Miracle-dz/UniFAR-FTUs huggingface dataset:
Economías de aglomeración, sistemas de transporte público masivo tipo BRT (Bus Rapid Transit) y decisiones de ubicación geográfica de empresas

Resumen La literatura asociada con las Economías de Aglomeración se ha ocupado tradicionalmente de la relación entre el desarrollo económico y el desarrollo urbano de las ciudades, incluyendo a las organizaciones como objeto de estudio. Este artículo busca revisar la literatura acerca de la posible relación de causalidad entre los flujos de capital generados por las decisiones de localización de las empresas y la oferta de servicios se transporte tipo BRT. Dado el tema del trabajo doctoral que generó esta revisión, estas propuestas son analizadas en comparación con los resultados de la investigación enunciada, encontrándose particularidades para la ciudad de Bogotá que pueden complementar los postulados tradicionales de la literatura, permitiendo que este hecho se proponga como argumento para resaltar la necesidad de llevar a cabo estudios de validación empírica que permitan discutir y complementar el cuerpo teórico disponible al respecto. Como aporte principal se resalta la identificación de algunos vacíos teóricos y de comprobación empírica sobre el análisis y comprobación de los posibles efectos de las inversiones en los sistemas de transporte público masivo tipo BRT en las decisiones estratégicas de ubicación geográfica de las empresas, situación a la que este artículo pretende aportar.
The Impact of Economic Complexity on the Formation of Environmental Culture

This paper establishes economic complexity as a powerful predictor of environmental attitudes. While the economic complexity index (ECI) has been associated with a series of economic outcomes, yet there has not been a link in the literature between ECI and environmental attitudes. This research pushes forward the hypothesis that economic complexity shapes cultural values and beliefs. The research method used is a multilevel empirical analysis that associates aggregate values of the ECI, at the country level, with individual responses related to attitudes towards the environment. Our findings suggest that a marginal increase of the ECI, increases by 0.191 the probability to be a member of environmental organisations and an increase by 0.259 in the probability to engage in voluntary work for the environment. To further reinforce our findings by ensuring identification we replicate the benchmark analysis using as a proxy of a country’s level of economic complexity, the average ECI of the neighbouring countries (weighted by population and/or volume of trade). With a similar intention, i.e., to mitigate endogeneity concerns as well as to further frame our findings as “the cultural implications of ECI” we replicate our analysis with a sample of second generation immigrants. The immigrant analysis, suggests that the level of economic complexity of the parents’ country of origin, has a long-lasting effect on second generation immigrants’ attitudes related to the environment. Because humankind’s attitudes and actions are of key importance for a sustainable future, a better understanding as to what drives environmental attitudes appears critical both for researchers and policy makers.
Decision Trees in Large Data Sets

Data mining is the process of obtaining information, which is used to identify and define the relationships between data of different qualities. One of the important problems encountered in this process is the classification process in large data sets. Extensive research has been done to find solutions to this classification problem and different solution methods have been introduced. Some decision tree algorithms are among the structures that can be used effectively in this field. In this article, various decision tree structures and algorithms used for classification process in large data sets are discussed. Along with the definitions of the algorithms, the similarities and existing differences between them were determined, their advantages and disadvantages were investigated.
Joint Replacement Registries Significantly Reduce Revision Rates

BackgroundDespite the rapid establishment of joint replacement registries (JRR), its effect on key outcomes such as revision rates is uncertain. While some countries with JRR have recorded reductions in revision rates, other countries without JRR also have reported similar reductions. This study evaluated the impact of JRR on revision rates across countries while controlling for non-JRR related factors and JRR outcomes transfer (to non-registry countries) that could contribute to reduction in revision rates. MethodsThis assessment was performed by a difference-in-differences statistical approach using a panel regression model. We compared revision rates of non-registry countries to registry countries, and further compared non-registry period revision rates to registry period (of registry countries) revision rates. We controlled for non-JRR related factors and JRR outcomes transfer by the inclusion of a linear trend in the model. Data were collected from 1980 – 2018. Registry data were obtained from JRR databases while non-registry data were obtained from literature search in Medline and Google Scholar. ResultsThe average difference in revision rates between registry countries compared to non-registry countries was not statistically significant for hip (p-value = 0.056) and knee (p-value = 0.501) respectively. The average difference in revision rate in the registry period of registry countries relative to the non-registry periods was statistically significant for hip (p-value < 0.0001) and knee (p-value = 0.004) respectively. The impact of JRR on revision rate reduction as a percentage was 19.23% (95% CI: 10.86 – 31.55%) and 13.07% (95% CI: 3.28 – 31.18%) for hip and knee respectively. ConclusionsJoint replacement registries cause significant reduction in revision rates and its effect on this outcome may be further improved by increasing surgeons’ participation. Establishment of JRR in countries or regions yet to would be a worthwhile decision.
Comparative Evaluation of Voltage Source Converters With Silicon Carbide Semiconductor Devices for High-Voltage Direct Current Transmission

Recent advancements in silicon carbide (SiC) power semiconductor technology enable developments in the high-power sector, e.g., high-voltage-direct-current (HVdc) converters for transmission, where today silicon (Si) devices are state-of-the-art. New submodule (SM) topologies for modular multilevel converters offer benefits in combination with these new SiC semiconductors. This article reviews developments in both fields, SiC power semiconductor devices and SM topologies, and evaluates their combined performance in relation to core requirements for HVdc converters: grid code compliance, reliability, and cost. A detailed comparison of SM topologies regarding their structural properties, design and control complexity, voltage capability, losses, and fault handling is given. Alternatives to state-of-the-art SMs with Si insulated-gate bipolar transistors (IGBTs) are proposed, and several promising design approaches are discussed. Most advantages can be gained from three technology features. First, SM bipolar capability enables dc fault handling and reduced the energy storage requirements. Second, SM topologies with parallel conduction paths in combination with SiC metal–oxide–semiconductor field-effect transistors offer reduced losses. Third, a higher SM voltage enabled by a higher blocking voltage of SiC devices results in a reduced converter complexity. For the latter, ultrahigh-voltage bipolar devices, such as SiC IGBTs and SiC gate turn-off thyristors, are envisioned.
Nuclear Magnetic Resonance Spectroscopy of RNA

High-resolution structure has been a missing element in our understanding of RNA function. Advances in crystallographic and nuclear magnetic resonance (NMR) methodologies have led to a growing number of high-resolution structures in recent years (Varani and Pardi 1995). Here, we review the application of NMR spectroscopy to RNA structure determination. Practical aspects of a successful NMR study are highlighted, including system design, synthesis of RNAs for NMR, up-to-date methods for spectral analysis and interpretation, and calculation of RNA structures from NMR data. For definitions of the various terms in NMR spectroscopy, the reader is referred to Homans (1992). What NMR can tell us about RNA structure is illustrated by recent NMR studies of RNA. THEORY NMR is a spectroscopic method that probes the spin states of nuclei. In the presence of a magnetic field, these spin states have different energies such that transitions between the states can be monitored. Nuclei with spin = 1/2, such as 1 H, 31 P, 15 N, and 13 C, have two energy levels in the presence of a magnetic field, which gives the simplest spectroscopic behavior. The latter two isotopes, although not significantly present at natural abundance, can be incorporated into RNAs and proteins at close to 100% abundance using synthetic and biosynthetic methods. The energy-splitting between the two energy states in 1 H NMR is small compared to the splitting between electronic energy levels (UV spectroscopy) and directly proportional to the magnetic field strength; in the presence of an 11.7 Tesla field, the energy-splitting corresponds to a frequency.
Hydropower affects fish trophic structure both downstream of the dam and upstream of the reservoir

Dams often cause drastic changes in freshwater environments and can compromise the quality and availability of food resources in rivers. This study aims to analyze the influence of a dam on the trophic structure of fish assemblages in lotic areas located both upstream and downstream of the Irapé Hydroelectric Power Plant. Fish sampling occurred before (2003 to 2005) and after (2011 to 2017) the impoundment, which began in 2006. The trophic structure and species composition before dam construction were similar upstream of the reservoir and downstream of the dam. After the building of the dam, both aspects of the assemblages changed along the lotic stretches – the upstream incurred an increase in biomass of detritivores and a decrease of piscivores and omnivores, while downstream went exactly the opposite, causing a differentiation between the two assemblages. Because lotic areas upstream of reservoirs are also impacted by river damming, efforts for impact mitigation should also focus on these areas.
Symmetry and nonexistence of positive solutions for an elliptic system involving the Fractional Laplacian

Abstract In this paper, we study a nonlinear elliptic system involving a fractional Laplacion: where 0 < α < 2, p, q > 0 and max{p, q} ≥ 1, τ ≥ 0, n ≥ 2. There are two cases to be considered. The first one is where the domain is bounded, and the second one is where the domain is the whole space. First of all, we consider the above system in the star-shaped and bounded domain Ω, by using the Pohozaev identity. We prove the nonexistence of a positive solution in the critical and supercritical case p + q + 1 ≥ . In addition, we show that the positive solutions of the above system are radially symmetric and decreasing about the origin by using the method of moving planes in ℝ n. Moreover, while in the subcritical case , we prove the nonexistence of a positive solution for the above system in ℝ n . Then, through the doubling lemma we obtain the singularity estimates of the positive solutions on a bounded domain .
A Comprehensive Review on Medical Diagnosis Using Machine Learning

: The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high accuracy. The use of machine learning could assist the doctors in making decisions on time, and could also be used as a second opinion or supporting tool. This study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various diseases. We present the various machine learning algorithms used over the years to diagnose various diseases. The results of this study show the distribution of machine learning methods by medical disciplines. Based on our review, we present future research directions that could be used to conduct further research.
EFFECTIVE STRESS PRINCIPLE IN MODELLING SHRINKAGE AND CREEP OF CONCRETE AT EARLY AGES AND BEYOND

In this work a novel numerical model of hygro-thermal and hydration phenomena in concrete at early ages and beyond is presented. This is a solidification-type model where all changes of material properties are expressed as functions of the hydration degree, and not the maturity nor equivalent hydration period as in the maturity-type models. A mechanistic approach, typical in the mechanics of porous media, was used to obtain the governing equations, by means of a hybrid mixture theory. The final equations, mass (water species and dry air), energy and momentum balances are written in terms of the chosen primary variables: gas pressure, capillary pressure, temperature and displacements. The model [1-3] takes into account full coupling between hygral, thermal and chemical phenomena, as well as changes of concrete properties caused by hydration process, i.e. porosity, density, permeability. Phase changes and chemical phenomena, as well as the related heat and mass sources are considered. For a more detailed description of the mathematical model, the governing equations and the constitutive relationships, see [1-3]. Kinetics of cement hydration is described by means of an evolution equation which relates the internal variable, hydration degree, with the hydration rate through the chemical affinity. The latter one is considered as the driving force of the chemical reaction, [1-3].
Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.
A Cavity-Backed Patch Antenna With Distributed Multi-Port Feeding, Enabling Efficient Integration With Doherty Power Amplifier and Band-Pass Filter

A joint design approach for cointegrated antenna and power amplifier (PA), employing a high-efficiency Doherty PA (DPA) architecture and including a bandpass RF filter, is proposed. This design is realized through the optimally distributed and balanced multiport feeding of the cavity-backed patch antenna element that provides the desired (unique) loading conditions for the main and auxiliary PA branches and tailored power combining. A novelty and advantage of this feeding solution is that each pair of feeding points forms a virtual common feeding center of the radiating element; as a result, the radiation pattern remains power invariant when the port excitations change. A joint optimization of the integrated antenna-DPA transmitter is carried out to enhance the overall performance and maximize the bandwidth. This optimization is demonstrated through an example design for the sub-6 GHz telecommunication applications that target high power efficiency (>50%) at the 6 dB backed-off power levels and require RF-filtering in a compact integrated design. The latter challenge leads to a nonconventional implementation, which generally does not require the filter to be inserted between the antenna and the final output stage of the PA, and can be embedded in the topology with complex-valued source/load impedance values. The results of numerical studies are supported by measurements obtained with the antenna-DPA-filter prototype system.
Perspective of Competitive Advantage in Services Dominant Logic

The process of marketing activities is the process of transactions occurring between producers and consumers, where producers market to consumers. The development of a globally connected world environment has resulted in a level of competition between companies not only on a domestic scale but also becoming global. The competition requires different perspectives both theoretically and practically to be able to provide the best for consumers so that companies can continue to exist in the long run and are not easily imitated by competitors or have competitive advantage. Marketing as an economic exchange model initially had a dominant logic based on the exchange of products or known as Goods-Dominant logic. Good- Dominant Logic focuses on the separation between producers and consumers and this is still used. It aims to maximize production control, efficiency, and profit maximization. This is usually achieved by standardizing products and producing them far from the market. Vargo and Lusch (2004) introduce a new dominant logic that is different from the goods-dominant logic. Dominant-logic focuses on the interaction between producers, consumers, and partners in the bidding network and the creation of value as parties who co-create through the process of collaboration. This logic is known as Service-Dominant logic. Service-Dominant logic arises because of the impetus of the initial goal to do something for and with other parties better known as customer centric and customer responsive. In this logic, services are defined as the application of competencies through actions, processes and performance that are beneficial to other entities and the entities themselves. This can increase the company's strength to satisfy consumer needs and achieve organizational and social goals. In this case the company can be said to have the power to compete through services. And competition through services is more than adding value to the product. Effective competition through services must be carried out with the views and approaches of all parties in the organization aimed at providing satisfaction to consumers (Lusch et al., 2007). In short, it can be said that service-dominant logic becomes the philosophical foundation for service science and service systems as the basis of theoretical constructs (Maglio and Spohrer, 2007). This research explains the new dominant logic, how changes in perspective occur, and how new can become conceptual based on the service science that producers try to provide or offer to consumers, and this becomes a competitive force and implications for business.
Insomnia among medical students and its association with exams

Background: Insomnia is a sleep disorder associated with several significant daytime consequences such as fatigue, low mood, lack of energy, and daytime sleepiness. Medical students appear to be more prone to developing sleep-related problems potentially due to long study years in college and a stressful lifestyle. The primary objective of the present study was to determine the association between exams and insomnia among medical students at King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia. In addition, it also aimed to determine the association between naps, sleep medications, medical conditions, and insomnia. Methods: This cross-sectional study was conducted among male medical students at KSAU-HS, Riyadh. Students were surveyed using the Insomnia Severity Index to evaluate the prevalence of insomnia 2 weeks prior to exams and 2 weeks after exams. Results: A total of 367 medical students were included. The prevalence of insomnia before and after exams were 32.9% (n = 49) and 27.1% (n = 59), respectively. The association between insomnia and exams was not statistically significant (p = 0.27). A total of 47.25% of the students reported taking naps and 5.96% took sleep medications. Napping and medical conditions affecting sleep did not significantly influence students’ quality of sleep. There was a significant association between insomnia and sleep medications (p = 0.006). Conclusions: The prevalence of insomnia among medical students in the present study was similar to other studies. Insomnia among medical students was not related to exams. Furthermore, taking sleep medications such as melatonin and antihistamines was associated with insomnia. More than half of the students who took sleep medications had insomnia, while only one-quarter of the students who did not take sleep medications had insomnia.
Hydrogen transport through stainless steel under plasma irradiation

The paper presents the results of investigation of gas exchange through stainless steel surface of the plasma chamber under irradiation with hydrogen atoms in oxygen atmosphere or oxygen contaminated hydrogen plasma. Dependence of this process on various irradiation parameters, such as the metal temperature, energy of irradiating ions, gas composition of plasma are studied. It is shown, that desorption from stainless steel is activated with the increase of the plasma chamber walls temperature and energy of irradiating ions. Hydrogen release occurs also under irradiation of the walls by helium and argon plasmas added with oxygen, however the amount of released hydrogen is several times lower than in the case of irradiation with oxygen contaminated deuterium plasma.
Separated Random Linear Network Coding Based on Cooperative Medium Access Control

A separated random linear network coding (SRLNC) technique that separately transmits a coding coefficient (CC) and a coded packet (CP) in different frames is proposed based on cooperative control frames in distributed relay networks. SRLNC technique can improve retransmission performance by reducing retransmission overhead, because either the CC or CP is retransmitted, whereas conventional RLNC retransmits the CC and CP simultaneously. The throughput performance is also analyzed to investigate the impact of additional cooperative control frames, because SRLNC requires little additional cooperative control frames. The simulation results show that the proposed scheme outperforms the conventional RLNC in distributed relay networks.