Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary factors affecting tissue profiles of long chain polyunsaturated fatty acids in cattle

The main goal of this dissertation was to evaluate different methods to protect polyunsaturated fatty acids (PUFA) against biohydrogenation by ruminal microorganisms. The first chapter is a review of literature pertaining to fat and fatty acid metabolism by ruminants and why these fats are relevant in human nutrition. The second chapter discusses effects of supplementing high concentrations of dietary copper to feedlot cattle to assess impact on PUFA profiles in tissues. Two levels of copper (10 or 100 mg/kg) were supplemented to diets with or without flaxseed during the finishing period for beef heifers. Added copper did not affect performance (P > 0.15). Final body weights were similar for cattle fed with or without flaxseed (P > 0.05), but cattle fed diets with flaxseed consumed less feed (P < 0.05), and therefore were more efficient (P < 0.01). Carcass traits were unaffected by treatment. Feeding elevated levels of copper did not appreciably alter proportions of PUFA in plasma, but plasma concentrations of omega-3 fatty acids were greater for heifers fed flaxseed (P < 0.05). Chapter 3 describes the evaluation of 3 novel methods to protect PUFA from microbial biohydrogenation activity within the rumen, including a) coextrusion of flaxseed with molasses; b) mixing with soybean meal followed by induction of a non-enzymatic browning reaction; and c) encapsulation of ground flaxseed within a matrix consisting of dolomitic lime hydrate (L-Flaxseed). The resulting products were evaluated using in vitro methods to estimate resistance to biohydrogenation or in 12to 14-d feeding studies in which plasma concentrations of α-linolenic acid (ALA) were measured. Our processing strategies a) and b) did not improve efficiency of omega-3 fatty acid utilization (P > 0.1). The in situ study of L-flaxseed revealed a 2-fold increase in resistance of ALA to ruminal biohydrogenation, and the concentration in plasma after 14 d on feed was more than 4 times that observed in cattle fed ground flaxseed, suggesting the dolomitic lime hydrate was effective as a protective matrix. Chapter 4 evaluated performance, carcass traits, and meat quality of finishing beef heifers in response to feeding diets containing L-Flaxseed. Animals were blocked by weight, randomly assigned to individual pens, and pens to 6 dietary treatments: Control (high concentrate finishing diet), ground flaxseed fed at 3 or 6% of diet DM, L-Flaxseed fed at 2, 4, or 6%. Concentration of ALA in meat increased linearly in response to the level of flaxseed fed (P < 0.05); Moreover, transfer of dietary ALA to tissues increased by 47% when flaxseed was encapsulated within the dolomitic lime matrix. Cattle that were fed diets with 4 or 6% L-Flaxseed consumed less feed than other treatments (P < 0.05), which adversely affected feedlot performance and carcass traits. DIETARY FACTORS AFFECTING TISSUE PROFILES OF LONG CHAIN POLYUNSATURATED FATTY ACIDS IN CATTLE
A Novel Secondary Power Management Strategy for Multiple AC Microgrids With Cluster-Oriented Two-Layer Cooperative Framework

Reducing time consumption of economical power allocation operation among multiple microgrid (MG) clusters can significantly enhance the balance efficiency between power supply and load demand. In this article, a novel secondary power management strategy with cluster-oriented two-layer cooperative (TLC) framework is proposed, by which both the power sharing requirement for all DGs within each MG cluster and the economical power allocation demand among multiple MG clusters can be simultaneously realized during the secondary control process. In the framework, all cluster-head distributed generators (DGs) constitute the upper control layer, which enable the economical power allocation operation among multiple MG clusters, and all noncluster-head DGs constitute the lower control layer allowing the power sharing adjustment within each MG cluster. All the power mismatches across the TLC framework are fed back in the primary control to generate the frequency/voltage nominal set-points. Sufficient conditions, in terms of control time constants of the TLC framework and connectivity of the two-layer cyber network, are derived to guarantee the stability of the entire multiple MG cluster system with both power balance and power generation constraints. Specially, both the lower and upper layer controllers are designed based on a sparse two-layer cyber network, allowing different numbers of heterogeneous DGs in each MG cluster. The effectiveness of the control methodology is verified by the simulation of a multiple ac MG cluster system in MATLAB/SimPowerSystems.
Cuantificación de Proteínas totales en extractos crudos de Cepas Nativas de Bacillus Thuringiensis Aisladas de Boyacá y Cundinamarca

The Cry proteins of Bacillus thuringiensis (Bt) produce parasporal crystal during sporulation which are toxic against insect larvae of lepidopteran, coleopteran and dipteran. In the present study, 10 native isolations of Bt strains were quantified from the Native Strains Bank of the Jorge Tadeo Lozano University, isolated from soil in the municipalities of Raquira, Santa Sofia, Villa de Leyva and Sutamarchan, in Boyaca; and also in Susa, Cundinamarca. Crude extracts of total proteins from the 10 strains incubated in Luria-Bertani medium (LB) for 15 days at 37 °C were obtained. For quantification of total protein of the spore crystal mixture was used the Bradford method using a standard pattern a calibration curve with bovine serum albumin (BSA). After 5 minutes, the determination was realized in the spectrophotometer at a wavelength of 595 nm. The brighter blue were presented by the strains ZBUJTL35 and ZBUJTL39, with a concentration of 560.71 and 526.43 mg / ml, respectively. The Bradford method is a simple and fast technique to estimate the protein concentration. The strains will be used to determine the toxicity over Bemisiatabaci larvae.
Loyola eCommons Loyola eCommons

With a growing number of services provided at or to a customer’s home, the familiarity of the service provider, or driver, with the customer’s location is increasingly important. One prominent example is retail distribution, where familiarity with the delivery location can save the driver time. In contrast to other kinds of familiarity (e.g., tasks, customer needs) that continually increase with a larger number of repetitions, location familiarity is primarily established with a driver’s ﬁrst visit. Thus, familiarity results from operational routing decisions. However, as we show in this paper, there is potential value in considering the tactical value of familiarity and its development over a longer horizon. To this end, we develop and solve a tactical model to specify the long-term implications of improved driver-customer familiarity, introducing a solution methodology for the stochastic and dynamic multi-period routing problem with driver-customer familiarity. Our methodology utilizes a policy that explicitly invests in the familiarity between selected driver-customer pairs, encouraging the development of pairs that are tactically beneﬁcial. We determine the appropriate investment dimensions for each pair, considering which locations a driver has visited and how many drivers have visited a location. We show that under the problem conditions tested this investment policy leads to a reduction in cost compared to a short term, myopic policy, while increasing the overall level of familiarity between drivers and customers and hedging against driver or customer turnover. We also ﬁnd that focusing only on routing or on exploiting existing familiarity leads to substantial increases in cost.
Acute Toxicity Studies and Anti-plasmodial Potentials of Newbouldia laevis and Crateva adansonii in Plasmodium Berghei-infected Mice

Article info: Received: 28 Dec 2019 Accepted: 29 Feb 2020 Online Published: 01 Apr 2020 Research Paper: Acute Toxicity Studies and Anti-plasmodial Potentials of Newbouldia laevis and Crateva adansonii in Plasmodium Berghei-infected Mice * Corresponding author: Stephen Damola Ariyeloye, MSc. Address: Department of Biochemistry, Institute of Health Sciences, Anadolu University, Eskisehir, Turkey. Tel: +23 (481) 68363402 E-mail: ariyeloye@gmail.com
Metal–organic chemical vapor deposition of 2D van der Waals materials—The challenges and the extensive future opportunities

The last decade has witnessed significant progress in two-dimensional van der Waals (2D vdW) materials research; however, a number of challenges remain for their practical applications. The most significant challenge for 2D vdW materials is the control of the early stages of nucleation and growth of the material on preferred surfaces to eventually create large grains with digital thickness controllability, which will enable their incorporation into high-performance electronic and optoelectronic devices. This Perspective discusses the technical challenges to be overcome in the metal–organic chemical vapor deposition (MOCVD) growth of 2D group 6 transition metal dichalcogenide (TMD) atomic crystals and their heterostructures, as well as future research aspects in vdW epitaxy for 2D TMDs via MOCVD. In addition, we encourage the traditional MOCVD community to apply their expertise in the field of “2D vdW materials,” which will continue to grow at an exponential rate.
Varying the Number of FOP Warnings on Hedonic and Utilitarian Food Products: Evidence from Chile

ABSTRACT FOP food-labeling systems seek to inform on a product`s healthy/unhealthy state and signal a product`s healthiness level. Research in this area has focused primarily on exploring the healthy/unhealthy dimension, leaving the effect of FOP schemes on the perception of healthiness under-researched. The objective of this study is to evaluate how an increase or decrease in the number of warning signs in the packaging of food products affects the healthiness perception of the consumer and the subsequent purchase intention. This examination is developed by comparing utilitarian and utilitarian food products as a means to examine whether FOP labeling effects are moderated by prior buying motivations. Results show that a different number of warnings is correctly perceived and used by consumers. Results also reveal that utilitarian products are more affected by the presence of one warning and in the case of these products these differences disappear when the number of warnings increases.
Detection of Protein Phosphorylation by Open-Sandwich Immunoassay

Understanding the post-translational modifications of proteins represents a next major challenge in post-genomic era. Intricate cascades of phosphorylation reactions regulate cell proliferation, differentiation, migration and so on. For example, Olsen et al recently applied high-resolution mass spectrometry-based proteomics to phosphoproteome of human cell cycle, quantifying 6,027 proteins and 20,443 unique phosphorylation sites [Olsen, 2010]. Phosphorylation-dependent signals participate in several diseases, such as cancers, immune diseases, and Alzheimer’s. The method to produce phosphorylation-site and phosphorylation state-specific antibodies was established in 1990’s [Nishizawa, 1991; Yano, 1991; Nagata, 2001; Goto, 2007] after a discovery of phosphorylated cytoskeletal proteinspecific antibodies [Sternberger, 1983]. Since then, investigators have successfully observed spatio-temporal dynamics of particular phosphorylation in vitro or in situ using the antibodies. Recently, these antibodies are also proven useful as a live cell imaging probe in vivo [Hayashi-Takanaka, 2009; Kimura, 2010; Hayashi-Takanaka, 2011], clinical diagnosis, and drug screening [Brumbaugh, 2011]. Here we show a couple of applications of phosphorylation-specific antibodies to proteomic studies, more specifically focusing on a novel immunoassay approach, which we call opensandwich immunoassay.
Retrospect and prospect of a section-based stratigraphic and palaeontological database – Geobiodiversity Database

Abstract. Big data are significant to the quantitative analysis and contribute to the data-driven scientific research and discoveries. Here the thorough introduction is given on the Geobiodiversity database (GBDB), a comprehensive stratigraphic and palaeontological database. The GBDB includes abundant geological records from China and contributes a serial of scientific studies on early Palaeozoic palaeogeography, tectonic and biodiversity evolution of China. Nevertheless, the existing problems of the GBDB limited the using of its data. The turnover and improvement of the GBDB were started in 2019. Besides the data collecting, processing and visualization as the GBDB did previously, the database and the website are optimized and re-designed, the new GBDB working team pays more attention to data analyzing with the professional artificial intelligence techniques. GBDB is complementary to other related databases and further collaborations are proposed to mutually benefit and push forward the quantitative research of palaeontology and stratigraphy in the era of big data. The persistent snapshot of the GBDB data can be found at: http://doi.org/10.5281/zenodo.3667645 (Xu, 2020).
Traits and Adaptations: A Theoretical Examination and New Empirical Evidence

We investigated the distinction between traits (also labelled basic tendencies or dispositions) and (characteristic) adaptations, two related features of the personality system postulated to influence how personality manifests throughout the lifespan. Traits are alleged to be universal, causal, and enduring entities that exist across cultures and through evolutionary time, whereas learned adaptations are acquired through sustained interaction with cultural, physical, and social environments. Although this distinction is central to several personality theories, they provide few measurable criteria to distinguish between traits and adaptations. Moreover, little research has endeavoured to operationalize it, let alone test it empirically. Drawing on insights from four frameworks—the Five–Factor Theory, Cybernetic Big Five Theory, Disposition–Adaptation–Environment Model, and New Big Five—we attempted to investigate the distinction both theoretically and empirically. Using various experimental rating conditions, we first scored 240 questionnaire items in their degrees of definitionally reflecting traits and/or adaptations. Next, we correlated these definitional ratings with the items’ estimates of rank–order stability, consensual validity, and heritability—criteria often associated with personality traits. We found some evidence that items rated as more trait–like and less adaptation–like correspond to higher cross–rater agreement and stability but not heritability. These associations survived controlling for items’ retest reliability, social desirability, and variance. The theoretical and empirical implications of these findings are discussed. © 2020 European Association of Personality Psychology
THE PURSUIT FOR NOVEL ACTIVATION FUNCTION

From the very start, activation functions in the neural network have been a key research area. More and more people are trying to come up with the state of the art activation functions for various purposes. These functions play an important role in deciding how good the model performs. Deep Learning allows us to create various complex learning models that are developed by algorithms capable of multi-level representation. It uses representation learning, which allows it to learn from the raw data and is capable of performing tasks like detection and classification. The functions play an important role in deciding the performance of a simple MLP to a very complex Deep Neural Networks. With the invention of every new activation function, we have seen a performance boost in various neural network architecture ranging from object detection to various Natural language applications too. The aim of the invented activation function is also focused on trying to further boost the performance of these Deep Neural networks, thereby providing a better user experience with increased performance in various Deep Learning-based applications.
Sticks and Stones: The Naming of Global Talent

In the workplace, demand for globally mobile workers continues to grow. This article examines the consequences for the individual of being named as global talent. Findings from a qualitative study within a large, multinational organisation, reveal the identity struggles these individuals engage in as they seek to reconcile the tensions inherent in such challenging careers. By combining and building on extant literature in naming, identity and global talent, the article offers a greater understanding of the lived experiences of global talent, as they construct and re-construct their identities in an on-going cycle. By drawing on the emerging field of socio-onomastics, a greater understanding of the meaning and connotations of being named as global talent is offered. By highlighting how names do not merely mirror identities, but are negotiated and resisted through a process of identity work, a contribution is made to the fields of identity studies and global talent management.
Designing Virtual Learning Media for a Vocational School

Developments in the areas of science and information technology affect the industrial and educational realms in Indonesia. Technological advances require teachers as educators to create innovative virtual learning media that can support students’ understanding either theoretically or practically. Considering the results of this observational study, it is confirmed that virtual learning has not been implemented widely in the Vocational School. Virtual learning media are an aid used to explain curriculum content that enables students to better understand the material either theoretically or practically. Virtual learning media have been incorporated into courses in personnel administration. This study explores whether virtual learning media improves students’ learning interest, motivation, and outcome.
Multi-Label Consistent Convolutional Transform Learning: Application to Non-Intrusive Load Monitoring

Convolutional transform learning is an unsupervised framework we introduced recently, for feature generation based on learnt convolutions. In this work, we propose a supervised formulation for convolutional transform so as to address the multi-label classification problem. Unlike the simple multiclass classification, in multi-label problems, each sample can correspond to multiple classes simultaneously, making the problem quite challenging. We propose to make use of a label consistency penalty and develop a suitable minimization algorithm for the training step. We illustrate the performance of the developed formulation on the practical problem of nonintrusive load monitoring. Comparisons with popular techniques show that our proposed approach yields better results on benchmark datasets.
Non-participatory user-centered design of accessible teacher-teleoperated robot and tablets for minimally verbal autistic children

Autistic children with limited language ability are an important but overlooked community. We develop a teacher-teleoperated robot and tablet system, as well as learning activities, to help teach facial emotions to minimally verbal autistic children. We then conduct user studies with 31 UK and Serbia minimally verbal autistic children to evaluate the system's accessibility. Results showed minimally verbal autistic children could use the tablet interface to control or respond to a humanoid robot and could understand the face learning activities. We found that a flexible and powerful wizard-of-oz tablet interface respected the needs of the children and their teachers. Our work suggests that a non-participatory, user-centered design process can create a robot and tablet system that is accessible to many autistic children.
Physical Biochemistry: Principles and Applications

Preface. Chapter 1 Introduction. 1.1 Special Chemical Requirements of Biomolecules. 1.2 Factors Affecting Analyte Structure and Stability. 1.3 Buffering Systems Used in Biochemistry. 1.4 Quantitation, Units and Data Handling. 1.5 The Worldwide Web as a Resource in Physical Biochemistry. 1.6 Objectives of this Volume. References. Chapter 2 Chromatography. 2.1 Principles of Chromatography. 2.2 Performance Parameters Used in Chromatography. 2.3 Chromatography Equipment. 2.4 Modes of Chromatography. 2.5 Open Column Chromatography. 2.6 High Performance Liquid Chromatography (HPLC). 2.7 Fast Protein Liquid Chromatography. 2.8 Perfusion Chromatography. 2.9 Membrane-Based Chromatography Systems. 2.10 Chromatography of a Sample Protein. References. Chapter 3 Spectroscopic Techniques. 3.1 The Nature of Light. 3.2 The Electromagnetic Spectrum. 3.3 Ultraviolet/Visible Absorption Spectroscopy. 3.4 Fluorescence Spectroscopy. 3.5 Spectroscopic Techniques Using Plane-Polarized Light. 3.6 Infrared Spectroscopy. 3.7 Nuclear Magnetic Resonance (NMR) Spectroscopy. 3.8 Electron Spin Resonance (ESR) Spectroscopy. 3.9 Lasers. 3.10 Surface Plasmon Resonance. References. Chapter 4 Mass Spectrometry. 4.1 Principles of Mass Spectrometry. 4.2 Mass Spectrometry of Proteins/Peptides. 4.3 Interfacing MS with other Methods. 4.4 Uses of Mass Spectrometry in Biochemistry. References. Chapter 5 Electrophoresis. 5.1 Principles of Electrophoresis. 5.2 Nondenaturing Electrophoresis. 5.3 Denaturing Electrophoresis. 5.4 Electrophoresis in DNA Sequencing. 5.5 Isoelectric Focusing (IEF). 5.6 Immunoelectrophoresis. 5.7 Agarose Gel Electrophoresis of Nucleic Acids. 5.8 Pulsed Field Gel Electrophoresis. 5.9 Capillary Electrophoresis. 5.10 Electroblotting Procedures. 5.11 Electroporation. References. Chapter 6 Three-Dimensional Structure Determination of Macromolecules. 6.1 The Protein-Folding Problem. 6.2 Structure Determination by NMR. 6.3 Crystallization of Biomacromolecules. 6.4 X-Ray Diffraction by Crystals. 6.5 Calculation of Electron Density Maps. 6.6 Other Diffraction Methods. 6.7 Comparison of X-Ray Crystallography with Multi-Dimensional NMR. 6.8 Structural Databases. References. Chapter 7 Hydrodynamic Methods. 7.1 Viscosity. 7.2 Sedimentation. 7.3 Methods for Varying Buffer Conditions. 7.4 Flow Cytometry. References. Chapter 8 Biocalorimetry. 8.1 The Main Thermodynamic Parameters. 8.2 Isothermal Titration Calorimetry. 8.3 Differential Scanning Calorimetry. 8.4 Determination of Thermodynamic Parameters by Non-Calorimetric Means. References. Chapter 9 Bioinformatics. 9.1 Overview of Bioinformatics. 9.2 Sequence Databases. 9.3 Tools for Analysis of Primary Structures. 9.4 Tertiary Structure Databases. 9.5 Programs for Analysis and Visualization of Tertiary Structure Databases. 9.6 Homology Modelling. References. Chapter 10 Proteomics. 10.1 Electrophoresis in Proteomics. 10.2 Mass Spectrometry in Proteomics. 10.3 Chip Technologies in Proteomics. 10.4 Post-Translational Modification Proteomics. Further Reading. References. Appendix 1 SI Units. Appendix 2 The Fourier Transform. Index.
Improved Nearest Neighbor Density-Based Clustering Techniques with Application to Hyperspectral Images

We consider the problem of density-based unsupervised classification in hyperspectral data. Our focus is especially on methods based on K nearest neighbors (KNN) graph. In this paper, we propose some improvements of recently published methods in this vein, namely GWENN (Graph WatershEd using Nearest Neighbors) as well as a KNN version of Density Peaks Clustering. These improvements address (i) the structure of the KNN graph, which can be modified efficiently to emphasize the dependencies between objects, especially in high dimensional data sets; (ii) the choice of the pointwise density model; and (iii) the ability of these methods to handle variable NN graphs. The improved methods are compared in the context of pixel partitioning in hyperspectral images and are shown to give encouraging results, outperforming state-of-the-art methods like DBSCAN and FCM.