color intensities from multiple views, some methods introduced Markov Random Field (MRF) [7] into texture patch registration to optimize the texture alignment, which considers both image visibility and color continuity, and computes the texture of each facet from only one viewpoint. After the texture patch registration, the Poisson fusion [8] approach to deal with the chromatic aberration between the sides of the patch joint. These methods have achieved good results in texture fusion objects described in their respective papers. But there are still some problems like
Experimental Verification of Nonlinear Position-Flux Zero-Bias Control for Heteropolar Active Magnetic Bearing

─ This study presents experimental verification of a nonlinear position-flux control for active magnetic bearing (AMB) system operated with zero-bias flux. Recently developed controllers for nonlinear fluxcontrolled AMB applications are complicated and inherently difficult to implement. Therefore, three designs of low-order controllers are proposed using nonlinear feedback tools including Lyapunov-based techniques and control Lyapunov functions (CLFs). The control objective is to globally stabilize the rotor mass position in the AMB system. Responses of the AMB system states to initial condition and to external load disturbance are presented and the simulation and experimental results for transient responses are compared. The overshoots are compensated for the zero neighbourhood, and the rotor position amplitude does not exceed 2.5% of the air gap. Index Terms ─ Active magnetic bearing, control Lyapunov function, nonlinear flux controller, zero-bias
MEAT QUALITY CHARACTERISTICS OF BLESBOK (Damaliscus dorcas phillipsi) AND RED HARTEBEEST (Alcelaphus buselaphus caama) MEAT

The aim of this study was to determine the effect of the sex, age and region on the morphological characteristics of blesbok. A total of73 blesbok, from both sexes, and from different age groups (adult, sub-adult and lamb) and different regions (Qua-Qua (QQ), Maria Moroka (MM), Rustfontein (RF) and Gariep (OR) in the Free State Province, South A frica) were measured. Within sex, the males had the highest values for all the characteristics, except for leg length. The male animals (67.38 kg) were significantly heavier than the females (60.19 kg). All carcass measurements (body weight, carcass weight, carcass length, carcass breadth, carcass depth, buttock circumference, chest girth and leg length) increased linearly with age. The sub-adults had the highest dressout percentage (54.31 %) and blesbok from RF (50.57%) the lowest. Regarding region, blesbok from QQ had the highest values for all the characteristics, except for carcass length and leg length.
! 1 ! Nitrogen and phosphorus recycling mediated by copepods and response of bacterioplankton community from three contrasting areas in the Western Tropical South Pacific ( 20 o S )

Valentina Valdés, François Carlotti, Ruben Escribano , Katty Donoso, Marc Pagano, Veronica Molina and Camila Fernandez 7, 8 Programa de Doctorado en Oceanografía, Departamento de Oceanografía, Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción, Concepción, Chile. UPMC Univ Paris 06, UMR 7621, Laboratoire d’Océanographie Microbienne, Observatoire Océanologique, Sorbonne Universités, Banyuls sur Mer F-66650, France. Aix-Marseille Univ, Universite de Toulon, CNRS, IRD, OSU PYTHEAS, Mediterranean Institute of Oceanography MIO, UM 110, 13288, Marseille, Cedex 09, France. Departamento de Oceanografía, Universidad de Concepción, Concepción, Chile. Instituto Milenio de Oceanografía, Universidad de Concepción, Concepción, Chile. Departamento de Biología and Programa de Biodiversidad, Facultad de Ciencias Naturales y Exactas, Universidad de Playa Ancha, Playa Ancha, Valparaíso, Chile. FONDAP INCAR center (15110027), and PFB-31 COPAS Sur Austral program; Departamento de Oceanografía, Universidad de Concepción, Concepción, Chile. Centro FONDAP de Investigación en Dinámica de Ecosistemas Marinos de Altas Latitudes (IDEAL), Valdivia, Chile.
Interactive comment on “ Estimation of phytoplankton pigments from ocean-color satellite observations in the Sénégalo-Mauritanian region by using an advanced neural classifier ” by Khalil Yala et al

2-3-4-5 Pigments allow to estimate phytoplankton groups but not phytoplankton species. We withdrew this statement in the text. Lines -53-60 we rewrote this section: An alternative method is the analysis of seawater samples by high-performance liquid chromatography (HPLC) which is widely used to categorize broad phytoplankton groups such as PFT or PSC (Jeffreys et al, 1997, Brewin et al, 2010, Hirata et al, 2011). HPLC enables identification of 25 to 50 pigments within a single analysis, which is much easier and faster to conduct than microscopic observations. Each phytoplankton group is associated with specific diagnostic pigments and a conversion formula can be derived to estimate the percentage of each group from the pigment measurements (Vidussi et al, 2001; Uitz et al, 2010). HPLC measurements are now recognized as the standard for calibrating and validating satellite-derived chlorophyll-a concentration and for mapping groups of phytoplankton (Sosik et al, IOCCG report n◦15, 2014).
Exploiting Non-Uniformities in Redundant Traffic Elimination

Protocol-independent redundant traffic elimination (RTE) at the network layer is a method of detecting and removing redundant chunks of data from data packets using caching at both ends of a network link or path. In this paper, we propose a set of techniques to improve the effectiveness of packet-level RTE. In particular, we consider two bypass techniques, with one based on packet size, and the other based on content type. Both bypass techniques are effective in reducing the processing requirements of RTE, with little or no adverse impact on redundancy detection. The bypass techniques apply at the front-end of the RTE pipeline. Within the RTE pipeline, we propose chunk overlap and oversampling as techniques that can improve redundancy detection, while obviating the storage and processing requirements associated with chunk expansion at the network endpoints as suggested by previous research. Finally, we propose savings-based cache management at the backend of the RTE pipeline, as an improvement to the commonly used FIFO-based cache management. We evaluate our techniques on full-payload packet-level traces from a university environment. Our results show that the 11-12% savings achieved with typical RTE can be improved to 16-18% with our techniques.
A promising route of magnetic based materials for removal of cadmium and methylene blue from waste water

Adsorption equilibrium is an essential measure to be controlled in attaining the maximum capacity of an adsorbent. Synthesis of magnetic biochar by using various discarded biomass possesses varied adsorbate adsorption capability. Maximising the removal percentage of the pollutant from wastewater by altering operational parameters are the very important skill to be mastered by environmentalist. In this research work, mangosteen peel derived ferric oxide magnetic biochar was pyrolysed at 800 C for 20 min via modified muffle furnace at zero oxygen environment. The factors affecting adsorption were studied for two different liquid pollutant. A comparative study was carried out for adsorption of methylene blue dye and Cd (II) ions by altering the adsorbate pH, agitation speed, and contact time and particle diffusion mechanism were investigated respectively. The removal of methylene blue dye attained maximum removal at pH of 7.0 and above, 50 min contact time and 150 rpm agitation speed. Moreover, adsorption equilibrium of Cd (II) ions reaches maximum removal percentage at the pH value of 8.0, agitation speed of 150 rpm and 60 min contact time. The thermodynamics study was performed to further understand the effect of operating temperature in determining the adsorption spontaneous of adsorption medium. The experimental analysis reveals that the produced magnetic biochar is viable for adsorption of both heavy metal ions and organic pollutant at optimised condition. © 2017 Elsevier Ltd. All rights reserved.
Selfie examinations : Applying computer vision , hashtag scraping and sentiment analysis to finding and interpreting selfies

In this preliminary investigation of selfies (self portraits in social media), we assess methods for identifying selfies and examine selfies as a form of emotional expression. We compare the accuracy of hashtags and computer vision in discriminating selfies form other images, using human ratings as a reference. Customized software was used to scrape (acquire from social media feeds) 2700 probable selfies and randomly select a sample of 100 images. To describe the emotional attributes of selfies we classified photos using customized sentiment analysis software and qualitatively examined photos. Although the majority of the selfies are upbeat, approximately 20% contain negative emotion words, with some reflecting isolation, disengagement and despair. Our examination shows promise for automatic detection of selfies using a blend of metadata, sentiment analysis and computer vision. The observation of selfies associated with despair and disengagement suggests opportunities to naturalistically assess and immediately address psychosocial needs. Author
Top-k Similarity Join Algorithm: An Indexing based approach

— There is a wide range of applications that require finding the top-k most similar pairs of records in a given database. However, computing such top-k similarity joins is a challenging problem today, as there is an increasing trend of applications that expect to deal with vast amounts of data. An algorithm, top k-join, is proposed to answer top-k similarity join efficiently. It is based on the prefix filtering principle and employs tight upper bounding of similarity values of unseen pairs. It also uses inverted indexes to find out candidates pairs i.e an indexed based approach. Experimental results demonstrate the efficiency of the proposed algorithm on large-scale real datasets.
Revisiting Absorptive Capacity : Literature review and a Practice-based Extension of the Concept Omid

This paper reviews the developed body of literature on absorptive capacity over the last two decades. It identifies and discusses the main research streams and argues that the tensions in the literature originate from overlooking the importance of ? meaning? in knowledge transfer and the dominance of variance models. Following from that, and building on the recent developments in literature, we argue that a practice-based extension of the concept, which embraces aspects of meaning, participation, identity transformations, and agency can complement the extant absorptive capacity research. It is, moreover, argued that when novelty increases, the practice-based approach can offer a stronger explanatory account of absorptive capacity compared with the existing conceptualiations.
2 3 A pr 2 01 7 Location Privacy in Spatial Crowdsourcing

Spatial crowdsourcing (SC) is a new platform that engages individuals in collecting and analyzing environmental, social and other spatiotemporal information. With SC, requesters outsource their spatiotemporal tasks (tasks associated with location and time) to a set of workers, who will perform the tasks by physically traveling to the tasks’ locations. However, current solutions require the workers, who in many cases are simply volunteering for a cause, to disclose their locations to untrustworthy entities. Revealing an individual’s location data to other entities may prevent people from contributing to SC applications, thus rendering location privacy a critical obstacle to the growth of SC applications. This chapter first identifies privacy threats toward both workers and requesters during the two main phases of spatial crowdsourcing, tasking and reporting. Tasking is the process of identifying which tasks should be assigned to which workers. This process is handled by a spatial crowdsourcing server (SC-server). The latter phase is reporting, in which workers travel to the tasks’ locations, complete the tasks and upload their reports to the SC-server. The challenge is to enable effective and efficient tasking as well as reporting in SC without disclosing the actual locations of workers (at least until they agree to perform a task) and the tasks themselves (at least to workers who are not assigned to those tasks). This chapter aims to provide an overview of the state-of-the-art in protecting users’ location privacy in spatial crowdsourcing. We provide a comparative study of a diverse set of solutions in terms of task publishing modes (push vs. pull), problem focuses (tasking and reporting), threats (server, requester and worker), and underlying technical approaches (from pseudonymity, cloaking, and perturbation to exchangebased and encryption-based techniques). The strengths and drawbacks of the techniques are highlighted, leading to a discussion of open problems and future work. Hien To University of Southern California, Los Angeles, CA 90089 e-mail: hto@usc.edu Cyrus Shahabi University of Southern California, Los Angeles, CA 90089 e-mail: shahabi@usc.edu