Miracle-dz/UniFAR-FTUs huggingface dataset:
Precise analytic approximation for the modiﬁed Bessel function I_(1)(x)

Precise analytic approximations have been found for the modiﬁed Bessel function I_(1)(x) of order one. The approximant is simple and with good accuracy for every positive value of the variable x. The method to obtain the approximant is an improvement of the multipoint quasirational approximation technique, MPQA. This is obtained combining rational functions with elementary auxiliary functions as a bridge function between the power series and asymptotic expansion.
Cryptocurrency gamification: Having fun or making money

The purpose of gamification in cryptocurrencies is to improve user engagement through game-thinking (Kabita, 2020; Rodrigues et al., 2019). Yet, it is unclear whether participants are motivated by the desire to have fun or to generate money. This study intends to explore the elements that encourage people to participate in cryptocurrency gamification by analysing perceived enjoyment, perceived profitability, and demographic variables. Data was obtained from Thai nationals residing in Thailand who have invested in digital assets or plan to in the future. Using multivariate logistic regression, statistically significant factors were identified. The data indicate that Thai investors’ interest in cryptocurrency gamification increases with age and student status. Also, people are attracted to the gamification of cryptocurrencies since they may be both interesting and lucrative. The study argues that it is essential to assess the risks associated with the gamification of cryptocurrencies. This will ensure that individuals who wish to earn money do not lose it. In addition, the likelihood of financial exploitation through cryptocurrency gaming must be evaluated. This is required because the risk of individuals being victimised through scams increases as the number of persons who play these games grows.
Proposal for a novel type of small scale aneutronic fusion reactor

The aim of this work is to propose a novel scheme for a small scale aneutronic fusion reactor. This new reactor type makes use of the advantages of combining laser driven plasma acceleration and electrostatic confinement fusion. An intense laser beam is used to create a lithium–proton plasma with high density, which is then collimated and focused into the centre of the fusion reaction chamber. The basic concept presented here is based on the 7Li–proton fusion reaction. However, the physical and technological fundamentals may generally as well be applied to 11B–proton fusion. The former fusion reaction path offers higher energy yields while the latter has larger fusion cross sections. Within this paper a technological realisation of such a fusion device, which allows a steady state operation with highly energetic, well collimated ion beam, is presented. It will be demonstrated that the energetic break even can be reached with this device by using a combination of already existing technologies.
MD Average of Vibrational Spectra of Nucleotides in a SERS Sensor Simulation with Varying Number of Au Nanoparticles

: Applying the surface-enhanced Raman scattering (SERS) method to detect bioactive molecules such as DNA, proteins, and drugs has signiﬁcant potential for structure-sensitive non-destructive chemical analysis. The SERS discrimination of single-molecule oligomers in DNA, microRNA, and proteins has attracted wide attention due to the possibility of developing new sensing technology. The collected signal’s sensitivity has the level of detection of single oligomers, which can be compared with the simulation results corresponding to the sensor structure. We investigate the averaging method of the individual bond spectra for DNA nucleotides in the ring part of the pyrimidine (6-ring) and purine (6–5-ring) bases to form vibrational spectra obtained by molecular dynamics (MD) simulation. The system consists of the Au nanoparticles (from 1 to 4 NP assay) attached to a graphene sheet at the edge of the nanopore that localizes in the nanopore nucleotide interaction and spectral enhancement. The nucleotide translocation velocity set at 0.025 m/s compares with the experimental range. The vibrational spectra ring average has been tested for adenine and guanine with close correspondence (in the 500–1700 cm − 1 range) to the experimental Raman and SERS spectra and extended to cytosine and thymine nucleotides. We also modiﬁed the number of the Au nanoparticles from one NP to four identical NPs to evaluate the inﬂuence of the interaction on the MD transient spectra. The variations of mode frequencies and amplitudes due to the number of Au NPs in bond spectra, as well as ring averages, mark the corresponding Au–nucleotide interactions and are considered for use as training sets for machine learning methods.
Personality Trait Detection using an Hierarchy of Tree-transformers and Graph Attention Network

Automatic personality trait detection from a person’s writings is helpful for professionals to assess the mental health of an individual, as well as helping individuals to determine their strengths and weaknesses for making choices such as personal improvement, workplace compatibility, and life-style decision-making. Psychologists have identified a set of personality traits that may be present in an individual’s personality. This work classifies the writings of an individual into a subset of these traits. The classifier model comprises an hierarchical structure of tree-transformers and a graph attention network (GAT). The tree-transformers encode the sentences and the following GAT layer encodes the complete text of an individual’s writing. Our model has shown a large performance boost over two benchmark corpora compared to previous works.
An integrated nonlinear wind-waves model for offshore wind turbines

This thesis presents a numerical model capable of simulating offshore wind turbines exposed to extreme loading conditions. External condition-based extreme responses are reproduced by coupling a fully nonlinear wave kinematic solver with a hydro-aero-elastic simulator. First, a two-dimensional fully nonlinear wave simulator is developed. The transient nonlinear free surface problem is formulated assuming the potential theory and a higher-order boundary element method (HOBEM) is implemented to discretize Laplace's equation. For temporal evolution a second-order Taylor series expansion is used. The code, after validation with experimental data, is successfully adopted to simulate overturning plunging breakers which give rise to dangerous impact loads when they break against wind turbine substructures. The impact force is quantified by means of an analytical model and the total hydrodynamic action is finally obtained by adding the impulsive term to the drag and inertial ones. In the second main core of the thesis, emphasis is placed on the random nature of the waves. Indeed, a global simulation framework embedding the numerical wave simulator into a more general stochastic environment is developed. Namely, first a linear irregular sea is generated by the spectral approach, then, only on critical space-time sub-domains, the fully nonlinear solver is invoked for a more refined simulation. The space-time sub-domains are defined as the wind turbine near field (space) times the time interval in which wave impacts are expected (time). Such a domain decomposition approach permits systematically accounting for dangerous effects on the structural response (which would be totally missed by adopting linear or weakly nonlinear wave theories alone) without penalizing the computational effort normally required. At the end of the work the attention is moved to the consequences that the proposed model would have in the quantification of the structural risk.
Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis

Locomotion transition recognition with external disturbances is a key issue in lower limb robotic prostheses. Redonning the prosthetic socket and individual differences are encountered frequently in daily life. They change the feature distribution and further fail the previously trained recognition model. To bridge the technical gap between laboratory validation and practical demands, researchers need to construct an adaptive recognition method with high accuracy, quick response, time-efficient calibration, and minimal interference to the human body. Our study developed an adaptive recognition algorithm based on two miniaturized inertial sensors (anterior thigh and forefoot) and a foot pressure sensor, which can easily be integrated into the prosthesis. The algorithm fused probability-based fuzzy classifiers, which took heuristic-based features as inputs with a dynamic-time-warping-based automatic template generation block. It enables the recognition model to quickly fit the parameters for an untrained mode after external disturbances. We validated the proposed adaptive recognition method on 13 healthy subjects, performing 18 motion transitions with random interday intervals and across user evaluation, both offline and online. Even with the data of one subject as the prior knowledge, the other subjects produced an average accuracy of 98.04% and an average transition time latency of −180.99 ms without manual training in interday and intersubject uses. We also tested the method on two subjects using robotic prostheses, one person with a transfemoral amputation and the other person with a transtibial amputation. The average accuracy was still as high as 98.06% (transfemoral) and 100% (transtibial) without manual calibration after seven days of intervals. The results proved that the adaptive recognition method is robust to sensor redonning and user changes. Compared with the state-of-the-art methods, our study makes a further step toward the practical use of robotic prostheses. Future studies will be conducted to implement the algorithm on the robotic prosthesis for more extensive tests.
Application of the finite-difference time-domain method to bioelectromagnetic simulations

The finite-difference time-domain (FDTD) method has been used extensively over the last decade for bioelectromagnetic dosimetry – numerical assessment of electromagnetic fields coupled to biological bodies [Gandhi; Lin & Gandhi]. Values of interest in these assessments include induced current or current density and specific absorption rate (SAR), which is a measure of absorbed power in the body. The FDTD algorithm is extremely simple and efficient, which has made it one of the most versatile numerical methods for bioelectromagnetic simulations. It is particularly well suited to these applications because it can efficiently model the heterogeneity of the human body with high resolution (often on the order of 1mm), can model anisotropy and frequencydependent properties as needed, and can easily model a wide variety of sources coupled to the body. It has been used to analyze whole-body or partial-body exposures to spatially uniform (far field) or non-uniform (near-field) sources. These sources may be sinusoidally varying (continuous wave (CW) ) or time-varying such as those from an electromagnetic pulse (EMP). The FDTD method has been used for applications over an extremely wide range of frequencies, from 60 Hz through 6 GHz, and also for broad-band applications. This paper describes several of these applications, and some of the details of how the FDTD method is applied to bioelectromagnetic simulations.
Pathological, microscopic, and molecular diagnosis of paratuberculosis/John’s disease in naturally infected dromedary camel (Camelus dromedarius)

Background and Aim: Paratuberculosis (PTB) or John’s disease is a chronic disease of ruminants impeding the reproduction and productivity of the livestock sector worldwide. Since there is a lack of pathological studies explaining the nature and development of the disease in camels, this study aimed to highlight the anatomopathological changes of PTB in camels, which may help in verifying and validating some diagnostic tests used to detect the etiology of the disease in camel tissues. Materials and Methods: In August 2017, at Alselaa border’s Veterinary Clinic of Al Dhafra Region, Western Abu Dhabi, UAE, one imported culled she-camel of 2 years old was subjected to clinical, microscopic, and anatomopathological investigations along with real-time quantitative polymerase chain reaction (q-PCR) to confirm the infection and correlate between clinical signs and pathological lesions of the PTB in dromedary camels. Results: Clinically, typical clinical signs compliant with the pathognomonic gross and histologic lesions of PTB were seen in naturally infected dromedary camel. As presumptive diagnosis microscopically, acid-fast coccobacillus bacterium clumps were demonstrated in direct fecal smears as well as in scraped mucosal and crushed mesenteric lymph node films, and in histopathological sections prepared from a necropsied animal and stained by Ziehl-Neelsen stain. Free and intracellular acid-fast clump phagosomes were further confirmed as Mycobacterium avium subsp. paratuberculosis by q-PCR. Conclusion: Clinical signs and pathological lesions of paratuberculosis in a dromedary camel were found to be similar to those of the other susceptible hosts.
Growth traits, hematological, and ruminal fluid profile of sheep offered ensiled coffee skin replacing dried water spinach

Background and Aim: Developing simple, cost-efficient sheep feed will improve farmers’ incomes. Including coffee skin in feed offers the most technical method of increasing sheep weight gain. This study aimed to evaluate varying proportions of ensiled coffee skin replacing dried water spinach and determine the optimal combination for the growth performance, physiological and hematological profiles, and rumen fluid of sheep. Materials and Methods: Eighty-four animals were randomly allocated to the treatments, arranged in a randomized block design using the initial weight as a block. Seven treatment diets were adjusted and a 12-animal replication was used for each treatment. The treatments were as follows: T0: 30% maize stover, 30% dried water spinach, 5% pollard, 20% coffee skin; T1: 30% maize stover, 25% dried water spinach, 5% pollard, 5% ensiled coffee skin; T2: 30% maize stover, 20% dried water spinach, 5% pollard, 10% ensiled coffee skin; T3: 30% maize stover, 15% dried water spinach, 5% pollard, 15% ensiled coffee skin; T4: 30% maize stover, 10% dried water spinach, 5% pollard, 20% ensiled coffee skin; T5: 30% maize stover, 5% dried water spinach, 5% pollard, 25% ensiled coffee skin; T6: 30% maize stover, 5% pollard, and 30% ensiled coffee skin. The sheep were reared for 70 days.The parameters observed during the early stage included growth performance (initial body weight, LW gain, final body weight, and feed intake). At the end of periods, a representative sample of ruminal fluid (approximately 150 mL) was collected from slaughtered sheep, duplicated, and then incubated for 18 h and blood samples were collected from the sheep (jugular vein) in ethylenediaminetetraacetic acid tubes. Then, used to analyze various blood biochemical parameters. Results: The final body weights showed a linear curve increasing as the treatment increased (p < 0.05). The ensiled coffee skin tended to increase at 6 h incubation time, producing reduced methane gas (p < 0.05). However, in general, the use of ensiled coffee skin did not significantly alter the blood biochemistry of crossbreed sheep (p > 0.05). There was no significant effect on the protozoal population (p > 0.05). Conclusion: Increasing the level of ensiled coffee skin up to 30% replacing dried water spinach increased the final body weight of crossbreed sheep with no adverse effect.
Simultaneous Multi-Slice Reconstruction Using Regularized Nonlinear Inversion: SMS-NLINV

Purpose: To develop a calibrationless parallel imaging method for accelerated simultaneous multi-slice (SMS) MRI with Cartesian and radial k-space trajec- tories based on Regularized Nonlinear Inversion (NLINV). Theory and Methods: NLINV is a parallel imaging method that jointly estimates image content and coil sensitivities using a Newton-type method with regularization. Here, NLINV is extended to SMS-NLINV for reconstruction and separation of all simultaneously acquired slices. The performance of the extended method is evaluated for different sampling schemes using phantom and in-vivo experiments based on Cartesian and radial SMS-FLASH sequences. Results: The basic algorithm was validated in Cartesian experiments by com- parison with ESPIRiT. For Cartesian and radial sampling, improved results are demonstrated compared to single-slice experiments, and it is further shown that sampling schemes using complementary samples outperform schemes with the same samples in each partition. Conclusion: The extension of the NLINV algorithm for SMS data was im- plemented and successfully demonstrated in combination with a Cartesian and radial SMS-FLASH sequence.
The Research on the Marketing Strategies and Influence of the WeChat Mini Program Game Taking the Game Sheep a Sheep for Example

With the popularity of the WeChat mini program game Sheep a Sheep, the successful marketing strategies behind it have brought reference to the game development industry, but at the same time, Internet addiction has also brought a significant negative impact on people's daily life, for example, people often immerse themselves in the Internet and thus affect their own lives, such as vision loss and other consequences. Therefore, through the literature reading, this paper aims to discuss and analyze the marketing strategies and replicability of the game, and finally discuss the methods to prevent Internet addiction. This paper concludes that game developers can create complaining points to capture people's psychology and strengthen the sense of game experience to expand the potential user base, and finally select the right communication platform to maximize the communication benefit. To prevent Internet addiction, people can start from four aspects: psychological cognition, individual behavior, game development company, and social sector.
Nanocontacts controlled atom-by-atom in an ion-crystal friction emulator

Friction is the basic, ubiquitous mechanical interaction between two surfaces that results in resistance to motion and energy dissipation. To test long-standing atomistic models of friction processes at the nanoscale, we implemented a synthetic nanofriction interface between a laser-cooled Coulomb crystal of individually addressable ions as the moving object and a periodic light-field potential as the substrate. Through a variety of experiments presented in this thesis, we show atom-by-atom and with high spatial resolution that friction at the nanoscale can substantially differ from the simple phenomenological laws observed at the macroscale. Namely, we show that atomic-scale stick-slip friction can be tuned from maximal to nearly frictionless via arrangement of the ions relative to the periodic potential, and study the associated transition in transport dynamics as manifested by the propagation of kinks. We show that friction depends on velocity and temperature, in excellent agreement with simple analytical models, and that in the appropriate velocity regime, the dynamics can be observed in a way that is effectively at zero-temperature. We also establish a direct link between Aubry's structural transition for an infinite chain in an incommensurate periodic potential, and the vanishing of friction in nanocontacts. Our model system enables a microscopic and systematic investigation of friction, potentially even into the quantum many-body regime.
A SMOOTH TIGHT UPPER BOUND FOR THE FIBONACCI REPRESENTATION FUNCTION R(N)

The function R(n) that counts the number of representations of the integer n as the sum of distinct Fibonacci numbers has been studied for over 40 years, and many fascinating properties have been discovered. In this paper we prove that R(n) • p n + 1 for all n ‚ 0, with equality if and only if n = F 2 m i 1 for some integer m ‚ 2.
On some generalisations of Brown's conjecture

Let P be a complex polynomial of the form P (z) = z n−1 ∏ k=1 (z − zk),where |zk| ≥ 1, 1 ≤ k ≤ n− 1 then P ′(z) 6= 0. If |z| < 1 n . In this paper, we present some interesting generalisations of this result.
Discrete Models of Disease and Competition

The aim of this work is to analyze the influence of the fast development of a disease on competition dynamics. To this end we present two discrete time ecoepidemic models. The first one corresponds to the case of one parasite affecting demography and intraspecific competition in a single host, whereas the second one contemplates the more complex case of competition between two different species, one of which is infected by the parasite. We carry out a complete mathematical analysis of the asymptotic behavior of the solutions of the corresponding systems of difference equations and derive interesting ecological information about the influence of a disease in competition dynamics. This includes an assessment of the impact of the disease on the equilibrium population of both species as well as some counterintuitive behaviors in which although we would expect the outbreak of the disease to negatively affect the infected species, the contrary happens.
SMR: Spatial-Guided Model-Based Regression for 3D Hand Pose and Mesh Reconstruction

3D hand reconstruction is an important technique for human-computer interaction. Interactive experience depends on the accuracy, efficiency, and robustness of the algorithm. Therefore, in this paper, we first propose a balanced framework called spatial-aware regression (SAR) to achieve precise and fast reconstruction. SAR can bridge convolutional networks and graph-structure networks more effectively than existing frameworks to fully exploit extracted spatial information using a novel spatial-aware initial graph building module. In addition, SAR uses adaptive-GCN to make keypoints interact efficiently and effectively; and regresses 2.5D belief maps to characterize uncertainty. SAR is highly flexible because it can predict an arbitrary number of keypoints and apply pose-guided refinement for coarse to fine regression. To produce more rational results for challenging cases and mitigate 3D label reliance, we also propose a more robust model-based framework called spatial-guided model-based regression (SMR) that is based on SAR. There are two critical designs of SMR: 1) it uses SAR to enhance the features with pose information to help the regression of hand model parameters; and 2) it regresses parameters in a spatially aware manner that is similar to SAR. Experiments demonstrate that the proposed frameworks surpass existing fully-supervised approaches on the FreiHAND, HO-3D, RHD, and STB datasets. Also, the performances of the proposed frameworks under weakly/self-supervised settings outperform other competitors. Meanwhile, the proposed frameworks are accurate and efficient.
Psychology's WEIRD Problems

Psychology has a WEIRD problem. It is overly reliant on participants from Western, Educated, Industrialized, Rich, and Democratic societies. Over the last decade this problem has come to be widely acknowledged, yet there has been little progress toward making psychology more diverse. This Element proposes that the lack of progress can be explained by the fact that the original WEIRD critique was too narrow in scope. Rather than a single problem of a lack of diversity among research participants, there are at least four overlapping problems. Psychology is WEIRD not only in terms of who makes up its participant pool, but also in terms of its theoretical commitments, methodological assumptions, and institutional structures. Psychology as currently constituted is a fundamentally WEIRD enterprise. Coming to terms with this is necessary if we wish to make psychology relevant for all humanity. This title is also available as Open Access on Cambridge Core.