Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Soil Properties, Bacterial Community Composition, and Metabolic Diversity in Fluvisols of a Floodplain Area

The quality of a soil environment affects the microbial community that inhabits it. We decided to examine whether soils formed from river sediments, located in an area of high biodiversity of organisms, are fertile and microbiologically diverse. Fluvisols are considered to be one of the most fertile soils. In this research, bacterial and metabolic diversity, as well as physico–chemical parameters, in three Fluvisols from the Vistula River Gorge of Lesser Poland was investigated. The analysis of physico–chemical and biological parameters demonstrated statistically significant differences between the three Fluvisols examined. While determining the metabolic potential of soil microbiomes with the use of the EcoPlate™ Biolog® technique, we also noted variation between the Fluvisols; however, they were arranged in a significantly different manner from other properties. The next generation sequencing method enabled us to determine the microorganisms common to three Fluvisols, and we identified bacteria specific to individual soils. These results corresponded with the data obtained through EcoPlate™, indicating that the structural diversity and metabolic potential of the microbiome does not always depend on soil quality parameters. Meanwhile, the increased structural diversity of the microbiome was found to improve the metabolic potential of soil microorganisms.
Energy efficient drying technologies for sweet potatoes: Operating and drying mechanism, quality-related attributes

Sweet potatoes (SPs) are a versatile tuberous crop used as subsistence and cash crop in raw and processed forms. The major issue with SPs is post-harvest losses, which result in noticeable quality decline because of inappropriate handling, storage, delayed transit, and sales, as well as microbiological and enzymatic activity. Drying is an excellent strategy for managing short postharvest storage life, preserving nutrients, and maximizing long-term benefits. However, several parameters must be considered before drying SPs, such as relative humidity, temperature, drying duration, size, and shape. The current review looks at the factors influencing SPs' moisture loss, drying kinetics, diverse drying methods, pretreatments, operating conditions, and their efficacy in improving the drying process, functional, and nutritional qualities. An optimal drying process is required to preserve SPs to obtain concentrated nutrients and improve energy efficiency to be ecofriendly. Drying sweet potatoes using traditional methods such as sun or open-air drying was found to be a slow process that could result in a lower quality. Various advanced drying techniques, like vacuum, infrared, freeze drying, and pretreatments such as ultrasound and osmotic dehydration, have been developed and are successfully used globally. The best-fit thin-layer models (Hii, Page, two-term, logarithmic) utilized for drying SPs and appropriate modeling methods for optimizing drying procedures are also discussed.
Learning multi-market microstructure from order book data

In this paper, we investigate market behaviors at high-frequency using neural networks trained with order book data. Experiments are done intensively with 110 asset pairs covering 97% of spot-futures pairs in the Korea Exchange. An efficient training scheme that improves the performance and training stability is suggested, and using the proposed scheme, the lead–lag relationship between spot and futures markets are measured by comparing the performance gains of each market data set for predicting the other. In addition, the gradients of the trained model are analyzed to understand some important market features that neural networks learn through training, revealing characteristics of the market microstructure. Our results show that highly complex neural network models can successfully learn market features such as order imbalance, spread-volatility correlation, and mean reversion.
Summaries of Doctoral Dissertations

Every year, there is a special moment at the Economic History Association meetings, when we convene to welcome and learn from the new scholars in our field. It is a unique rite that strengthens our community, and highlights that our field is particularly embracing of this peculiar process of creative destruction, as we celebrate new work that often challenges our priors and beliefs. It is a great honor to present the candidates for the 2018 Nevins Prize. Though I always look forward to this event as a participant, I must admit that convening the dissertation panel has been a daunting, humbling, and exhilarating exercise. I received 14 submissions for the prize. Of these, 60 percent dealt with diverse issues in macroeconomics, business, and financial history, while the remaining covered various other areas, such as labor, health, and income inequality. The submissions were strong works of economic history. Many of them boldly challenge existing knowledge. I commend the resourcefulness, dedication, and insights of these promising young scholars. The depth of the dissertations made my decision a very difficult one, but it has filled me with joy at the bright prospects of our field. The three worthy finalists have each written works that make substantial contributions to American economic history, but also to economics more broadly. They ask grand and difficult questions, and they use the full arsenal of tools at their disposal to answer them as best as possible. They do prodigious work with primary sources, use state-of-the-art methods to analyze the data, and rely on narrative histories to guide their analysis. I cannot do their work justice in a short amount of time, but I encourage you all to spend a few enjoyable and instructive hours reading their research to fully appreciate it.
Lassy Small Corpus

The Lassy Small Corpus 1.1 is a 1 million word corpus with manually verified syntactic annotations. The lemma and postag annotations have been automatically assigned using Tadpole. The syntactic dependency annotations have been assigned using the Alpino parser. The automatically assigned lemmas, postags and syntactic dependency annotations were checked and corrected. Organisations involved in the building of the Lassy Large Corpus: Alfa-informatica, University of Groningen; CCL, K.U. Leuven
The Attitude Towards Boycotts: Determining Factors

According to the theories of reasoned action and planned behavior, the precedent to any human conduct is the intention to display such conduct. One of those precedents is the attitude of people. Our work is framed within this line of research, as it seeks to analyze and explain the main determinants of attitude towards boycott. Thus, we understand that the attitude of consumers towards boycott behavior depends on three fundamental beliefs: perceived legitimacy of the behavior, ethical idealism towards such behavior, and finally, ethical relativism towards boycott behavior. We emphasize legitimacy, since the relevance of legitimacy processes in the business-client relationship lies in the recognition of the validity of actions that allow their subjective recognition and, therefore, differentiate them from the legal nature of the acts. The research is carried out with 371 people and the hypotheses presented are verified through structural equation models. Discussion of the results and its implications contribute to a better understanding of the factors that determine the attitude towards customer boycott by business managers and academics.
Analysis of cartesian stiffness in robotics application

Cartesian sti ness is usually described by a 6 6 matrix which is vital in the study of rigid body grasping by multiple robot ngers. In this thesis, a closed form expression is derived for evaluating the grasped object sti ness based on the contact geometry and sti ness properties of individual robot ngers. The kinematics of manipulation by elastic ngers is also developed which describes the in nitesimal motion of the grasped object in response to small motions of individual nger tips. Another more di cult problem is to identify the sti ness and con guration of individual ngers from the given sti ness of the grasped object. A number of algorithms have been published for this problem, mostly aiming at partitioning the desired sti ness matrix in a pure algebraic manner. In this thesis, a new algorithm will be developed which considers the geometric property of the ngers and makes the method practical to robotics application. Some geometric properties of isotropic sti ness matrix (those that can be constructed by simple line springs) are observed. For instance, a novel reference frame invariant property of isotropic sti ness matrix is discovered. A \Background Mathematics" chapter will rstly explain the related mathematical tools and terminology used in subsequent chapters, leading to the de nition of contact kinematics and spatial sti ness. The concepts of these two items will be further illustrated with practical experimental examples in a following chapter. ii
Strategic corporate governance factors for municipally owned companies: an empirical analysis from a municipal perspective

Empirical research on municipally owned companies is still an under-researched field. In particular, there is a lack of sound empirical success factor-related studies that take into account the municipal mission of creating public value, as well as future-oriented strategic measures by which municipally owned companies can be directed from a municipal perspective. Therefore, this study examines strategic success factors that have an impact on the perceived success of municipally owned companies by investigating the responses from 271 qualified key informants using structural equation modelling. The analysis of the responses indicates that three factors (shared vision, strategic coordination and goal clarity) show a positive significant impact on the perceived success of municipally owned companies. In summary, the study provides insights to academics and public officials, and contributes to address the prevailing gap of empirical knowledge in the field. Points for practitioners The findings suggest that creating a shared vision and building a common understanding with their municipally owned companies concerning their goals, roles and duties is an important task for municipalities. Furthermore, the results indicate that municipalities that take an active part in their ownership role are more likely to experience enhanced municipally owned company success than others that instead rely on contractual agreements. Thus, creating a joint understanding of the intended strategy and operations seems more promising than creating excessive bureaucratic burdens.
The Impact of Tropical Storms on Households: Evidence from Panel Data on Consumption

This paper investigates the impact of tropical storms on Jamaican household consumption. We build a panel data set that follows individual households over time thus enabling us to take account of time invariant household and location unobservables that could be correlated with mean tropical storm exposure. Our results show that while the average damaging hurricane reduces per capita consumption by approximately 1.1%, more destructive events can cause losses multiple times this amount. There are, however, heterogeneous impacts across households, where only those that live in buildings with less wind resistant walls are affected. Additionally, we find that households are able to partially buffer the negative impact on consumption through remittances and savings, as well as by shifting funds away from non‐regular expenditures. Again, households differ in the nature of this buffering according to the wind resistance of their buildings.
Global Imbalances - Fractures in the world monetary system

The Global Imbalances that contributed to the financial crisis (2007-2010) are still present, and the world still has not fully recovered from recession. There is no consistent explanation of the Global Imbalances and their interaction with simultaneous events yet. The current state of the literature is that papers contradict each other and the main questions remain unsolved. This paper aims to provide a coherent story of the economic environment that laid the ground for the financial crisis, focusing on the evolution of Global Imbalances. It will reconcile the discrepancies of the different strands of existing literature and hypotheses. Hypotheses which can be rejected will be discarded. The paper will try to explain what mechanisms (inside and outside of the US) worked within these Imbalances, how they were motivated and if these mechanisms are sustainable. The single most important result will be that there is no obvious reason why China and the other emerging Asian economies finance the US. Further, the US finance themselves by means that are not fully understood yet and can only partially be explained. One important factor appears to be the use of the Exorbitant Privilege via Seigniorage. Other factors remain unknown.
Do Discounts in Ticket Prices Induce Sustainable Profit to Performing Arts Suppliers?

： This study investigates the effect of price promotions for musicals on consumer perception of fairness toward other similar musicals and the role of consumer involvement in performing arts as a moderating variable. A threshold regression estimation which was performed using data from a survey on South Korean consumers showed a decrease in consumers’ fairness perception once they became aware of discounts on similar performing arts and, consequently, a decrease in their intent to purchase tickets at regular prices. The results also showed that the samples can be split into low- and high-involvement groups, with the effect of fairness perception on purchase intention statistically significant for both groups, however, larger for the high-involvement group; the high-involvement group is expected to consume more performing arts products than the low-involvement group. These results imply that consumer perception of unfairness regarding ticket price discounts may negatively affect the long-term profits of performing arts suppliers.
Approaches for evaluation of novel CPP-based cargo delivery systems

Cell penetrating peptides (CPPs) can be broadly defined as relatively short synthetic, protein derived or chimeric peptides. Their most remarkable property is their ability to cross cell barriers and facilitate the translocation of cargo, such as drugs, nucleic acids, peptides, small molecules, dyes, and many others across the plasma membrane. Over the years there have been several approaches used, adapted, and developed for the evaluation of CPP efficacies as delivery systems, with the fluorophore attachment as the most widely used approach. It has become progressively evident, that the evaluation method, in order to lead to successful outcome, should concede with the specialties of the delivery. For characterization and assessment of CPP-cargo a combination of research tools of chemistry, physics, molecular biology, engineering, and other fields have been applied. In this review, we summarize the diverse, in silico, in vitro and in vivo approaches used for evaluation and characterization of CPP-based cargo delivery systems.
On the feasibility of simple brain-computer interface systems for enabling children with severe physical disabilities to explore independent movement

Introduction Children with severe physical disabilities are denied their fundamental right to move, restricting their development, independence, and participation in life. Brain-computer interfaces (BCIs) could enable children with complex physical needs to access power mobility (PM) devices, which could help them move safely and independently. BCIs have been studied for PM control for adults but remain unexamined in children. In this study, we explored the feasibility of BCI-enabled PM control for children with severe physical disabilities, assessing BCI performance, standard PM skills and tolerability of BCI. Materials and methods Patient-oriented pilot trial. Eight children with quadriplegic cerebral palsy attended two sessions where they used a simple, commercial-grade BCI system to activate a PM trainer device. Performance was assessed through controlled activation trials (holding the PM device still or activating it upon verbal and visual cueing), and basic PM skills (driving time, number of activations, stopping) were assessed through distance trials. Setup and calibration times, headset tolerability, workload, and patient/caregiver experience were also evaluated. Results All participants completed the study with favorable tolerability and no serious adverse events or technological challenges. Average control accuracy was 78.3 ± 12.1%, participants were more reliably able to activate (95.7 ± 11.3%) the device than hold still (62.1 ± 23.7%). Positive trends were observed between performance and prior BCI experience and age. Participants were able to drive the PM device continuously an average of 1.5 meters for 3.0 s. They were able to stop at a target 53.1 ± 23.3% of the time, with significant variability. Participants tolerated the headset well, experienced mild-to-moderate workload and setup/calibration times were found to be practical. Participants were proud of their performance and both participants and families were eager to participate in future power mobility sessions. Discussion BCI-enabled PM access appears feasible in disabled children based on evaluations of performance, tolerability, workload, and setup/calibration. Performance was comparable to existing pediatric BCI literature and surpasses established cut-off thresholds (70%) of “effective” BCI use. Participants exhibited PM skills that would categorize them as “emerging operational learners. ” Continued exploration of BCI-enabled PM for children with severe physical disabilities is justified.
Labor Markets and Business Cycles

Labor Markets and Business Cycles integrates search and matching theory with the neoclassical growth model to better understand labor market outcomes. Robert Shimer shows analytically and quantitatively that rigid wages are important for explaining the volatile behavior of the unemployment rate in business cycles. The book focuses on the labor wedge that arises when the marginal rate of substitution between consumption and leisure does not equal the marginal product of labor. According to competitive models of the labor market, the labor wedge should be constant and equal to the labor income tax rate. But in U.S. data, the wedge is strongly countercyclical, making it seem as if recessions are periods when workers are dissuaded from working and firms are dissuaded from hiring because of an increase in the labor income tax rate. When job searches are time consuming and wages are flexible, search frictions--the cost of a job search--act like labor adjustment costs, further exacerbating inconsistencies between the competitive model and data. The book shows that wage rigidities can reconcile the search model with the data, providing a quantitatively more accurate depiction of labor markets, consumption, and investment dynamics. Developing detailed search and matching models, Labor Markets and Business Cycles will be the main reference for those interested in the intersection of labor market dynamics and business cycle research.
Learning how to act: making good decisions with machine learning

This thesis is about machine learning and statistical approaches to decision making. How can we learn from data to anticipate the consequence of, and optimally select, interventions or actions? Problems such as deciding which medication to prescribe to patients, who should be released on bail, and how much to charge for insurance are ubiquitous, and have far reaching impacts on our lives. There are two fundamental approaches to learning how to act: reinforcement learning, in which an agent directly intervenes in a system and learns from the outcome, and observational causal inference, whereby we seek to infer the outcome of an intervention from observing the system. The goal of this thesis to connect and unify these key approaches. I introduce causal bandit problems: a synthesis that combines causal graphical models, which were developed for observational causal inference, with multi-armed bandit problems, which are a subset of reinforcement learning problems that are simple enough to admit formal analysis. I show that knowledge of the causal structure allows us to transfer information learned about the outcome of one action to predict the outcome of an alternate action, yielding a novel form of structure between bandit arms that cannot be exploited by existing algorithms. I propose an algorithm for causal bandit problems and prove bounds on the simple regret demonstrating it is close to mini-max optimal and better than algorithms that do not use the additional causal information.
Un espace de caractérisation pour l’édition de courbes à trois dimensions

La creation et l'edition de courbes 3D intervient dans de nombreux domaines d'application comme la CAO, l’edition de contenus spatio-temporels dans une video ou encore la generation de terrains et de routes. Cette diversite a conduit a une dispersion des travaux au sein de plusieurs communautes telles que SIGCHI ou SIGGRAPH. Cet article propose un espace de caracterisation visant a rassembler les techniques proposees pour la creation et l'edition de courbes 3D. Cet espace est decompose en deux axes: dispositif et langage afin de decrire et comparer les techniques existantes.
Multimodal Monolingual Comparable Corpus Alignment

Increased production of information materials like text or audio available (newspapers, radio, audio of television programs, etc.) requires the development of automated tools for tracking and navigation. It should be possible for example, when reading a newspaper article online, to access parts of radio emissions corresponding to the current reading. This fine navigation between different media requires the alignment of "Passages" with similar content within document extracts of different comparable monolingual modalities. Our work focuses on this alignment problem of short texts in a multimodal monolingual comparable context. The problem lies in finding similarities between short text and how to extract the features of these texts to help us find similarities for the alignment process. We contribute to this problem in three parts. The first part tries to define similarity which is the basis of the alignment process. The second part aims at developing a new text representation to facilitate the creation of the gold corpus on which alignment methods will be evaluated. Finally, the third contribution is to study different methods of alignment and the effect of its components on the alignment process. These components include different text representations, weights and similarity measures.
Developing an Approach to Harvesting, Cleaning, and Analyzing Data from Twitter Using R.

Using data from social media can be of great value to businesses and other interested parties. However, harvesting data from social media networks such as Twitter, cleaning the data, and analyzing the data can be difficult. In this article, a step-by-step approach to obtaining data via the Twitter application program interface (API) is described. Cleaning of the data and basic sentiment analysis are also described.