Miracle-dz/UniFAR-FTUs huggingface dataset:
PENGARUH ORIENTASI KEWIRAUSAHAAN, INOVASI PRODUK, DAN KEUNGGULAN BERSAING TERHADAP KINERJA PEMASARAN USAHA NASI KUNING DI KOTA MANADO

Penelitian ini merupakan sebuah pengujian dari pengaruh orientasi kewirausahaan, inovasi produk, dan keunggulan bersaing terhadap kinerja pemasaran usaha nasi kuning di kota Manado. Jumlah pelaku usaha nasi kuning khas Manado yang terus berkembang menuntut kemampuan bersaing dalam memasarkan produknya. Penelitian ini menggunakan pendekatan kuantitatif. Metode penelitian yang digunakan asosiatif. Data penelitian didasarkan pada tinjauan literatur yang relevan serta angket yang dikirim pada 47 pemilik usaha nasi kuning di kota Manado. Penelitian menggunakan metode sampling jenuh. Alat analisis data yang digunakan adalah analisis jalur. Hasil penelitian menggaris bawahi bahwa orientasi kewirausahaan tidak berpengaruh positif dan signifikan terhadap keunggulan bersaing, inovasi produk berpengaruh positif dan signifikan terhadap keunggulan bersaing, orientasi kewirausahaan dan inovasi produk secara simultan berpengaruh positif dan signifikan terhadap keunggulan bersaing, dan keunggulan bersaing berpengaruh positif dan signifikan terhadap kinerja pemasaran. Sebaiknya pemilik usaha nasi kuning di kota Manado meningkatkan keunikan produk dan kualitas produk yang sesuai dengan keinginan konsumen. Kata kunci : orientasi, kewirausahaan, inovasi, keunggulan bersaing
A Numerical Bayesian Approach to Spatial Data Analysis

Investigators in diverse fields of scientific investigations (specially the geo-statisticians) have long been concerned with the so called Regionalised Variable (ReV) or variables whose values are in some way related to their positions in space. In such situations it becomes sometimes necessary to estimate the values for certain measures based on the ReV over some suitable blocking or redivision of the space. In thls paper we deliniate a numerical Bayesian method based on the Gibbs sampling approach towards solving this class of problems whlch is capable of being tuned to various situations arising in the geological and other investigations dealing with ReVs. The paper deals with the problem of estimating the volume of an accumulation, from a data comprising of heights of the accumulation at random points, in some details and also reports the results of a few numerical applications of the methodology developed.
Separation of Time Scales in Sloppy Models: Perturbing the van der Pol Oscillator

We use an extension of the van der Pol oscillator as an example of a system with multiple time scales to study the sensitivity to polynomial perturbations in the dynamics. A striking feature of many nonlinear, multi-parameter models is an apparently inherent insensitivity to large magnitude variations in certain linear combinations of parameters. This phenomenon of “sloppiness” is quantified by calculating the eigenvalues of the Hessian matrix of the least-squares cost function which reveals that they typically span many orders of magnitude. The van der Pol system is no exception: Perturbations in its dynamics show that most directions in parameter space weakly affect the limit cycle, whereas only a few directions are stiff. With this study we show that separating the time scales in the van der Pol system leads to a further separation of eigenvalues and that parameter combinations which perturb the slow manifold are stiffer as these perturbations accrue most cost over time. Correspondingly, those which affect the transients in the dynamics are sloppier owing to their low contribution to cost.
RPBS: Rotational Projected Binary Structure for point cloud representation

In this paper, we proposed a novel three-dimension local surface descriptor named RPBS for point cloud representation. First, points cropped form the query point within a predefined radius is regard as a local surface patch. Then pose normalization is done to the local surface to equip our descriptor with the invariance to rotation transformation. To obtain more information about the cropped surface, multi-view representation is formed by successively rotating it along the coordinate axis. Further, orthogonal projections to the three coordinate plane are adopted to construct two-dimension distribution matrixes, and binarization is applied to each matrix by following the rule that whether the grid is occupied, if yes, set the grid one, otherwise zero. We calculate the binary maps from all the viewpoints and concatenate them together as the final descriptor. Comparative experiments for evaluating our proposed descriptor is conducted on the standard dataset named Bologna with several state-of-the-art 3D descriptors, and results show that our descriptor achieves the best performance on feature matching experiments.
Enhanced gamma ray sensitivity in bismuth triiodide sensors through volumetric defect control

Some of the more attractive semiconducting compounds for ambient temperature radiation detector applications are impacted by low charge collection efficiency due to the presence of point and volumetric defects. This has been particularly true in the case of BiI3, which features very attractive properties (density, atomic number, band gap, etc.) to serve as a gamma ray detector, but has yet to demonstrate its full potential. We show that by applying growth techniques tailored to reduce defects, the spectral performance of this promising semiconductor can be realized. Gamma ray spectra from >100 keV source emissions are now obtained from high quality Sb:BiI3 bulk crystals with limited concentrations of defects (point and extended). The spectra acquired in these high quality crystals feature photopeaks with resolution of 2.2% at 662 keV. Infrared microscopy is used to compare the local microstructure between radiation sensitive and non-responsive crystals. This work demonstrates that BiI3 can be prepared in .
Jan Simon Schymik : Trade , Technologies , and the Evolution of Corporate Governance

Do international trade and technological change influence how firms create incentives for human capital? I present a model that incorporates agency problems into a framework with firm heterogeneity and human capital. My model indicates that trade liberalizations and skill-biased technological change alter the way how the largest firms in an economy incentivize their managers. Increases in managerial reservation wages lead to a reduction in corporate governance investments and a rise in performance compensation since monitoring managers becomes less efficient. Using data on CEO compensation and entrenchment opportunities in public industrial firms in the U.S., I document strong empirical regularities in support of the model predictions. Firms allow for more managerial entrenchment and offer larger CEO compensation when their industries become more open to trade or when production becomes more I.T. intensive. JEL Classification: F1, F16, G34, J33, L22, O33
Price simulation and prediction of leaf vegetable based on gene expression algorithm

Based on the traditional gene expression algorithm, the paper proposed an improved gene expression algorithm, adding “inverted string” and “gene extraction” operator. An improved GEP algorithm is used in the leafy vegetables prices forecast, create the mathematical model through the analysis and evolution of training data, realize the simulation and forecast of the price of leafy vegetables. Through several experiments, the results proved that the new type of gene expression programming algorithm has faster convergence rate and higher precision in predicting the price of leafy vegetables.
Learning Inverse Mappings with Adversarial Criterion

We propose a flipped-Adversarial AutoEncoder (FAAE) that simultaneously trains a generative model G that maps an arbitrary latent code distribution to a data distribution and an encoder E that embodies an "inverse mapping" that encodes a data sample into a latent code vector. Unlike previous hybrid approaches that leverage adversarial training criterion in constructing autoencoders, FAAE minimizes re-encoding errors in the latent space and exploits adversarial criterion in the data space. Experimental evaluations demonstrate that the proposed framework produces sharper reconstructed images while at the same time enabling inference that captures rich semantic representation of data.
European Journal of Special Education Research-ISSN 2501-2428

This study investigated the relationship between mental resilience, culture free selfesteem and self-efficacy for peer interactions in students with and without mild special educational needs. Results have shown that students with mild special educational needs had scored significantly lower mean values for mental resilience, culture free self-esteem and self-efficacy for peer interactions than their control counterparts did. For the group of students with mild special educational needs the internal factors of mental resilience and their self-efficacy for peer interactions interpreted the external factors of their mental resilience at 52% whereas for the control group it was the mental resilience as an overall score and their general self-esteem that interpreted the self-efficacy for peer interactions at 24%.
Variation of false twist on spinning process stability and resultant yarn properties in a modified ring spinning frame

Twisting is an important process to form a continuous yarn from short fibers and to determine the structure and properties of the resultant yarn. This article reports on the effect of variation of false twist on process stability and resultant yarn quality in a modified ring spinning frame. Based on twist kinematics, three practical cases that cause twist variations in the spinning process are investigated, namely step function, rectangular function and periodic function changes in false twist. The simulation results are validated by experiments and a good agreement has been demonstrated. The resultant properties of yarn within 30% periodic change in false twist demonstrated insignificance compared with yarn without variation. With the developed model, essential system parameters are numerically examined and their quantitative relationships are studied. The practical implications are discussed.
The accurate analysis of smoothly fluctuating harmonics applied to the calibration of harmonic analysers.

The aim of this research is to develop an accurate method for the analysis of signals composed of fluctuating harmonics. The results obtained of analysis are applied to the calibration of harmonic analysis instruments. A new method is presented suitable for the accurate analysis of smoothly fluctuating harmonic signals. The method is based on a model of signals with a known period, in which the harmonics are individually modulated by polynomial functions normalised over a sampled signal sequence time. Using this model, a decomposition method is developed such that the modulating polynomials can be recovered from a signal. The polynomial decomposition method leads to a piece-wise analysis of the waveform. Two methods based on least squares and splines respectively, are developed with the aim of giving continuity to the piece-wise analysis. Comparisons of the new method with the short time Fourier transform are given. Having defined a test signal and obtained and accurate analysis of it properties, it can be used to calibrate harmonic analysers. For a given applied signal, analysis with these devices can give rise to variation in results as a function of the phase between the signal and the STFT windows. This result distribution due to variable phase (RDVP) is discussed and examples are given for various signals. The RDVP complicates the calibration process due to the spread of results that occur when testing the device. A method is developed to find the RDVP for an applied signal that uses the polynomial decomposition method to find the modulation functions of each harmonic in the applied calibration signal. Having found the RDVP for an applied signal, it is necessary to fit the results of the analyser under test, to the distribution. The random nature of the phase makes the systematic comparison of the theoretical and measured distributions difficult to achieve. A novel method that uses multiple phase shifted modulated harmonics is presented. By comparing the results of the analyser under test to the distributions of each of the phase-shifted harmonics, a best-fit phase shift can be determined and the required calibration comparison made. Key words: time-frequency analysis, demodulation, harmonic analysis, fluctuating harmonics, waveform metrology, calibration of harmonic analysers.
A new view on exoplanet transits: Transit of Venus described using three-dimensional solar atmosphere Stagger-grid simulations

Stellar activity and, in particular, convection-related surface structures, potentially cause fluctuations that can affect the transit light curves. Surface convection simulations can help the interpretation of ToV. We used realistic three-dimensional radiative hydrodynamical simulation of the Sun from the Stagger-grid and synthetic images computed with the radiative transfer code Optim3D to provide predictions for the transit of Venus in 2004 observed by the satellite ACRIMSAT. We computed intensity maps from RHD simulation of the Sun and produced synthetic stellar disk image. We computed the light curve and compared it to the ACRIMSAT observations and also to the light curves obtained with solar surface representations carried out using radial profiles with different limb-darkening laws. We also applied the same spherical tile imaging method to the observations of center-to-limb Sun granulation with HINODE. We managed to explain ACRIMSAT observations of 2004 ToV and showed that the granulation pattern causes fluctuations in the transit light curve. We evaluated the contribution of the granulation to the ToV. We showed that the granulation pattern can partially explain the observed discrepancies between models and data. This confirms that the limb-darkening and the granulation pattern simulated in 3D RHD Sun represent well what is imaged by HINODE. In the end, we found that the Venus's aureole contribution during ToV is less intense than the solar photosphere, and thus negligible. Being able to explain consistently the data of 2004 ToV is a new step forward for 3D RHD simulations that are becoming essential for the detection and characterization of exoplanets. They show that the granulation have to be considered as an intrinsic incertitude, due to the stellar variability, on precise measurements of exoplanet transits of, most likely, planets with small diameters.
Microtubules with a twist: a lumenal interrupted helix in human sperm tail microtubules

John Heumann*, Cindi L. Schwartz*, Azusa Suzuki-Shinjo**, Garry Morgan*, Per Widlund***, Johanna Höög**** * Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO, USA ** Krefting Research Centre, University of Gothenburg, Gothenburg, Sweden *** Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden **** Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
Stability and bifurcation in an age-structured model with stocking rate and time delays

In this paper, a predator-prey model with age structure, stocking rate and two delays is investigated. We show that Hopf bifurcation occurs when one of the time delay $τ$ crosses a sequence of critical values, by applyingHopf bifurcation theory for abstract Cauchy problems with non-dense domain. Numerical simulations are included to verify our results and a summary is also given.
Economica

provides the guidelines for the employer to make effective the monetary payment to the employee as compensation for his time worked, However, there may be different socioeconomic factors that lead SMEs to partial or total noncompliance with the provisions established in that law. Therefore, this research is developed based on the main economic and social challenges faced by SMEs in the metropolitan area of San Salvador, taking into account the effects and implications that influence compliance with the Law, with the interest of addressing key points of improvement that will allow the entity to avoid fines or penalties in the future.
Adaptive channel estimation for soft decision decoding over non-Gaussian optical channel

An adaptive priori likelihood ratio (LLR) estimation method is proposed over non-Gaussian channel in the intensity modulation/direct detection (IM/DD) optical communication systems. Using the nonparametric histogram and the weighted least square linear fitting in the tail regions, the LLR is estimated and used for the soft decision decoding of the low-density parity-check (LDPC) codes. This method can adapt well to the three main kinds of intensity modulation/direct detection (IM/DD) optical channel, i.e., the chi-square channel, the Webb-Gaussian channel and the additive white Gaussian noise (AWGN) channel. The performance penalty of channel estimation is neglected.
Electric and magnetic parts of the Weyl tensor and spin coefficients

Abstract It is known that electric and magnetic parts of the Weyl tensor in General Relativity are analogous to that occur in the theory of electromagnetism. On the other hand, Newman-Penrose formalism provides a new dimension to the solutions and interpretations for the theory of relativity. Its significance in understanding spacetimes with some particular Petrov types, solutions with different material contents is well known. This paper provides spin coefficient form of electric and magnetic parts of the Weyl tensor, which leads to a new and efficient way for the computation of electric and magnetic parts of the Weyl tensor. It is observed that the computational time is greatly reduced when done using computer algebra system in comparison to that is done manually. This technique is elaborated in the example of Pure Radiation metric.
2 Happy House : Spousal Weight and Individual Well-Being

We use life satisfaction and Body Mass Index (BMI) information from three waves of the GSOEP to test for social interactions in BMI between spouses. Semi-parametric regressions show that partner’s BMI is, beyond a certain level, negatively correlated with own satisfaction. Own BMI is positively correlated with satisfaction in thin men, and negatively correlated with satisfaction after some threshold. Critically, this latter threshold increases with partner’s BMI when the individual is overweight. The negative well-being impact of own BMI is thus lower when the individual’s partner is heavier. This is consistent with social contagion effects in weight. However, this cross-partial effect is insignificant in instrumental variable regressions, suggesting that the uninstrumented relationship reflects selection on the marriage market or omitted variables, rather than contagion.
Jukuri, open repository of the Natural Resources Institute Finland (Luke)

Phycobiliproteins are pigments with uses in pharmacology, cosmetics, foods, and as fluorescent probes in biochemistry. Cryptophyte microalgae are one possible source of phycobiliproteins as well as other molecules such as omega-3 fatty acids. The use of cryptophytes in biotechnology is currently very limited and especially the potential of freshwater species is poorly documented. For commercial microalgae production, it is important to find the best performing strains in terms of growth and yields of the products of interest. Phycoerythrin is a phycobiliprotein with red colour and strong yellow fluorescence. In this study, we evaluate the growth and phycoerythrin production of eight strains of freshwater cryptophytes belonging to the genus Cryptomonas, comparing them to two marine strains. The strains are grown in batch cultures under standardised conditions. Most of the studied freshwater strains have lower growth rates and all of them have lower biomass yields than the marine strains. However, most of them have much higher cellular phycoerythrin concentrations, which in the case of two strains leads them to a significantly higher overall phycoerythrin yield. There is large variation among cryptophytes in growth rates and phycoerythrin content. Our results suggest that freshwater cryptophytes of the genus Cryptomonas may be better sources of phycoerythrin than the more extensively studied marine strains.
Jukuri, open repository of the Natural Resources Institute Finland (Luke)

Fish assemblages are known to change from headwaters to river outlets. Still, our knowledge of this change is often approximate or sporadic. In this study, we quantified the average longitudinal change from a large electrofishing data set of boreal streams in Northern Europe. The average species richness increased from headwaters to medium-sized rivers but levelled off when reaching large rivers. Existence of some headwater specialist fish species, e.g. brook trout (Salvelinus fontinalis), was interpreted to support the fish zonation concept over the concept of accumulative addition of species downstream. The traditional fish zonation concept developed in Western Europe suggests four zones from headwaters to river outlets, the trout zone, the grayling zone, the barbel zone and the bream zone. Of these, only the trout zone was clearly present with a high dominance in the headwaters of the streams studied. For the North European boreal streams, we suggest a zonation concept with three dominating fish species from headwaters downstream, brown trout (Salmo trutta), bullhead (Cottus gobio) and Atlantic salmon (Salmo salar). Discovered longitudinal shifts in fish guild compositions offered an opportunity for an ecological interpretation of the data and a promising basis for bioassessment.
A Heterogeneous Graph-based Framework for Scalable Fraud Detection

The rise of online marketplaces has led to increased concerns regarding the presence of bad actors involved in coun-terfeit or engage in fraudulent activities. While efforts are being made by organizations to monitor and address these issues, bad actors persistently find new ways to engage in fraudulent behavior, including creating new accounts using different credentials, account hijacking etc. To combat this issue, our study proposes the use of Heterogeneous Relational Graph Convolutional Networks (HRGCN) to identify risky relationships among entities like sellers or customers. By leveraging this advanced graph-based approach, we aim to enhance the detection and mitigation of fraudulent behavior on the e-commerce marketplaces. The HRGCN model is designed to detect sellers with risky associations with other known bad sellers by analyzing various connecting edges such as encrypted device and identity credentials. With the rapid growth of e-commerce stores, the number of sellers has witnessed an exponential increase, leading to a significant expansion in their social networks formed by sharing various relationships such as digital contact information, communication channels and devices. This has made it challenging to process the data with the direct implementation of HRGCN. This highlights the importance of model scalability in handling large datasets. To address this issue, we have introduced a novel mini-batch version of HRGCN variant that works in tandem with a neighborhood sampler, which is optimized to run on GPUs, significantly reducing the training time by 70%. This mini-batch version of HRGCN maintains and/or improves the performance of the model while addressing the scalability issue, making it an efficient solution for handling large datasets. In this paper, we compare the performance of three models: a benchmark model based on Random Forest trained on seller node features alone, HRGCN trained on