Reviewerly/exHarmony huggingface dataset:
Supplemental material: Transport and biogeochemical reaction of metals in a physically and chemically heterogeneous aquifer

Geosphere, June 2006, v. 2, p. 220-235, doi: 10.1130/GES00029.1. Animation 1 - Animation of simulation results for U(VI) contamination period (22 yr) for the Geophys2 case. Upper panel—sorbed U(VI); lower panel—aqueous U(VI). All concentrations are in molar units (M). The file size is 1.4 MB.
Blockchain Technology Application as an Add-On Feature in Supply Chain Management of Drug Production Process in the Pharmaceutical Industry

The production process is an important process to determine the quality of drugs produced by the pharmaceutical industry. The production process aims to send goods for use by consumers. This process does not have full visibility and uses a manual process to track the movement of ingredients. This results in a lack of data transparency in drug production, a major problem often faced by the pharmaceutical industry in supply chain management. The process without data transparency will reduce the quality and assurance of drugs and the ability to record information in the drug production process. Based on these problems, this study develops a mobile application by implementing a blockchain system to support the system supply chain management process from material sources, production processes to distribution to consumers. This research was conducted with a prototyping model approach in application development and multichain as blockchain technology. This research produces a mobile application with a blockchain system in the supply chain management process. The development of the application ensures that all transaction data is recorded properly and produces information that anyone can see so that the blockchain system becomes transparent, ensures security, data integrity, and makes tracking production information easier.
Reviewer Acknowledgements

Applied Economics and Finance (AEF) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether AEF publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 7, Number 3 Ali Massoud, Sohag University, EgyptAyoub Taha Sidahmed, SIU, SudanFarhat Iqbal, University of Balochistan, PakistanHedieh Shadmani, Fairfield University, USAIulia Lupu, Victor Slavescu” Centre for Financial and Monetary Research, Romanian Academy, RomaniaKaveh Dalvand, University of Delaware, United StatesMagdalena Radulescu, University of Pitesti, RomaniaMagdalena Zioło, University of Szczecin, PolandMamdouh Abdelmoula M. Abdelsalam, Minufiya University, EgyptMohammed Al-Mahish, King Faisal University, Saudi ArabiaNana Rusadze, Akaki Tsereteli State University, GeorgiaNuno Crespo, ISCTE-IUL, PortugalPatrycja Kowalczyk-Rolczynska, Wroclaw University of Economics, PolandRajeev Rana, APB Govt. P.G. College, IndiaRamona Orastean, Lucian Blaga University of Sibiu, RomaniaRichard Nguyen, Alliant International University, USARomeo Victor Ionescu, Dunarea de Jos University, RomaniaRuhet Genc, Turkish-German University, TurkeyShahram Fattahi, Razi University, IranSzabolcs Blazsek, Universidad Francisco Marroquín, GuatemalaVictoria Cociug, Academy of Sciences of Moldova, MoldovaY. Saidi, M’sila University, AlgeriaZi-Yi Guo, Wells Fargo Bank, N.A., USAZuzana Janko, San Francisco State University, USA Nikki GibbsEditorial AssistantOn behalf of,The Editorial Board of Applied Economics and FinanceRedfame Publishing9450 SW Gemini Dr. #99416Beaverton, OR 97008, USAURL: http://aef.redfame.com
Novel Filtering Methods for Image and Video Processing Applications

During the last few years, digital filtering methods for image/video processing applications have reached a satisfactory level. However, their performance degrades in the presence of noise, trend, motion, shape deformation, intensity inhomogeneity, shadows, or low image quality, to name a few. To cope with these challenges, this dissertation presents novel filtering methods for image/video processing applications that outperform the existing and state-of-the-art methods. The dissertation starts by introducing a novel trend filtering method that transforms the inter-frame registration problem into low complexity trend filtering problem. In the proposed method, Laplacian eigenmaps in conjunction with the modified empirical mode decomposition has been used to suppress the noise artifacts and the trend term. In multi-dimensional signals, the trend term is often referred to as non-uniform illumination or global intensity inhomogeneity. This dissertation presents a new filtering method for estimating the global intensity inhomogeneity in two dimensional and volume images. Global intensity inhomogeneity often arises due to the imperfections of data acquisition device, direction of source light, and properties of the subject under study. The proposed method generates a high-pass filter based on the grey-weighted distance transform of the frequency content of an image/volume. It provides an accurate estimation of global intensity inhomogeneity without any parameter tweaking, which makes it applicable to many imaging modalities. The dissertation also presents a filtering methodology to cope with local intensity inhomogeneity that gives rise to shadow artifacts. These artifacts appear as sharp discontinuities and are often corrected at different scales and orientations. The proposed method makes use of decimation-free directional filter bank to suppress the local intensity inhomogeneity and shadow artifacts irrespective of scale and orientation. In addition to intensity inhomogeneity correction, the dissertation also presents a filtering method that utilizes the Gabor filter bank to generate rotation invariant feature codes. The effectiveness of the proposed method has been evaluated in both identification and verification modes for fingerprint recognition. The uniqueness of the presented filtering methods lies in the fact that they are essentially parameter free and can easily be scaled to higher dimensions. This makes them applicable to many different image/video processing applications with least of effort from the end user, i.e., eliminating the user biases.
Automated Text Analysis

This chapter examines automated text analysis (ATA), which describes the different methodologies that can be applied in order to perform text analysis with the use of computer software. ATA is a computer-assisted method for analysing text, whenever the analysis would be prohibitively labour-intensive due to the volume of texts to be analysed. ATA methods have become more popular due to current interest in big data, taking into account the volume of textual content that is made easily accessible by the digitization of human activity. Key to ATA is the notion of <italic>corpus</italic>, which is a collection of texts. A necessary step before starting any analysis is to collect together the necessary documents and construct the corpora that will be used. Which texts need to be included in this step is dictated by the research question. After text collection, some processing steps need to be taken before the analysis starts, for example tokenization and part-of-speech tagging. Tokenization is the process of splitting a text into its constituent words, also called tokens, whereas part-of-speech tagging assigns each word a label that indicates the respective part-of-speech.
Python Classes

In Python everything is an object and as such is an example of a type or class of things. For example, integers are an example of the int class, real numbers are examples of the float class etc.
Useful description of update to cloud and flux data set

Line 188: they state here that thin multi-layer clouds are retrieved as the weighted average of the two layers.It would be useful to say if this situation is flagged in the data or if there's some mechanism to screen the data for this.From line 221 to the end of the section: they discuss hear the uncertainty of the radiative flux estimates.Does uncertainty here refer to precision or accuracy?Also, are the values given for CERES (5.4 and 4.6 W/m2) the uncertainty for the global average or at a grid point?Captions of Fig. 4 and 5.The captions refer to "forcing", but they really mean are fluxes.This should be changed.
Chapter 19: Open-Source Clustering Software

Many clustering algorithms have been implemented in different programming languages. In this chapter, we introduce some open source clustering software, i.e., software that is publicly available with source codes. In particular, we introduce clustering software that has been implemented in popular programming languages such as R, Python, Java, and C++.
Licensing Negative Concord Items

This chapter discusses the syntactic configurations and processes that are involved in licensing the various types of NCIs (negative concord items) in Arabic. The author argues for a revised syntactic agreement approach. In this way, the chapter explains the behavior of Arabic NCIs with extra mechanisms (positing an abstract negative operator) to explain non-strict NCIs by conceptualizing a revised inventory of abstract negation features that the various types of Arabic NCIs carry, thus partially building on and departing from analyses for Germanic languages. The coordinators <italic>laa-wala</italic> ‘neither-nor’ are conspicuous analogues of the NCI <italic>wala</italic>, which can combine with NPs to create person-NCIs such as <italic>wala-ħada</italic> ‘no body,’ in their ability to co-occur with the negative adverb <italic>maʕumrhiš</italic> ‘never’ in the CP (complementizer phrase) layers without triggering a double negation reading. A covert negative operator licenses the coordinators <italic>laa-wala</italic> as a last resort in the absence of overt licensors.
SLOCKTM- Sleep Sock for Tracking Chronobiology

Circadian rhythm is the natural rhythm associated with the sleep-wake cycle present in the body, it is an indication of the functioning of Hypothalamic-pituitary (HPA) axis. This rhythm can be tracked using biomarkers such as cortisol. Circadian rhythm is often disrupted in people that are shift workers, frequent travelers, suffering from sleep disorders, depression or adrenal disorders. An estimate of 50-70 million Americans suffer from chronic sleep disorders (NHLBI, 2003) which hinders routine functioning and have deleterious health implications including elevated cortisol levels, increased risk of hypertension, diabetes, depression, cardiac conditions and stroke. Currently available technologies for monitoring the circadian rhythm include techniques like Polysomnography (Ambulatory monitoring of nocturnal sleep), Actigraphy (Multiday ambulatory assessment), cortisol assays, core body temperature monitoring and cardiovascular activity monitoring. However, these technologies do not provide an accurate estimation of the extent of circadian disruption, as they are superficial. Biomarker estimation using cortisol helps us analyze the severity of the disease. Assays for cortisol usually rely on the use of blood or serum and take about 3-4 hours for the test results which proves to be an ineffective solution, from the point of view of developing a circadian profile for the user. This project is aimed at developing a wearable, circadian rhythm self-monitoring platform which is non-invasive, label free and cost- effective solution to track the sleep-wake cycle in the body. The platform is a flexible porous electrochemical sensor integrated into a sock that is ideally used to capture the rise and fall of circadian biomarkers like cortisol during the sleep-wake cycle in order to track the HPA axis functioning in the user. This sensor is calibrated using Electrochemical Impedance Spectroscopy (EIS) and the Impedance changes are recorded as a function of cortisol concentration, depicted in Fig. 1. Limit of detection of the sensor is 1 ng/ml and it operates over the relevant physiological range for cortisol in sweat i.e. 8-141 ng/ml. Figure 1 : Calibrated dose response curve for cortisol plotted as impedance vales against cortisol concentration . Figure 1
Disaster Recovery Method for Network Surge and Sudden Change Data Based on DELTA Compression Algorithm

With the rapid development of our country's industrialization process, how to ensure the data security of information systems in daily production has become an important issue that modern enterprises must solve. For computer information systems, continuous and uninterrupted provision of efficient services is the main goal. In actual production, some non-man-made natural disasters and subjective and objective man-made disasters such as earthquakes, fires, computer viruses, network failures, hardware/software failures, etc, affect IT services. This article focuses on the network surge mutation data disaster recovery method based on the DELTA compression algorithm, understands the DELTA compression algorithm and the related theories of the data disaster recovery method based on the literature, and then designs the network surge mutation data based on the DELTA compression algorithm disaster recovery system and test the designed system. The test results show that the DELTA compression algorithm in this article has a good effect on eliminating the redundancy of the two types of data files except audio and video files in the test cases.
Investigating the use of mobile instant messaging-facilitated 5E-flipped learning: a two-stage study

Despite the worldwide popularity of flipped learning, we understand little about how to coherently structure a flipped class with appropriate communication services to engage students. This two-stage study examines in flipped learning context, how students perceived learning guided by the 5E design model (engagement-exploration-explanation-elaboration-evaluation), and how different technologies impacted the learning experience. We first reported a multiple-case study on how students felt about the 5E model-based flipped learning, facilitated by mobile instant messaging (MIM) tools. We then conducted a comparative study to investigate how students felt about using either MIM or a threaded asynchronous forum for discussion. The results suggested that 92% of participants found flipped learning more engaging and 81% reported that flipped learning gave them more time to discuss or solve problems. Most students welcomed using MIM for flipped learning, but online forum was still preferred for academic discussions. Possible reasons and suggestions for future research are discussed.
Research on 3D Human Body Reconstruction Algorithm of Monocular Image

The three-dimensional human body feature parameters extracted by the neural network method are coupled in the high-dimensional feature space. The fully connected network processes the three-dimensional human pose and shape feature information synchronously, which cannot handle multifactor features well, which makes the model perform poorly. To solve this problem, on the basis of the benchmark network, a decoupling model is added, which processes the three-dimensional human pose and shape information separately, and finally integrates the features through the bi-linear transformation method. Through experimental verification, the algorithm effectively reduces the reconstruction error, and the improved algorithm performs better.
Importance of Context in Prediction Systems of Mobile Applications

Many traditional systems give recommendations to the users based on their past history without considering the context of the situation the user is in currently. Such systems may be good at prediction based on the past but do not consider the rapidly changing environment and the prediction may not be the best for the user. Context personalized to the user is important because it explains the situation the user is in. The recommendations to the user should also change according to the various contexts present. Context often represents the hidden state information that the user is in currently. Many systems often take into consideration the location of the user because the situation of the user generally changes with the location. In this paper, we explain why context is important while predicting results for the users by reviewing a set of papers where different contexts such as weather, time, location, user preference, and activity have been taken into consideration. These papers have taken context such that the recommendations to users change dynamically according to their situation or location and these recommendations can be of various forms such as search results or targeted advertisement. Location based Services, Location based advertisement and several types of context have also been discussed in the paper. A general architecture of context-aware systems has also been proposed. Several real world companies also make use of this contextual information so that the user has a dynamic user experience where all the states which might affect his decision making are taken into consideration.
Collaborative filtering based service ranking with invocation histories

Collaborative filtering based recommender systems have been very successful on dealing with the information overload problem and providing personalized recommendations to users. When more and more web services are published online, this technique can also help recommend and select services which satisfy users’ particular Quality of Service (QoS) requirements and preferences. In this thesis, we propose a novel collaborative filtering based service ranking mechanism, in which the invocation and query histories are used to infer the users’ preferences, and user similarity is calculated based on invocations and queries. To overcome some of the inherent problems with the collaborative filtering systems such as the cold start and data sparsity problem, the final ranking score is a combination of the QoS-based matching score and the collaborative filtering based score. The experiment using the simulated data proves the effectiveness of the proposed algorithm.
Skills for managing digital security risks and privacy

The ability of organisations and people to manage digital security risk and privacy is key to fostering trust in online environments. From a business perspective, management of digital security risk needs to be integrated across the entire business process in order to be effective. It may be undertaken internally by employees or outsourced depending on the business strategy and the availability of resources, including skills present in the workforce. From an individual perspective, awareness of security and privacy threats and the competencies to prevent and respond to them are crucial for prospering in the digital society.
Correlation And Simple Regression As Inferential Techniques

Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.
Verizon: Cyber-Espionage Report

Spying is getting easier all the time. Meetings with ‘assets’ on shady corners in exotic locations is quickly becoming a thing of the past. Spies accustomed to operating in the shadows can now remain in the comfort of their brightly lit, air-conditioned offices and simply crack open their laptops. Everything is available on the Internet.
Arithmetical Comprehension

This chapter focuses on arithmetical comprehension. Arithmetical comprehension is the most obvious set existence axiom to use when developing analysis in a system based on Peano arithmetic (PA) with set variables. This axiom asserts the existence of a set <italic>X</italic> of natural numbers for each property <italic>φ‎</italic> definable in the language of PA. More precisely, if <italic>φ‎</italic>(<italic>n</italic>) is a property defined in the language of PA plus set variables, but with no set quantifiers, then there is a set <italic>X</italic> whose members are the natural numbers <italic>n</italic> such that <italic>φ‎</italic>(<italic>n</italic>). Since all such formulas <italic>φ‎</italic> are asserted for, the arithmetical comprehension axiom is really an axiom schema. The reason set variables are allowed in <italic>φ‎</italic> is to enable sets to be defined in terms of “given” sets. The reason set quantifiers are disallowed in <italic>φ‎</italic> is to avoid definitions in which a set is defined in terms of all sets of natural numbers (and hence in terms of itself). The system consisting of PA plus arithmetical comprehension is called ACA<sub>0</sub>. This system lies at a remarkable “sweet spot” among axiom systems for analysis.
Umicore to establish a fuel cell catalyst plant in South Korea

We discuss the issues of primary importance to understand the nature of climate changes in the 20th century and main physical processes responsible for these changes and present a physical model for the solar activity (SA) effect on climate characteristics. A key concept of this model is the heliogeophysical disturbance effect on the Earth climate system parameters driving the long-wave radiation flux moving away from the Earth out into space in high-latitude regions. We address the solar activity effect on the changes in the temperature of the atmosphere and of the World Ocean. The aa–index of the geomagnetic activity (GA) was used as an SA proxy index. We discuss the results of analyzing the regularities and peculiarities of the tropospheric and sea surface temperature (SST) responses to both separate heliogeophysical disturbances and long-term changes in solar and geomagnetic activity. The structure of the tropospheric and SST temperature responses was shown to feature a spatial time irregularity. We revealed the regions, where long-term SST changes are determined mainly by SA variations.
Congratulations to the Elected IEEE Presidents

We are pleased to announce that Professor Toshio Fukuda, the second Editor-in-Chief of JRM, has been elected as 2019 IEEE (The Institute of Electrical and Electronics Engineers) President-Elect (2020 President), and Professor Kazuhiro Kosuge, former Deputy Editor-in-Chief of JRM, has been elected as 2019 IEEE Technical Activities Vice President-Elect (2020 IEEE TA Vice President). Congratulations! They have devoted themselves to the development of the Journal of Robotics and Mechatronics. Prof. Fukuda and Prof. Kosuge will serve as IEEE President and IEEE Technical Activities Vice President, respectively, in 2020. We look forward to their continued success in the future.
Animation Classes

In this chapter, we’ll review a set of animation classes that can be used to provide basic animation support for certain elements of your next game. The MmgPositionTween class in particular is an advanced implementation that takes into account child objects, timing, drawing, and positioning. This class needs to be plugged into the game engine’s drawing routine and receive update calls to maintain the correct timing during the animation: