Miracle-dz/UniFAR-FTUs huggingface dataset:
Derivation for Mass–Frequency Relationship of a Quartz Crystal Microbalance Based on an Equivalent Circuit Network Analysis Method

Saurbrey equation has solved frequency dependence on mass change for a rigid film on a quartz crystal microbalance device. Does it hold true for any rigid film that is deposited on a quartz crystal microbalance? A new expression for the mass–frequency relationship of a quartz crystal microbalance device is derived based on equivalent circuit network analysis combined with physical properties of the quartz crystal. Compared to Sauerbrey equation, the proposed expression is derived without applying any approximations. Theoretical analysis is validated with finite-element analysis and experimental test. The results demonstrate that frequency shift of a quartz crystal microbalance is related not only to mass of the deposited addition but also density of the deposited addition. This work is significant to supplement and extend the theory of quartz crystal microbalance.
Is there an abundance anomaly for the 2.2 eV FeI lines in the solar spectrum

L'etude des raies Fe I dans le spectre solaire en utilisant les forces d'oscillateur d'Oxford montre que l'abondance solaire moyenne pour huit raies de 2,2 eV est d'environ 16% plus faible que celle de toutes les raies entre 0 eV et 2,6 eV. De nouvelles mesures semblent confirmer cette anomalie
Exploring SME’s behavioural changes resulting from innovation policy: the effect of receiving a subsidy on intrapreneurship

ABSTRACT Intrapreneurship is critical for small to medium-sized enterprises (SMEs), in that it enhances innovation and organizational performance. This study details how intrapreneurship develops in subsidized relative to unsubsidized SMEs. We build on behavioural additionality research, as these studies examine changes in firm behaviour that occur after the firm receives public support. Prior studies focus on the effect on external collaboration, but subsidies also can lead to organizational learning and upgraded competencies, implying the potential for changes to organizational routines. Our test of the behavioural additionality effect relies on an original longitudinal data set involving manufacturing SMEs in the Dutch province of Limburg. The data analysis combines propensity score matching with a difference-in-difference approach, which reveals a significantly higher increase in one aspect of intrapreneurship, namely strategic renewal behaviour, among SMEs that receive an innovation subsidy. The findings advance understanding of intrapreneurship and behavioural additionality effects and provide policy makers with new evidence of the added value of subsidy programmes.
Adjustable-Loop Cortical Suspensory Fixation Results in Greater Tibial Tunnel Widening Compared to Interference Screw Fixation in Primary Anterior Cruciate Ligament Reconstruction

Background: Although the use of adjustable-loop suspensory fixation has increased in recent years, the influence of the shortcomings of suspensory fixation, such as the bungee-cord or windshield-wiper effects, on tunnel widening remains to be clarified. Hypothesis/Purpose: The purpose of this study was to compare adjustable-loop femoral cortical suspensory fixation and interference screw fixation in terms of tunnel widening and clinical outcomes after anterior cruciate ligament reconstruction (ACLR). We hypothesized that tunnel widening in the adjustable-loop femoral cortical suspensory fixation (AL) group would be comparable to that in the interference screw fixation (IF) group. Methods: This study evaluated patients who underwent primary ACLR at our institution between March 2015 and June 2019. The femoral and tibial tunnel diameters were measured using plain radiographs in the immediate postoperative period and 2 years after ACLR. Tunnel widening and clinical outcomes (Lysholm score, 2000 International Knee Documentation Committee subjective score, and Tegner activity level) were compared between the two groups. Results: There were 48 patients (mean age, 29.8 ± 12.0 years) in the AL group and 44 patients (mean age, 26.0 ± 9.5 years) in the IF group. Tunnel widening was significantly greater in the AL group than that in the IF group at the tibia anteroposterior (AP) middle (2.03 mm vs. 1.32 mm, p = 0.017), tibia AP distal (1.52 mm vs. 0.84 mm, p = 0.012), tibia lateral proximal (1.85 mm vs. 1.00 mm, p = 0.001), tibia lateral middle (2.36 mm vs. 1.03 mm, p < 0.001), and tibia lateral distal (2.34 mm vs. 0.85 mm, p < 0.001) levels. There were no significant differences between the two groups with respect to femoral tunnel widening and clinical outcomes. Conclusions: Tibial tunnel widening was significantly greater in the AL group than in the IF group at 2 years after primary ACLR. However, the clinical outcomes in the two groups were comparable at 2 years.
Compression of protein conformational space

Compressing conformational space is the process of defining a subspace of minimal dimensionality where any point may represent a protein-like structure. This is similar to the problem of image compression, where it is desired to reconstruct an image from a small amount of information. In this case, the similarity (in atomic detail) between a true protein and the protein like structure obtained by projecting the compressed protein back into real space is the measure of the success of the compression algorithm. If proteins may be accurately compressed to a space that is efficiently searchable, and then decompressed back to real space, existing energy functions that use atomic detail may finally be rigorously tested in an exhaustive conformational search. (Note: Unlike in the threading approach, such an exhaustive simulation search may consider the folding pathway, and therefore the folding kinetics.) In this paper, we apply compression techniques to various representations of the proteins of known structure. We apply principle component analysis (PCA) to the coordinate, backbone angle, and distance matrix representations. Additionally, we applied Fourier transform techniques to distance matrix space. The success of the compression was measured by the structural difference between the original and the reconstructed coordinates for proteins that were not used in the development of the compression algorithm. It is found that some representations of the model are more easily compressed that others. We find, unexpectedly, that the models that retain the most atomic detail may be compressed to the smallest subspace. Compressing Protein Conformational Space
Optimized and Efficient Authentication in VANET using Blockchain

Vehicle ad hoc networks (VANETs) are the most exciting area of research in smart transport systems as they provide convenience and safety information to drivers. However, VANET's unique features make security, privacy, and trust management promising issues in the design of VANETs. It is a challenging problem to provide an effective anonymous authentication system in ad hoc vehicle networks (VANETs) with low computational cost. Blockchain technology in VANET offers a decentralized, secure, and reliable database, which is maintained by the network node. Earlier, vehicle authentication is performed whenever the vehicle enters the RSU range. In this paper, authentication will be done if a vehicle fails to travel a certain distance. This decreased number of authentications and time required for it leads to an increase in the efficiency of the system.
Understanding of surface reflections in computer vision by color and multiple views

This thesis addresses problems and presents models for the detection and separation of specularities from Lambertian reflections using color and multiple images with different viewing directions. From the models, three algorithms are proposed and experimental results are presented. The first algorithm uses only color information for the separation of diffuse as well as sharp specularities and inter-reflections from Lambertian reflections through image segmentation. A computational model based on the dichromatic model is presented for interpretation of various surface reflections in a spectral space with three orthogonal basis functions. The established model is used for arranging color data for segmentation and separation. Applicable objects and illumination for the algorithm are limited to uniformly colored dielectrics under singly colored scene illumination. Use of multiple views for understanding reflection properties is proposed with the second and the third algorithms called spectral differencing and view sampling, respectively. Both use multiple views in different viewing directions, and are based on the Lambertian consistency that image irradiance from Lambertian reflection does not vary depending on viewing directions while image irradiance from specular reflection does. Spectral differencing is a detection algorithm that detects specularities by color difference between two images without any geometrical correspondence. The object domain for detection is extended to nonuniformly colored dielectrics and metals under multiply colored scene illumination. As a detection algorithm, spectral differencing can be used with the image segmentation algorithm for more stable performance. With densely sampled views in wide angle and with known viewing directions, the view sampling algorithm reconstructs object structure as well as separates specularities from Lambertian reflections. The view sampling algorithm does not require color information, and is applicable to dielectrics and metals. Experimental results agree well with the models and algorithms within the limitations discussed.
Estimation of remaining fatigue life with an energy-based model considering the effects of loading sequence and load interaction

Accurate estimation of remaining fatigue life is crucial to assess the structural durability and reliability of engineering components. For this purpose, an energy-based model is proposed in this paper for modeling the process of fatigue damage accumulation under multistep loading. To account for the effects of loading sequence and load interaction, two parameters, a concept of normalized fatigue driving energy (NFDE) and a load interaction factor, are introduced in the model. The former is based on variable energy-life curves and the latter is formulized as an exponential function of the loading intensity ratio and the number of loading cycles. The implementation procedure of such model only requires the loading information and materials’ basic fatigue properties. Moreover, extensive experimental results of six metallic materials under two-, four- and eight-step loadings with different loading sequences are employed for model comparative study. The results indicate that, compared with several existing damage models, the proposed model can provide better remaining fatigue life estimations under multistep loading.
Effect of Clover Sward Management on Nitrogen Fixation and Performance of Following Spring- and Winter Wheat Crops; Results of a 3-Year Pilot Study

Wheat yields in organic production are significantly lower than those achieved in conventional farming systems and in Northern Europe organic farmers also struggle to achieve the processing quality levels demanded by millers and bakers, especially in winter-wheat crops. Here, we report the findings of a 3-year pilot study which investigated the potential of increasing grain yields and both standard processing (e.g., grain protein levels and specific weights) and selected nutritional (tocopherol and tocotrienol isomers) quality parameters via (i) changes in the management of clover crops grown before wheat (Rhizobium seed inoculation, application of greenwaste compost to clover swards) and (ii) use of new varieties developed in both the UK and continental Europe. Results indicate that the use of compost amendment to preceding clover swards significantly increased the grain protein levels in the three winter-wheat, but not the four spring-wheat varieties, and also significantly increases grain yields in one winter-wheat variety (Greina). In contrast, the use of Rhizobium-inoculation was found to significantly reduce protein concentrations in the winter-, but not spring wheat varieties, and had no significant effect on grain yields in both winter and spring wheat. However, analysis of variance detected significant interactions between Rhizobium seed inocula in clover pre-crops and (a) compost application for grain specific weights in winter-wheat and grain hardness in spring wheat crops and (b) variety for grain protein content in spring wheat crops. No significant effect of clover pre-crop management on tocopherol and tocotrienol isomer profiles could be detected, although significant differences between varieties were detected in both winter and spring wheat. Results of this pilot study need to be confirmed in future trials, but indicate that both (a) changes in clover-management practices and (b) the selections of wheat varieties that are more suitable for organic farming systems has the potential to increase grain yield and allow organic farmers to more frequently achieve baking or milling grade quality.
General parameter control framework for evolutionary computation

This study proposes a general multiple parameter control framework by leveraging the ability of a reinforcement learning system to learn empirical knowledge for evolutionary computation. We design a feedback evaluation mechanism to define the rewards offered to agents, using which they can learn to choose appropriate parameters in formulated action sets. Moreover, a learning strategy is proposed to utilize the parameter selection‐related knowledge that is gained during training episodes. Three famous evolutionary computation (EC) methods (i.e., particle swarm optimization, artificial bee colony, and differential evolution) are selected as the baseline algorithms and applied to the proposed framework. The aforementioned redesigned algorithms are tested on 15 common benchmark functions, as well as the CEC2017 benchmarks. In addition, the robustness of the algorithms is demonstrated through parameter sensitivity analysis. The results of the comparative analysis reveal that the three improved algorithms exhibit a faster overall convergence and higher accuracy than their state‐of‐the‐art variants. It is also confirmed that our proposed framework has the capability to improve the performance of EC approach.
A Relativistic Light Speed Maximum for Escape Velocity

This paper now appears the |Journal of High Energy Physics, Gravitation and Cosmolgy| at http://www.scirp. org/journal/paperinformation.aspx? paperid=68063 The escape velocity equation shows mathematical parallels between General Gravitational Relativity & Special Relativity Time distortions. Like the light-speed limit that SR puts to Real velocity, GR puts a parallel limit to escape velocity. Time Distortion would mean all Bosons are slowed. There is a mathematic argument that General Relativity Graviton slowdown leads to that escape velocity limit – the fundamental escape velocity from any body will never be greater than light speed. The principal equation introduced in this paper is a rephrased GR Time equation. The Escape velocity equation |vesc=(2GM/r)^½| can also be as written |vesc^2=(2GM/r)|. So |1 – 2GM/rc^2| can be re-expressed as |1 – vesc^2/c^2|. It is reasoned the expression will never have a zero value, only a Graviton||Boson slowdown. Time passage would never cease; only approach cessation. Time slowdown predicted by Relativistic distortion is confirmed by muon decay. The different phrasing of the Gravitational Force equation |F=GMm/r^2| would mean a limitless gravitational force. While Bosons compression would be unlimited, any matter could escape after formation absorbing sufficient kinetic energy from slowing Photons||Bosons. This reasoning is illustrated by calculating Classic Relativity interpretations for distortions for Sagittarius A [SA] body at the center of the Milky Way.
Integrated computational imaging system for enhanced polarimetric measurements

Polarimetry is a common technique used in chemistry for solution characterization and analysis, giving insight into the molecular structure of a solution measured through the rotation of linearly polarized light. This rotation is characterized by the Boits law. Without large optical path lengths, or high concentrations of solution, these optical rotations are typically very small, requiring elaborate and costly apparatuses. To ensure that the rotation measurements are accurate, these devices usually perform complex optical procedures or time-averaged point measurements to ensure that any intensity variation seen is a product of optical rotation and not from inherent noise sources in the system, such as sensor or shot noise. Time averaging is a lengthy process and rarely utilizes all of the information available on the sensor. To this end, we have developed a novel integrated, miniature, computational imaging system that enhances polarimetric measurements by taking advantage of the full spot size observed on an array detector. This computational imaging system is capable of using a single acquisition at unity gain to enhance the polarimetric measurements using a probabilistic framework, which accounts for inherent noise and optical characteristics in the acquisition process, to take advantage of spatial intensity relations. This approach is faster than time-averaging methods and can better account for any measurement uncertainties. In preliminary experiments, this system has produced comparably consistent measurements across multiple trials with the same chemical solution than time averaging techniques.
Reduced Rank Regression Using Generalized Method of Moments Estimators with Extensions to Structural Breaks in Reduced Rank Models

Generalized Method of Moments (GMM) Estimators are derived for Reduced Rank Regression Models, the Error Correction Cointegration Model (ECCM) and the Incomplete Simultaneous Equations Model (INSEM). The GMM (2SLS) estimators of the cointegrating vector in the ECCM are shown to have normal limiting distributions. Tests for the number of unit roots can be constructed straightforwardly and have Dickey-Fuller type limiting distributions. Two extensions of the ECCM, which are important in practice, are analyzed. First, cointegration estimators and tests allowing for structural shifts in the variance (heteroscedasticity) of the series are derived and analyzed using a Generalized Least Squares Estimator. Second, cointegrating vector estimators and tests are derived which allow for structural breaks in the cointegrating vector and/or multiplicator. The resulting cointegrating vectors estimators have again normal limiting distributions while the cointegration tests have limiting distributions which differ from the standard Dickey-Fuller type.
Causations or payoffs? The interaction between countries’ economic results and competing proxies of social capital

The repository of literature studying the relationship between economic indicators and social capital through traditional surveys data is growing. At the same time, the emergence of social networks has created competing big data that require in-depth analysis and comparison of results. The aim of this research is to analyze the interaction between countries’ economic outcomes and proxy indicators of social capital, considering and comparing the traditional data of surveys and Facebook’s data of social connectedness index. Correlation analysis, Granger and Dumitrescu Hurlin Panel Causality tests, Ordinary Least Squares (OLS) regression methods of analysis on panel and cross-country data are used to show that countries’ GDP per capita indicator is a cause for higher social capital, while social connectedness indicators explain only a very small part of the GDP per capita indicator. It is also shown that institutional trust and networks elements of social capital are the most influential and statistically significant explaining variables of GDP per capita (in case of the latter variable, the connection is two-sided). The scientific contribution of this study is that it brings research growing in two different directions into one dimension. The results of the analysis are also of practical importance for public policy development, social media companies and the buyers-users of their data.
Farming Performance can be Estimated using Blockchain Technology

On a wireless blockchain-based network, a sustainable smart farm with noise signal or noise signal with the ratio (SIR/SNR) to be employed as the optimal relay has already been addressed. During the uninterrupted selection of the optimal relay performance, the transmission success rate (TRS), overall communication throughput (OCT), power splitting relaying (PSR), and time switching relay (TSR) are also output. As the number of potential relay nodes increases, the performance of TRS, OCT, PSR, and TSR all improve. Numerical simulations were used to verify the validity of the theoretical values' strength.
SISTEMA BCI QUE PERMITA EL CONTROL DE UN EXOESQUELETO DE MIEMBRO INFERIOR A TRAVÉS DEL PROCESAMIENTO DE SEÑALES ELECTROENCEFALOGRÁFICAS

Eneste artículo se propone el control de un exoesqueleto de miembro inferior, a través del procesamiento de las señales electroencefalográficas (EEG), utilizando técnicas de imaginación motora (MI). Para esto, la señal EEG fue adquirida por medio de una interfaz cerebro computador (BCI) utilizando el sistema Nautilus16. Para ello, se hace uso de un exoesqueleto a escala de miembro inferior con dos grados de libertad, basado en el modelo de un CPWalker diseñado y fabricado en el programa de Ingeniería Electrónica de la Universidad del Quindío. Para el control del exoesqueleto, se implementó una máquina de vector de soporte (SVM), utilizando el kernel de Función de Base Radial (RBF), el cual permite identificar la intención de movimiento (miembro derecho o Izquierdo), a partir del análisis de los ritmos motores cerebrales. Finalmente, para generar el movimiento en el exoesqueleto se hace uso de una interfaz serial, la cual comunica el entorno de desarrollo de Python con una tarjeta Arduino Uno, donde se envían los comandos de control a los motores del exoesqueleto, conforme a la respuesta generada por el modelo de clasificación. Para evaluar el prototipo, se realizaron una serie de pruebas piloto con dos usuarios totalmente sanos, con un rango de edad de 22 a 25 años. Las señales EEG de los participantes, fueron filtradas, segmentadas y procesadas de acuerdo a los parámetros de entrenamiento del modelo generado, obteniendo resultados de exactitud del 91%.