Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis of spiral and reverse spiral Co-ferrite by co-precipitation method and XRD Characterization

The Co-ferrite were prepared via co-precipitation of CoCl2.6H2O, ZnCl2.4H2O and FeCl3. 6H2O salts in the presence of NaOH as a precipitating agent at 90 ◦ C. The prepared ferrites were characterized using X-ray diffraction (XRD) and particle size was investigated by sheerer formula. The prepared Co-ferrites were found to be magnetized and particle size was ranged from 22-53 nm. The maximum spontaneous magnetization and minimum particle size was obtained at x = 0.25 when metal ion was in beaker. By reversing the solutions, the ferrites changed from spiral to inverse spiral with decreased particle size. It is found that ferrite properties were dependent to the co-precipitation condition such as concentration of metal ion and solution interchangeability.
HRM IN FOREIGN FIRMS IN INDIA. A RESOURCE-BASED VIEW

Currently, foreign firms in India face three major challenges in the field of human resource management (HRM): personnel recruitment, development and retention. We adapted the resource-based view of the firm (RBV) for HRM, and tested in a sample of 80 foreign firms which HRM practices have a positive impact on the efficiency of HRM. Our findings suggest that there is a close relationship between the employment of HRM instruments shaped according to the RBV and HRM efficiency; hence they help foreign firms in India to positively affect the HRM challenge. Copyright statement Please do not quote without permission from the authors. Only the final version that will be accepted for publication should be cited. This document has been posted for the purpose of discussion and rapid dissemination of preliminary research results.
Nonlinear Pricing under Asymmetric Competition with Complete InformationWe gratefully acknowledge helpful comments from seminar participants at Caltech, SHUFE, UC Davis, UCSB, University of Hong Kong, University of Southern California, Zhejing University, UBC, U of Washington, UC Irvine, National Ch

Motivated by several recent antitrust cases, we study a strategic model of competition in intermediate-goods markets. Our model is a three-stage game with complete information in which a dominant firm offers a general tariff first and then a rival firm responds with a per-unit price, followed by a buyer making her decision to purchase from one or both firms. We characterize subgame perfect equilibria of the game and study the implications of the equilibrium outcome. Our paper makes three main contributions. First, it provides a novel explanation for the prevalence of nonlinear pricing (a menu of offers conditional on volumes) under duopoly in the absence of private information: The dominant firm can use a menu of offers to constrain its rival’s choices and extract surplus from the buyer. Second, it shows that when the capacity of the rival firm is constrained, as compared to linear pricing schemes, the nonlinear pricing tariff adopted by the dominant firm reduces the price, sales, and profits of the rival ∗We gratefully acknowledge helpful comments from seminar participants at Caltech, SHUFE, UC Davis, UCSB, University of Hong Kong, University of Southern California, Zhejing University, UBC, U of Washington, UC Irvine, National Cheng Kung University, Chinese University of Hong Kong, and UNC Chapel Hill. Chao: College of Business, University of Louisville, yong.chao@louisville.edu; Tan: Department of Economics, University of Southern California, guofutan@usc.edu; Wong: Department of Economics, Lingnan University, adamwong@ln.edu. hk.
Where and When Counts: Action Recognition in Videos

Videos usually contain redundant information that not only results in computation complexity but also introduces disturbance for action recognition task. The redundant information comes from two ways. The first is temporal-level redundancy: for a video, some frames have little relevance to the action. The second is spatiallevel redundancy: in a frame, some regions have nothing to do with the action. We believe only attending to the relevant information has the potential to boost accuracy for video action recognition. In this work, we propose an attention agent that can decide where and when to focus on, and we build our spatiotemporal attention agent upon Long-term recurrent convolutional network[2]. We evaluate our model on UCF-11, and find our model improves the accuracy compared with the baseline methods.
PORTFOLIO THEORY AND THE CAPM: THEORY AND TESTS

The purpose of this handout is two-fold. Firstly, it serves as a guide to understanding some of the important intuitions from portfolio theory and the capital asset pricing model (CAPM). This purpose is best served by gaining comfort with the assumptions, remarks, and figures in this handout. The second goal here is to provide interested students with an accurate sketch of the theory guiding the results from this section of the course. Although proofs are not provided in full detail, the work contained in the appendices should allow students to gain a sufficient understanding of the foundational theorems of portfolio theory and the CAPM. As a special bonus, I have included a couple summaries of important empirical papers related to the CAPM. These write-ups were prepared for personal use and are not expected to be fully absorbed by everyone. However, since I’m sure some students have the technical background necessary to follow these summaries, I’ve decided to throw them in. I encourage students to at least read over the summaries of these sections. 1. Portfolio Theory I: General Discussion. Remark 1.1 (Portfolio Theory). Portfolio theory is an economic theory of investor behavior. It postulates a framework for selecting optimal (efficient) portfolios. This framework is closely connected to the efficiency frontier because every investor chooses a portfolio on the upward sloping part of this curve. The importance of this topic became clearest when it was used to derive the CAPM (which is a model of asset pricing based on investor behavior described by the portfolio theory). In its essence, portfolio theory narrows in on one specific aspect of normative investment. short term diversification. Its results, taken at face value, are not accurate if we consider diversification over long horizons, asymmetric information/differences in opinion, transactions costs, nontradeability of certain assets, and other imperfections in financial markets. Regardless, portfolio theory remains an important component of finance theory for three reasons:
Terroir Suitability Zoning for the Six Prevailing Wine Grape Varieties in Ningxia Hui Autonomous Region (with a Focus on the Helan Mountain East) of China

Terroir plays an important role in wine grape production and good wine making. Among all the aspects of terroir in a given region, climate, soil and variety are the most important ones. The goal of this study was to evaluate these three aspects of terroir in Ningxia Hui Autonomous Region of China, with a focus on the Helan Mountain East. Based on historical weather data during the period 1981 to 2016 from 22 meteorological stations in the research area, the climatic indices were derived, with which the growable zone for wine grape cultivation in the research area was identified. By synthesizing the climatic indices and soil type data, stepwise and optimization methods were used to divide the growable zone into optimal, suitable, near-suitable and unsuitable zones for the six prevailing wine grape varieties. In the analysis, the six prevailing wine grape varieties include two white wine grape varieties of “Chardonnay” and “Riesling” and four red wine grape varieties of “Cabernet Sauvignon”, “Merlot”, “Pinot Noir” and “Grenache Noir”. With the Geographic Information System (ArcGIS) software, the geographical distributions of these terroir suitability zonings were mapped in the research area according to a small grid simulation model. The results showed that the growable zone for wine grapes was mainly focused in most of the northern and central parts of Ningxia Hui Autonomous Region. This particular zone was suitable for the typical red wine varieties like late-maturing “Grenache Noir”, medium-to-late maturing “Cabernet Sauvignon”, medium-maturing “Merlot” and early-maturing “Pinot Noir”. In particular, the optimal zone for these four red wine varieties was centered in Xixia county of Yinchuan city, Pigeon Hill of Qingtongxia city and Baima Township of Zhongning County. For the two early-to-medium maturing white wine varieties of “Riesling” and “Chardonnay”, the optimal and suitable zones were in the cool area of the central arid zone and the Qingshui River tributary.
Differential Privacy for Image Publication

Rapidly generated image data can be shared to advance research and benefit various communities. However, sensitive individual information captured in the data, such as license plates and identities, may inflict privacy concerns when sharing image data with untrusted parties. Existing image privacy solutions rely on standard obfuscation, e.g., pixelization and blurring, which may lead to reidentification. In this study, we explore how differential privacy can enhance standard image obfuscation. Specifically, we extend the standard differential privacy notion to image data, which protects individuals, objects, and/or their features. We develop differentially private methods for two popular image obfuscation techniques, i.e., pixelization and Gaussian blur. Empirical evaluation with realworld datasets demonstrates the utility and privacy of our methods. Furthermore, our methods are shown to effectively reduce the success rate of CNN based re-identification attacks. The abstract extends our previously published conference paper [4], with a newly developed DP-Blur method and additional empirical results. Discussions are also provided for future work on differential privacy for image publication. ACM Reference Format: Liyue Fan. 2019. Differential Privacy for Image Publication. In Proceedings of TPDP ’19: Theory and Practice of Differential Privacy (TPDP ’19). ACM, New York, NY, USA, 4 pages. https://doi.org/XXX
Gene diversity and demographic turnover in central and peripheral populations of the perennial herb Gypsophila fastigiata

General rights Unless other specific re-use rights are stated the following general rights apply: Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal
INFLUENCE OF Ni/Zn RATIO VARIATION ON STRUCTURAL AND MAGNETIC PROPERTIES OF NiZn FERRITES

Pure single phase polycrystalline NiZn ferrite materials with the chemical composition NixZn1-xFe2O4, where x = 0.30, 0.33, 0.36, 0.42 and 0.50 were prepared by solid state reaction with a slow cooling from the sintering temperature 1200oC for 6 hours. The influence of Ni/Zn ratio in composition on structural and magnetic properties prepared ferrite samples was investigated. The str uctural properties were analysed using by the X–ray diffraction method, the particle size and shape were studied using by the Scanning Electron Microscope. Low-frequency magnetic properties of prepared NiZn ferrites were determined from the measured magnetisation curves. The results have confirmed known, a little bit surprising fact, that for x > 0.3 the addition of ferromagnetic metal (Ni) into the chemical composition deteriorates some magnetic properties (especially the permeability, coercivity, etc), meanwhile the Curie temperature increases.
Ose of Preoperative MR to Predict Dural, Perineural, and Venous Sinus Invasion of Skull Base Tumors

PORPOSE: To assess the accuracy of MR imaging in predicting dural, venous sinus, and perineural invasion by skull base tumors. METHODS: The preoperative MR images of 22 patients who had resection of skull base neoplasms were evaluated for the following characteristics: dural enhancement, pial enhancement, local perineural invasion by adjacent tumor, and venous sinus invasion by tumor. The greatest width of dural enhancement was measured, and the character of dural enhancement was noted. The pathologic and surgical reports were reviewed retrospectively with specific attention to dural, venous, and local perineural invasion. RESOLTS: Of the 22 patients studied, dural invasion by tumor was confirmed in eight patients, vascular invasion in six patients, and perineural invasion in four patients. The sensitivity of dural enhancement in predicting invasion was 8B%, the specificity 50%, and the accuracy 64/o. When enhancement and focal nodularity were present, the sensitivity remained at88%; however, specificity was 100% and accuracy 95%. lf the dural enhancement was more than 5 mm thick, sensitivity, specificity, and accuracy were 75/o, 100%, and 91%, respectively. Predicting tumor invasion of the dura by the presence of pial enhancement was 50% sensitive and 100% specific, Venous sinus/jugular vein invasion was predicted with 100% sensitivity, 94% specificity, and 95% accuracy. Local perineural invasion was predicted with 100% sensitivity, 50% specificity, and 59% accuracy. CONCLOSIONS: The presence of pial enhancement, focal dural nodules, or dural thickening of more than 5 mm is highly accurate in predicting the presence of neoplastic dural invasion. Linear enhancement of dura does not imply dural infiltration by tumor. Venous invasion by tumor can be predicted accurately with preoperative MR imaging.
Improving Visual Question Answering Using Semantic Analysis and Active Learning

In this work, we aim to train a model for the task of visual question answering, using only a small number of labeled data. In order to do so, we used the ideas inﬂuenced by the active learning. We deﬁned an oracle to provide a label for the question that is asked about an image. This oracle is an image captioning network, that given an image as its input, generates a sentence that describes the objects that are visible in that image. We use a semantic similarity calculator, in order to connect the result of the image captioning model and interpret that to become a potential label for the visual question answering task. By using this structure and deﬁning a new loss function, we became able to train a visual question answering model using a small number of labeled data. We conclude that by using this idea, we can train a model that has a generalization that is in the class of the classical models that use a great amount of data.
Short Term Ration Restriction and Re-alimentation: Effect on Compensatory Growth, Body Composition and Insulin-like Growth Factor Gene Expression in Cyprinus carpio

We wish to acknowledgement our sincere gratitude to the Indian Council of agricultural Research (ICAR) and The Director, Central Institute of Fisheries Education, Mumbai, India for granting institutional fellowship for the successful completion of this piece of research work. We also acknowledge the facilities provided at Wet laboratory (Aquaculture), Fish Genetics and Biotechnology Laboratory of CIFE, Mumbai to carry out this research work successfully.
Fluorogenic Trp(redBODIPY) cyclopeptide targeting keratin 1 for imaging of aggressive carcinomas†

Keratin 1 (KRT1) is overexpressed in squamous carcinomas and associated with aggressive pathologies in breast cancer. Herein we report the design and preparation of the first Trp-based red fluorogenic amino acid, which is synthetically accessible in a few steps and displays excellent photophysical properties, and its application in a minimally-disruptive labelling strategy to prepare a new fluorogenic cyclopeptide for imaging of KRT1+ cells in whole intact tumour tissues.
Spatial and temporal variations in the groundwater contributing areas of inland wetlands

Water quality and groundwater dynamics in wetlands are strongly influenced by the spatiotemporal distribution of contaminant application, and variations and changes in climate, vegetation, and anthropogenic interventions in its neighborhood. For groundwater‐fed wetlands, this relevant neighborhood at least extends to the groundwater contributing area (GCA) boundary. In spite of its importance, understanding of the nature of GCA dynamics vis‐à‐vis meteorological variations remains largely understudied. This work attempts to map GCA of inland forested wetlands. Following that, two specific questions are answered: (a) Is GCA extent and its variation different than that of the topographic contributing area (TCA)? and (b) Is the temporal dynamics of GCA for different wetlands, all of which are experiencing very similar climatological forcing, similar? Our results show that GCAs for wetlands vary temporally, are much different in extent and shape than the TCA, and on an average are larger than the TCA. Although wetlands in the studied watershed experienced similar meteorological forcings, their covariation with forcings varied markedly. Majority of the wetlands registered an increase in GCA during dry period, but for a few the GCA decreased. This highlights the role of additional physical controls, other than meteorological forcings, on temporal dynamics of GCA. Notably, wetlands with larger TCA are found to generally have larger average GCA as well, thus indicating the dominant role of topography in determining the relative size of average GCA over the landscape. Our results provide a refined picture of the spatiotemporal patterns of GCA dynamics and the controls on it. The information will help improve the prediction of wet period dynamics, recharge, and contamination risk of groundwater‐fed wetlands.
THE EIGENVALUE SPECTRUM OF THE LINEAR BOLTZMANN OPERATOR IN L'(W) AND L2(W) *

SOMMARIO. Viene studiato lo spettro di autovalori dell'operatore tntegrodifferenziale lineare del trasporto dei ncutronL nell'ambito dell'approccio del tipo cteoria dello scattering# di Heflmanek. Lo spettro risulta alquanto diverso da quello che si ottiene nell'ambito della teoria classica; un'interpretazione fisica di tale diversitd ~ accennata hell'ultimo paragrafo. Le due teorie spettrali hanno perd in comune it fatto che, in entrambi i casi, esiste una regione piana interamente occupata dallo spettro. Cid esclude in pratica, ogni possibilit~ di giungere a una formula di risoluzione spettrale.
Evaluation of Biofilm Formation and Anti-biofilm Properties of Peganum Harmala and Crocus Sativus in Shigella Flexneri Clinical Isolates

Biofilm formation causes many serious problems in the treatment of bacterial infections. In addition, chronic infections due to biofilm formation can pose a huge burden to the health care systems. Also, many bacteria are biofilm producers as an important strategy for pathogenicity. Furthermore, the traditional use of herbal medicines such as Peganum harmala and Crocus sativus in Iran is interesting.
Understanding what you feel: A Mobile Audio-Tactile System for Graphics Used at Schools with Students with Visual Impairment

A lot of information is nowadays presented graphically. However, students with blindness do not have access to visual information. Providing an alternative text is not always the appropriate solution as exploring graphics to discover information independently is a fundamental part of the learning process. In this work, we introduce a mobile audio-tactile learning environment, which facilitates the incorporation of real educational material. We evaluate our system by comparing three methods of interaction with tactile graphics: A tactile graphic augmented by (1) a document with key index information in Braille, (2) a digital document with key index information and (3) the TPad system, an audio-tactile solution meeting the specific needs within the school context. Our study shows that the TPad system is suitable for educational environments. Moreover, compared to the other methods TPad is faster to explore tactile graphics and it suggests a promising effect on the memorization of information.
Artifact Elimination from EEG Signals using Error Normalized algorithms for Brain Computer Interface Systems

In this paper some efficient and low computation complex signal conditioning algorithms are proposed in distant health tracking applications, for improvement of the electroencephalogram (EEG) signal. Few artifacts are contaminated also mask small characteristics underlying EEG signal activity in medical environments during extraction of EEG signal. Low computational difficulty filters are appealing especially within distant healthcare surveillance. Therefore, we provided several effective and less computing adaptive noise cancellers (ANCs) in this work to improve EEG signal. Most of these techniques use easy addition as well as shift calculations also attain significant convergence performance compared to other standard techniques. Real EEG signals collected using emotional EEG systems are verified for proposed implementations. Using several performances measures our studies demonstrate that techniques suggested provides best performance than prevailing methods. This methodology is suitable in the analysis of brain computer interface (BCI) applications.
Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds

Many important applications, including robotics, data-center management, and process control, require planning action sequences in domains with continuous state and action spaces and discontinuous objective functions. Monte Carlo tree search (MCTS) is an effective strategy for planning in discrete action spaces. We provide a novel MCTS algorithm (voot) for deterministic environments with continuous action spaces, which, in turn, is based on a novel black-box function-optimization algorithm (voo) to efficiently sample actions. The voo algorithm uses Voronoi partitioning to guide sampling, and is particularly efficient in high-dimensional spaces. The voot algorithm has an instance of voo at each node in the tree. We provide regret bounds for both algorithms and demonstrate their empirical effectiveness in several high-dimensional problems including two difficult robotics planning problems.
Many Faced Hate: A Cross Platform Study of Content Framing and Information Sharing by Online Hate Groups

Hate groups are increasingly using multiple social media platforms to promote extremist ideologies. Yet we know little about their communication practices across platforms. How do hate groups (or "in-groups"), frame their hateful agenda against the targeted group or the "out-group? " How do they share information? Utilizing "framing" theory from social movement research and analyzing domains in the shared links, we juxtapose the Facebook and Twitter communication of 72 Southern Poverty Law Center (SPLC) designated hate groups spanning five hate ideologies. Our findings show that hate groups use Twitter for educating the audience about problems with the out-group, maintaining positive self-image by emphasizing in-group's high social status, and for demanding policy changes to negatively affect the out-group. On Facebook, they use fear appeals, call for active participation in group events (membership requests), all while portraying themselves as being oppressed by the out-group and failed by the system. Our study unravels the ecosystem of cross-platform communication by hate groups, suggesting that they use Facebook for group radicalization and recruitment, while Twitter for reaching a diverse follower base.