Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-creating value and its impact on customer satisfaction and customer loyalty: A banking sector perspective

The application of co-creation is important and traditionally proves that banks that offer products and services without taking into account the opinions and recommendations of customers have the opportunity to remain focused on the bank and not be successful (Keshavarz & Jamshidi, 2018). In many organizations, especially those dealing with services, customer satisfaction is considered a challenge. Customer satisfaction influences customer loyalty and a loyal customer is a constant source of revenue, and satisfied customers do not focus on replacement products found on the market. From this, we conclude that customer satisfaction increases loyalty and reduces opposition to the products and services that the company offers (Jaakkola, Helkkula, & Aarikkula-Stenroos, 2015). This study aims to measure the impact of co-creation value through the DART (dialogue, access, risk assessment, and transparency) model on customer satisfaction and customer loyalty. The method used to answer the research questions is the quantitative method, where data were collected through primary research; the population of this study is the customers of all commercial banks in Kosovo, where the sample was 300 customers of randomly selected banks. Based on the research results, referring to Spearman’s rho correlation we conclude that co-creation with customer satisfaction and customer loyalty are in direct proportion. According to the ordinary least squares (OLS) model, we conclude that co-creation affects customer satisfaction and customer loyalty. Through this research, banking structures have the opportunity to increase customer satisfaction and create loyalty to customers through the co-creation process, strengthening its components such as dialogue, access, risk assessment, and transparency.
WAVELET CHARACTERIZATIONS OF WEIGHTED HERZ SPACES

We characterize the homogeneous weighted Herz space ˙ K α,p q (w1, w2) and the non-homogeneous weighted Herz space K α,p q (w1, w2) using wavelets in C 1 (R n ) with compact support. Applying the characterizations, we prove that the wavelet basis forms an unconditional basis in ˙ K α,p q (w1, w2) and in K α,p q (w1, w2) .
Ergogenic Effects of Caffeine on Ballistic (Throwing) Performance: A Meta-Analytical Review

Ballistic exercise is characterized by high velocity, force, and muscle activation. Typical examples of ballistic exercise are jumping and throwing activities. While several studies explored caffeine’s effects on throwing performance, the between study findings varied. Therefore, we performed a meta-analysis exploring caffeine’s effects on throwing performance (e.g., shot put, medicine ball throw, bench press throw). Seven databases were searched for eligible research. Ten studies (n = 151) were included. In the main meta-analysis, there was a significant ergogenic effect of caffeine on throwing performance (standardized mean difference [SMD]: 0.19; 95% confidence interval [CI]: 0.05, 0.33; p = 0.007). There was a significant ergogenic effect of caffeine in the subgroup analysis for studies that evaluated throwing velocity (SMD: 0.24; 95% CI: 0.10, 0.37; p = 0.0006) and used caffeine doses ≤3 mg/kg (SMD: 0.18; 95% CI: 0.05, 0.31; p = 0.006). There was no significant difference between caffeine and placebo in the subgroup analysis for studies that evaluated throwing distance (SMD: 0.15; 95% CI: −0.09, 0.40; p = 0.22) and used caffeine doses >3 mg/kg, (SMD: 0.17; 95% CI: −0.08, 0.41; p = 0.19). However, after one outlier study was excluded as part of a sensitivity analysis, an ergogenic effect was also observed for throwing distance and caffeine doses >3 mg/kg. Based on the results of this review, we conclude that individuals interested in the acute enhancement of throwing performance may consider caffeine supplementation.
Cinématique guidée par les distances

Ce papier decrit une nouvelle methode de controle cinematique de systemes articules. Contrairement aux approches classiques, nous posons le probleme dans un nouvel espace : celui des distances. Nous proposons une nouvelle formalisation de la cinematique guidee par les distances et une methode d’optimisation qui permettent de resoudre un ensemble de problemes classiques d’adaptation de mouvement et de cinematique inverse. L’originalite de la methode reside egalement dans la possibilite d’introduire des contraintes de distance avec priorites. L’approche est validee par un ensemble d’experiences mettant en oeuvre plusieurs operations classiques de cinematique appliquees au controle du mouvement de personnages et systemes articules, et comparee a d’autres approches au moyen de considerations de stabilite, de convergence et de performance.
Prevalence of Bacterial Coinfections with Vibrio harveyi in the Industrialized Flow-through Aquaculture Systems in Hainan Province: A Neglected High-Risk Lethal Causative Agent to Hybrid Grouper

Vibrio harveyi is one of the most serious bacterial pathogens to aquatic animals worldwide. Evidence is mounting that coinfections caused by multiple pathogens are common in nature and can alter the severity of diseases in marine animals. However, bacterial coinfections involving V. harveyi have received little attention in mariculture. In this study, the results of pathogen isolation indicated that bacterial coinfection was a common and overlooked risk for hybrid groupers (♀ Epinephelus polyphekadion × ♂ E. fuscoguttatus) reared in an industrialized flow-through pattern in Hainan Province. The artificial infection in hybrid groupers revealed that coinfections with V. harveyi strain GDH11385 (a serious lethal causative agent to groupers) and other isolated pathogens resulted in higher mortality (46.67%) than infection with strain GDH11385 alone (33.33%), whereas no mortality was observed in single infection with other pathogens. Furthermore, the intestine, liver and spleen of hybrid groupers are target organs for bacterial coinfections involving V. harveyi. Based on the infection patterns found in this study, we propose that V. harveyi may have a specific spatiotemporal expression pattern of virulence genes when infecting the host. Taken together, bacterial coinfection with V. harveyi is a neglected high-risk lethal causative agent to hybrid groupers in the industrialized flow-through aquaculture systems in Hainan Province.
Verifying Timed Commitment Specifications for IoT-Cloud Systems with Uncertainty

Cloud Computing plays an essential role in meeting the increasing demand for large data storage and infrastructures in IoT applications. The applications of IoT-Cloud are in an exponential rise in the number of interacting components with different interaction protocols within open and uncertain environments. The main challenge that faces these applications is ensuring their reliability and efficiency. This paper proposes a scalable verification approach for IoT-Cloud applications in uncertainty-characterised settings with timed commitments using three-valued model checking. Timed commitments are powerful artifacts that capture flexible and rich interaction protocols. We use a new logic for reasoning about uncertainty in commitment protocols, model a smart contract-based IoT mortgage system with commitments under uncertain settings, introduce a set of specifications, and implement a verification framework of our model against its specifications using a transformation algorithm and the ${MCMAS}_{+}$ model checker. Finally, we report and discuss our experimental results.
Structural modelling for assessing the effectiveness of system for countering legalization of illicit money

The article suggests a scientific and methodological approach to the evaluation of the infrastructural component’s effectiveness in the anti-money laundering system due to digitalization. Structural modelling is the basis for the mentioned approach implementation, which consists of several steps. First, the input data is selected in terms of the effective regulation of the financial services market, law enforcement and judicial activities, and digitalization. Next, the moving average method is used to identify the growth rate of missing values in the available data series. Then, the selection of relevant factors for financial services market regulation, law enforcement activity, judicial activity and digitalization is based on the principal component analysis. After reducing the input array of data to a comparable form, a structural equations system can be constructed to reflect the impact of the digitalization level on the latent integral characteristics of the directions of anti-money laundering work done by regulatory authorities. Finally, the model is checked for adequacy. The result of this research can serve as an information base for further strengthening the digital vector in the development of regulation institutions and law enforcement agencies overseeing the financial services market, as well as for the radical transformation of courts in Ukraine since digitalization currently negatively affects them.
Multi-Connectivity for 5G Networks and Beyond: A Survey

To manage a growing number of users and an ever-increasing demand for bandwidth, future 5th Generation (5G) cellular networks will combine different radio access technologies (cellular, satellite, and WiFi, among others) and different types of equipment (pico-cells, femto-cells, small-cells, macro-cells, etc.). Multi-connectivity is an emerging paradigm aiming to leverage this heterogeneous architecture. To achieve this, multi-connectivity proposes to enable UE to simultaneously use component carriers from different and heterogeneous network nodes: base stations, WiFi access points, etc. This could offer many benefits in terms of quality of service, energy efficiency, fairness, mobility, and spectrum and interference management. Therefore, this survey aims to present an overview of multi-connectivity in 5G networks and beyond. To do so, a comprehensive review of existing standards and enabling technologies is proposed. Then, a taxonomy is defined to classify the different elements characterizing multi-connectivity in 5G and future networks. Thereafter, existing research works using multi-connectivity to improve the quality of service, energy efficiency, fairness, mobility management, and spectrum and interference management are analyzed and compared. In addition, lessons common to these different contexts are presented. Finally, open challenges for multi-connectivity in 5G networks and beyond are discussed.
The Deuteration Clock for Massive Starless Cores

To understand massive star formation requires study of its initial conditions. Two massive starless core candidates, C1-N & C1-S, have been detected in IRDC G028.37+00.07 in N 2 D + (3–2) with ALMA . From their line widths, either the cores are subvirial and are thus young structures on the verge of near free-fall collapse, or they are threaded by ∼1 mG B -fields that help support them in near virial equilibrium and potentially have older ages. We modeled the deuteration rate of N 2 H + to constrain collapse rates of the cores. First, to measure their current deuterium fraction, D ≡ [ N 2 D + ]/[ N 2 H + ], we observed multiple transitions of N 2 H + and N 2 D + with CARMA , SMA , JCMT , NRO 45 m and IRAM 30 m , to complement the ALMA data. For both cores we derived D ∼ 0.3, several orders of magnitude above the cosmic [D]/[H] ratio. We then carried out chemodynamical modeling, exploring how collapse rate relative to free-fall, α ff , affects the level of D that is achieved from a given initial condition. To reach the observed D , most models require slow collapse with α ff ∼0.1, i.e. , ∼1/10th of free-fall. This makes it more likely that the cores have been able to reach a near virial equilibrium state and we predict that strong B -fields will eventually be detected. The methods developed here will be useful for measurement of the pre-stellar core mass function.
In Vitro/In Vivo Translation of Synergistic Combination of MDM2 and MEK Inhibitors in Melanoma Using PBPK/PD Modelling: Part II

The development of in vitro/in vivo translational methods for synergistically acting drug combinations is needed to identify the most effective therapeutic strategies. We performed PBPK/PD modelling for siremadlin, trametinib, and their combination at various dose levels and dosing schedules in an A375 xenografted mouse model (melanoma cells). In this study, we built models based on in vitro ADME and in vivo PK/PD data determined from the literature or estimated by the Simcyp Animal simulator (V21). The developed PBPK/PD models allowed us to account for the interactions between siremadlin and trametinib at PK and PD levels. The interaction at the PK level was described by an interplay between absorption and tumour disposition levels, whereas the PD interaction was based on the in vitro results. This approach allowed us to reasonably estimate the most synergistic and efficacious dosing schedules and dose levels for combinations of siremadlin and trametinib in mice. PBPK/PD modelling is a powerful tool that allows researchers to properly estimate the in vivo efficacy of the anticancer drug combination based on the results of in vitro studies. Such an approach based on in vitro and in vivo extrapolation may help researchers determine the most efficacious dosing strategies and will allow for the extrapolation of animal PBPK/PD models into clinical settings.
A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery

Rotating machinery plays an important role in industrial systems, and faults in the machinery may damage the system health. A novel image-based diagnosis method using improved deep convolutional generative adversarial networks (DCGAN) is proposed for the feature recognition and fault classification of rotating machinery. First, vibration signal data from the rotating machinery is transformed into time–frequency feature 2-D image data by a continuous wavelet transform and used for fault classification with the neural network method. The adaptive deep convolution neural network (ADCNN) is then combined with the generative adversarial networks (GANs) to improve the performance of the feature self-learning ability from input data. Compared with different fault diagnosis methods, the proposed method has better performance for image feature classification in rotating machinery.
Competing many-body instabilities and unconventional superconductivity in graphene

The band structure of graphene exhibits van Hove singularities (VHSs) at dopings $x=\ifmmode\pm\else\textpm\fi{}1/8$ away from the Dirac point. Near the VHS, interactions effects, enhanced due to the large density of states, can give rise to various many-body phases. We study the competition between many-body instabilities in graphene using the functional renormalization group. We predict a rich phase diagram, which, depending on band structure as well as the range and scale of Coulomb interactions, contains a $d+id$-wave superconducting (SC) phase, or a spin-density-wave phase at the VHS. The $d+id$ state is expected to exhibit quantized charge and spin Hall response, as well as Majorana modes bound to vortices. Nearby the VHS, we find singlet $d+id$-wave and triplet $f$-wave SC phases.
Second Language Learning via Syntactic Priming: Investigating the Role of Modality, Attention, and Motivation

: We examined whether input modality and individual differences in attention and motivation inﬂuence second language (L2) learning via syntactic priming. In an online study, we compared the primed production of English passives by 235 L2 and native English speakers in reading-to-writing versus listening-to-writing conditions. We measured immediate priming (producing passives immediately after exposure to passives) and short- and long-term learning (producing more passives in immediate and 1-week delayed posttests relative to pretests). Both groups showed immediate priming and short- and long-term learning, although L2 speakers produced more passives with immediate priming and showed greater long-term learning. Learning was unaffected by modality, but immediate priming was greatest in the listening-to-writing condition across groups. Individual differences in attention and motivation did not inﬂuence priming or learning. Thus, syntactic priming fosters long-term L2 learning regardless of input modality, but participants may be sensitive to the frequency of passives in spoken versus written language during immediate priming.
Faint dwarf galaxies in Hickson Compact Group 90

We report the discovery of a very diverse set of five low-surface brightness (LSB) dwarf galaxy candidates in Hickson Compact Group 90 (HCG 90) detected in deep U- and I-band images obtained with VLT/VIMOS. These are the first LSB dwarf galaxy candidates found in a compact group of galaxies. We measure spheroid half-light radii in the range $0.7\! \lesssim\! r_{\rm eff}/{\rm kpc}\! \lesssim\! 1.5$ with luminosities of $-11.65\! \lesssim\! M_U\! \lesssim\! -9.42$ and $-12.79\! \lesssim\! M_I\! \lesssim\! -10.58$ mag, corresponding to a color range of $(U\! -\! I)_0\! \simeq\! 1.1\! -\! 2.2$ mag and surface brightness levels of $\mu_U\! \simeq\! 28.1\,{\rm mag/arcsec^2}$ and $\mu_I\! \simeq\! 27.4\,{\rm mag/arcsec^2}$. Their colours and luminosities are consistent with a diverse set of stellar population properties. Assuming solar and 0.02 Z$_\odot$ metallicities we obtain stellar masses in the range $M_*|_{Z_\odot} \simeq 10^{5.7-6.3} M_{\odot}$ and $M_*|_{0.02\,Z_\odot}\! \simeq\! 10^{6.3-8}\,M_{\odot}$. Three dwarfs are older than 1 Gyr, while the other two significantly bluer dwarfs are younger than $\sim 2$ Gyr at any mass/metallicity combination. Altogether, the new LSB dwarf galaxy candidates share properties with dwarf galaxies found throughout the Local Volume and in nearby galaxy clusters such as Fornax. We find a pair of candidates with $\sim\! 2$ kpc projected separation, which may represent one of the closest dwarf galaxy pairs found. We also find a nucleated dwarf candidate, with a nucleus size of $r_{\rm eff}\! \simeq\! 46\! -\! 63$ pc and magnitude M$_{U,0}=-7.42$ mag and $(U\! -\! I)_0\! =\! 1.51$ mag, which is consistent with a nuclear stellar disc with a stellar mass in the range $10^{4.9-6.5}\,M_\odot$.
Note on regular black holes in a brane world

In this work, we show that regular black holes in a Randall-Sundrum-type brane world model are generated by the nonlocal bulk influence, expressed by a constant parameter in the brane metric, only in the spherical case. In the axial case (black holes with rotation), this influence forbids them. A nonconstant bulk influence is necessary to generate regular black holes with rotation in this context.
Density Functional Theory studies of structural, electronic and optical properties of Fluorine Doped Magnesium Hydride

In order to overcome the disadvantages of magnesium hydride (MgH2) towards its applications in solar cell science and technology, doping with non-metals such as Fluorine (F) doping is a promising approach to tune its large band gap. In order to expose the hidden potential in F doped MgH2, details analysis of electronic and optical absorptions is needed. Theoretical calculations of structural, electronic and optical properties of F doped MgH2 are studied using first-principles approach within density functional theory (DFT) framework. The calculated lattice constants with PBE-GGA are in better agreement with experimental result. The bandgap value of 3.34 eV for the undoped MgH2 is close to experimental value. When one atom of F is introduced into MgH2 at Mg site, the doping effects modified the band gap from 3.34 to 2.72 eV. Also, by introducing one atom of F to H site, the band gap value reduced to 1.59 eV. Our findings confirmed that non-metal doping narrow the energy band gap of semiconductor materials. The results of optical absorptions indicate that F doped MgH2 at H has strong absorption behavior in the visible light frequency, which depicts its suitability for solar cell applications.
Bonding of 5 μm Cu-Sn Micro Bumps Using Thermal Reflow and Solid-State Pre-Bonding

Copper–tin (Cu–Sn) transient liquid-phase (TLP) bonding has attractive advantages and has been widely used in three-dimensional (3-D) integration to establish electrical connections between stacked chips. However, TLP bonding has technical difficulties in bonding Cu–Sn bumps with small diameters and fine pitches due to the bonding pressure-induced lateral extrusion of the melted Sn layer. As bonding of micro bumps with diameters smaller than 5 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> is highly desired in future applications, this article reports the TLP bonding of micro bumps using improved reflow and pre-bonding. Due to the large surface-to-volume ratio of micro bumps, the reflow conditions dramatically influence the reflow characteristics, and systematical investigations are performed such that an Sn layer with an optimal thickness has been obtained to avoid lateral extrusion. A new bonding scheme has been developed by combining a solid-state pre-bonding and a TLP final bonding. The new bonding method and the Sn thickness control reflow avoid liquid Sn extrusion under bonding pressure. Using these techniques, Cu–Sn bonding of bumps with a diameter down to 5 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> has been successfully achieved with a high bonding yield.
Design of ROS-based Robotic Platform with High-precision stepping motor control

Robot technology rapidly expands from traditional industrial manufacturing to home services, medical care, education, rescue exploration, and military applications. In this paper, we design a Robot Operating System (ROS) based robotic platform with a stepping motor with a high precision advantage. This robotic platform is focused on controlling a stepping motor and combination with sensors such as 2D-Lidar, and Inertial Measurement Unit (IMU) to achieve Simultaneous localization and mapping (SLAM) and navigation function. Furthermore, we propose a speed control algorithm for the stepping motor, which can convert the speed command published by Single Board Computer (SBC) into a Pulse-width modulation (PWM) signal. Finally, in the corridor scenario, we tested the robotic platform's 2D-Lidar mapping and autonomous navigation functions. The experimental results show that the robot platform has the good mapping and high-precision autonomous navigation capabilities.