Miracle-dz/UniFAR-FTUs huggingface dataset:
Price dependence of biofuels and agricultural products on selected examples

The growing demand for raw materials for the production of biofuels may lead to an increase in the prices of these raw materials and, due to the shortage of land, to an increase in the prices of other crops. This is due to the fact that the growing demand for raw materials for the production of methyl esters and bioethanol (the most widely used biofuels), such as rape and corn, is a form of competition on the food and feed markets. It should be mentioned that although the topic is not new, it is still very relevant, taking into account the expansion of energy crops, as well as national, European and world energy policy. Especially due to the fact that, as has already been mentioned, the use of plant products for the production of biofuels has an impact on the regulations of the food market.This study is to analyze the volatility and dependence of ethanol, biodiesel, maize and rapeseed prices in the period of 2016-2019 and aims at assessing the correlation between the agricultural and biofuel markets. In this paper, the investigation regarding co-integration of biofuel and agricultural commodity prices has utilized ethanol and commodity prices with the use of the vector error correction model (VECM). Price dependencies between the prices of biodiesel, rapeseed, maize and ethanol were found, indicating the existence of long-term causality in at least one direction between the analyzed prices. The results indicated that biodiesel prices during the period in question were influenced by the previous week’s prices of biofuel and rapeseed. Moreover, biodiesel prices had an impact on the level of ethanol and rapeseed prices. In the case of rapeseed, the correlation between its prices and those of corn is also noticeable, while prices of corn may also affect prices of ethanol.
Automated Embedded Payment Systems

Payment industry is largely aligned in their desire to create embedded payment systems ready for the modern digital age. The trend to embed payments into a software platform is often regarded as first step towards a broader trend of embedded finance based on digital representation of fiat currencies. Since it became clear to our research team that there are no technologies and protocols that are protected against attacks of quantum computing, and that enable automatic embedded payments, online or offline with no fear of counterfeit, P2P or device-to-device to be made in real time without intermediaries, in any denomination, even continuous payments per time or service, while preserving the privacy of all parties, without enabling illicit activities, we decided to utilize the Generic Innovation Engine [1] that is based on the Artificial Intelligence Assistance Innovation acceleration methodologies and tools in order to boost the progress of innovation of the necessary solutions. These methodologies accelerate innovation across the board. It proposes a framework for natural and artificial intelligence collaboration in pursuit of an innovative (R&D) objective The outcome of deploying these Artificial Innovation Assistant (AIA) methodologies was tens of patents that yield solutions, that a few of them are described in this paper. We argue that a promising avenue for automated embedded payment systems to fulfil people’s desire for privacy when conducting payments, and national security agencies demand for quantum-safe security, could be based on DeFi and digital currencies platforms that does not suffer from flaws of DLT-based solutions, while introducing real advantages, in all aspects, including being quantum-resilient, enabling users to decide with whom, if at all, to share information, identity, transactions details, etc., all without trade-offs, complying with AML measures, and accommodating the potential for high transaction volumes. It is not legacy bank accounts, and it is not peer-dependent, nor a self-organizing network.
A Novel Axial High-Temperature Superconducting Magnetic Bearing With Simple Structure and Large Suspension Force

In this article, we propose a novel axial high-temperature superconducting magnetic bearing (HTSMB), which is used in the field of shaftless magnetic levitation flywheel. The permanent magnet (PM) rotor of the HTSMB is assembled with Halbach PM rings and a polymagnet yoke disc, and high-temperature superconducting (HTS) bulks are equally distributed in a circle on the stator disk. First, the structure of the novel axial HTSMB is proposed, and the potential advantage is introduced. Second, the suspension characteristic of an HTS bulk is simulated based on COMSOL Multiphysics interface of Magnetic Field, No Current, Magnetic Field Formula (mfh), and Moving Mesh (ale), and it is verified by experiments. On this basis, the specific structure and size of the HTSMB are optimally designed by using ANSYS Maxwell. Then, the HTSMB is processed and assembled, a general method for assembling the PM rotor is introduced in detail. Finally, the suspension characteristic of the HTSMB is experimentally studied. The experimental results show that the HTSMB has more advantages in axial suspension characteristics and material cost.
T 2 Tests, the Linear Two-Group Discriminant Function, and Their Computation by Linear Regression

Abstract Tests for redundancy of variables in linear two-group discriminant analysis are well known and frequently used. We give a survey of similar tests, including the one-sample T 2 as a special case, in the situation in which only the mean vector (but no covariance matrix) is available in one sample. Then we show that a relation between linear regression and discriminant functions found by Fisher (1936) can be generalized to this situation. Relating regression and discriminant analysis to a multivariate linear model sheds more light on the relationship between them. Practical and didactical advantages of the regression approach to T 2 tests and discriminant analysis are outlined.
Structural and Piezoelectric Properties of DC-Sputtered AlN Films Deposited on Different Si-Based Substrates

We study the DC magnetron sputtering deposition of AlN on different substrates: (100) resistive Si, Si3N4 on Si and SiO2 on Si. The growth conditions of such films have been analysed to obtain the best structural and piezoelectric properties on each substrate. We show that, while AlN follows a columnar growth from the early stage of deposition on Si, the non—crystalline nature of Si3N4 and SiO2 induces an amorphous early growth stage on such substrates. Despite this structural difference, high performances have been obtained by AlN delay lines realised on both Si3N4/Si and pure resistive Si, providing further flexibility in the development of Si-based technological applications.
Convex programming in Hilbert space

This note gives a construction for minimizing certain twice-differentiable functions on a closed convex subset C, of a Hubert Space, H. The algorithm assumes one can constructively "project" points onto convex sets. A related algorithm may be found in Cheney-Goldstein [ l ] , where a constructive fixed-point theorem is employed to construct points inducing a minimum distance between two convex sets. In certain instances when such projections are not too difficult to construct, say on spheres, linear varieties, and orthants, the method can be effective. For applications to control theory, for example, see Balakrishnan [2], and Goldstein [3]. In what follows P will denote the "projection" operator for the convex set C. This operator, which is well defined and Lipschitzian, assigns to a given point in H its closest point in C (see, e.g., [ l ] ) . Take x £ f f and y £ C . Then [x — y, P(x) —y]^\\P(x) —y\\. In the nontrivial case this inequality is a consequence of the fact that C is supported by a hyperplane through P(x) with normal x — P(x). Let ƒ be a real-valued function on H and x0 an arbitrary point of C. Let 5 denote the level set (xGC: / (x ) ^f(x0)}, and let S be any open set containing the convex hull of S. Let ƒ'(*, • )= [V/(x), •] signify the Fréchet derivative of ƒ at x. A point zin C will be called stationary if P(z—pVf(z)) =z for all p > 0 ; equivalently, when ƒ is convex the linear functional f (z, •) achieves a minimum on C a t z.
Inclusiveness as a key determinant of work engagement: evidence from V4 countries

Research background: There is currently a need for empirical research regarding the validity of specific work environment model elements supported by strong statistical evidence. The amount of research conducted in this field has been particularly limited in Central-Eastern Europe. The desire to fill in these gaps was at least in part responsible for the uniqueness of the research approach and its differences from previous similar studies. Purpose of the article: The purpose of this study was to examine factors affecting employee engagement and to examine their relationship with each other using Visegrad countries as an example. Methods: The initial data is taken from the fourth European Company Survey (2019) for management respondents. After data cleaning, the sample sizes for Czechia, Hungary Poland, and Slovakia are N(CZ)=904, N(HU)=682, N(PL)=511, and N(SK)=361, respectively. As a result of the exploratory factor analysis (EFA), the following five dimensions were identified for this research: (1) inclusiveness, (2) empowerment, (3) work autonomy, (4) organizational learning environment, and (5) work engagement. An analysis of structural equation modeling (SEM) was conducted to determine the links that exist among these dimensions of a constructive work environment. Findings & value added: The structural model indicates that inclusiveness and empowerment have a significant positive impact on work engagement in all the countries examined. Inclusiveness was the strongest predictor of work engagement, followed by empowerment. Both of the two other predictors in the model (workplace autonomy and organizational learning environment) generally had less or no effect on employee engagement. The present study extends recent literature on work engagement by empirically validating the influence of workplace environment-related factors, as well as providing useful organizational policy recommendations for managers.
Rejoinder to "Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit‐Specific Outcomes"

In longitudinal studies and in clustered situations often binary and continuous response variables are observed and need to be modeled together. In a recent publication Dunson, Chen, and Harry (2003, Biometrics 59, 521–530) (DCH) propose a Bayesian approach for joint modeling of cluster size and binary and continuous subunit-specific outcomes and illustrate this approach with a developmental toxicity data example. In this note we demonstrate how standard software (PROC NLMIXED in SAS) can be used to obtain maximum likelihood estimates in an alternative parameterization of the model with a single cluster-level factor considered by DCH for that example. We also suggest that a more general model with additional cluster-level random effects provides a better fit to the data set. An apparent discrepancy between the estimates obtained by DCH and the estimates obtained earlier by Catalano and Ryan (1992, Journal of the American Statistical Association 87, 651–658) is also resolved. The issue of bias in inferences concerning the dose effect when cluster size is ignored is discussed. The maximumlikelihood approach considered herein is applicable to general situations with multiple clustered or longitudinally measured outcomes of different type and does not require prior specification and extensive programming.
Open-Set Patient Activity Recognition With Radar Sensors and Deep Learning

Open-set recognition (OSR) has achieved significant importance in recent years. For a robust recognition system, we need to identify the right class from a myriad of knowns and unknowns. In this work, we build and compare OSR systems for patient activity recognition (PAR) using compact radar sensors in a hospital setting. Radar sensors are an important part of a privacy-preserving monitoring system. Specifically, the proposed approach is based on a deep discriminative representation network (DDRN) trained using the large margin cosine loss (LMCL) and triplet loss (TL). A probability of an inclusion model in the embedding space based on the Weibull distribution is able to separate knowns from unknowns. This overall approach limits the risk of open space and enables us to easily identify any unknown activities. Our experiments show that the proposed approach is significantly better for open-set human activity recognition (HAR) with radar when compared with the state-of-the-art open-set approaches.
Silk Nanofibril-Palygorskite Composite Membranes for Efficient Removal of Anionic Dyes

To develop membrane materials with good performance for water purification that are green and low cost, this work reports an organic–inorganic composite membrane composed of silk nanofibrils (SNFs) and palygorskite (PGS). To improve the stability of the the composite membrane, genipin was used as a crosslinking agent to induce the conformational transition of SNF chains from random coils to β-sheets, reducing the swelling and hydrolysis of the membrane. The separation performance can be adjusted by tailoring the component ratio of the nanomaterial. The results showed that these membranes can effectively remove anionic dyes from water, and they exhibit excellent water permeability. The SNF-based membrane had strong mechanical and separation properties, and the PGS could tune the structure of composite membranes to enhance their permeability, so this green composite membrane has good prospects in water treatment and purification applications.
The National Hockey League Entry Draft, 1969–1995

We use NHL statistics for players selected in the National Hockey League Entry Draft to predict performance, which is measured by career games played, as a function of the player's position, year, and overall rank in the draft. This is done by inequality-constrained least squares using a weighted pool-adjacent-violators algorithm. The results are used to examine the value of having the ith versus the jth overall pick, to rank the drafting success of franchises, and to evaluate the performance of European players. The number of games actually played by European players drafted in the 1988–1992 period notably exceeded their expected number, as determined by the model.
A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry

Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion—Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.
Rydberg state excitation in molecules manipulated by bicircular two-color laser pulses

Abstract. Multiphoton resonant excitation and frustrated tunneling ionization, manifesting the photonic and optical nature of the driving light via direct excitation and electron recapture, respectively, are complementary mechanisms to access Rydberg state excitation (RSE) of atoms and molecules in an intense laser field. However, clear identification and manipulation of their individual contributions in the light-induced RSE process remain experimentally challenging. Here, we bridge this gap by exploring the dissociative and nondissociative RSE of H2 molecules using bicircular two-color laser pulses. Depending on the relative field strength and polarization helicity of the two colors, the RSE probability can be boosted by more than one order of magnitude by exploiting the laser waveform-dependent field effect. The role of the photon effect is readily strengthened with increasing relative strength of the second-harmonic field of the two colors regardless of the polarization helicity. As compared to the nondissociative RSE forming H2 * , the field effect in producing the dissociative RSE channel of ( H + , H * ) is moderately suppressed, which is primarily accessed via a three-step sequential process separated by molecular bond stretching. Our work paves the way toward a comprehensive understanding of the interplay of the underlying field and photon effects in the strong-field RSE process, as well as facilitating the generation of Rydberg states optimized with tailored characteristics.
An RF SQUID readout for a flux qubit-based microwave single photon counter

An analysis of the measurement of the magnetic flux in superconducting qubits based on RF SQUIDs was carried out with an 800 MHz bandwidth low-power-consumption cryogenic high-electron-mobility transistor amplifier. The preliminary experimental results obtained at temperatures 2 K and 4 K for RF SQUIDs in hysteretic, and in two non-hysteretic, regimes with a pump frequency of about 30 MHz are discussed. Parameters of RF SQUIDs in the hysteretic and non-hysteretic modes are analyzed within the framework of the resistively and capacitively shunted junction model for Josephson junctions. Its sensitivity at a temperature of 30 mK and frequency band (speed) are calculated and optimized to read the states of a flux qubit used as a single microwave photon counter. It is shown that an RF SQUID, operated in an adiabatic non-hysteretic mode for qubit readout, allows us to minimize its back-action effect and the dark count rate. This is due to the absence of Josephson generation, the small amplitude of the resonator electromagnetic field, and the selection of the pump frequency that does not coincide with the characteristic frequencies of the flux qubit.
Development of a Physiologically Based Pharmacokinetic Model for Tegoprazan: Application for the Prediction of Drug–Drug Interactions with CYP3A4 Perpetrators

Tegoprazan is a novel potassium-competitive acid blocker (P-CAB) developed by CJ Healthcare (Korea) for the treatment of gastroesophageal reflux disease and helicobacter pylori infections. Tegoprazan is mainly metabolized by cytochrome P450 (CYP) 3A4. Considering the therapeutic indications, tegoprazan is likely to be administered in combination with various drugs. Therefore, the investigation of drug–drug interactions (DDI) between tegoprazan and CYP3A4 perpetrators is imperative. In the present study, we first aimed to develop a physiologically based pharmacokinetic (PK) model for tegoprazan and its major metabolite, M1, using PK-Sim®. This model was applied to predict the DDI between tegoprazan and CYP3A4 perpetrators. Clarithromycin, a potent inhibitor of CYP3A4, and rifampicin, a strong inducer of CYP3A4, were selected as case studies. Our results show that clarithromycin significantly increased the exposure of tegoprazan. The area under the concentration–time curve (AUC) and Cmax of tegoprazan in the steady state increased up to 4.54- and 2.05-fold, respectively, when tegoprazan (50 mg, twice daily) was coadministered with clarithromycin (500 mg, three times daily). Rifampicin significantly reduced the exposure of tegoprazan. The AUC and Cmax of tegoprazan were reduced by 5.71- and 3.51-fold when tegoprazan was coadministered with rifampicin (600 mg, once daily). Due to the high DDI potential, the comedication of tegoprazan with CYP3A4 perpetrators should be controlled. The dosage adjustment for each individual is suggested.
Laser diode end-pumped V:YAG passively Q-switched UV lasers at 335 nm

In this paper, we present the using of a c-cut Nd:GdVO4 as the laser media, V:YAG as a saturable absorber and LBO as nonlinear crystal to obtain the passively Q-switched intra-cavity frequency doubled red laser at 670 nm and forth harmonic generation at 335 nm UV laser. Using dual end pump configurations at total pump power of 30 W at 808 nm, the repetition ratios of 153 kHz, the pulse width of 22 ns, average output power of 82 mW, peak power of 24.4 W and single pulse energy of 0.54 μJ pulsed 335 nm UV laser are obtained, the corresponding optical to optical conversion efficiency is about 0.273%.
Chronic and Postprandial Metabolic Responses to a Ketogenic Diet Compared to High-Carbohydrate and Habitual Diets in Trained Competitive Cyclists and Triathletes: A Randomized Crossover Trial

Extreme carbohydrate deficits during a ketogenic diet (KD) may result in metabolic adaptations reflective of low energy availability; however, the manifestation of these adaptations outside of exercise have yet to be elucidated in cyclists and triathletes. The purpose of this study is to investigate the chronic and postprandial metabolic responses to a KD compared to a high-carbohydrate diet (HCD) and habitual diet (HD) in trained competitive cyclists and triathletes. For this randomized crossover trial, six trained competitive cyclist and triathletes (F: 4, M: 2) followed an ad libitum KD and HCD for 14 d each after their HD. Fasting energy expenditure (EE), respiratory exchange ratio (RER), and fat and carbohydrate oxidation (FatOx and CarbOx, respectively) were collected during their HD and after 14 d on each randomly assigned KD and HCD. Postprandial measurements were collected on day 14 of each diet following the ingestion of a corresponding test meal. There were no significant differences in fasting EE, RER, FatOx, or CarbOx among diet conditions (all p > 0.050). Although postprandial RER and CarbOx were consistently lower following the KD meal, there were no differences in peak postprandial RER (p = 0.452), RER incremental area under the curve (iAUC; p = 0.416) postprandial FatOx (p = 0.122), peak FatOx (p = 0.381), or FatOx iAUC (p = 0.164) between the KD and HD meals. An ad libitum KD does not significantly alter chronic EE or substrate utilization compared to a HCD or HD; postprandial FatOx appears similar between a KD and HD; this is potentially due to the high metabolic flexibility of cyclists and triathletes and the metabolic adaptations made to habitual high-fat Western diets in practice. Cyclists and triathletes should consider these metabolic similarities prior to a KD given the potential health and performance impairments from severe carbohydrate restriction.
Less Is Enough: Assessment of the Random Sampling Method for the Analysis of Magnetoencephalography (MEG) Data

Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.