Miracle-dz/UniFAR-FTUs huggingface dataset:
Fossil field decay due to nonlinear tides in massive binaries

Context.Surface magnetic fields have been detected in 5–10% of isolated massive stars, hosting outer radiative envelopes. They are often thought to have a fossil origin, resulting from the stellar formation phase. Yet, magnetic massive stars are scarcer in (close) short-period binaries, as reported by the BinaMIcS (Binarity and Magnetic Interaction in various classes of Stars) Collaboration.Aims. Different physical conditions in the molecular clouds giving birth to isolated stars and binaries are commonly invoked. In addition, we propose that the observed lower magnetic incidence in close binaries may be due to nonlinear tides. Indeed, close binaries are probably prone to tidal instability, a fluid instability growing upon the equilibrium tidal flow via nonlinear effects. Yet, stratified effects have hitherto been largely overlooked.Methods. We theoretically and numerically investigate tidal instability in rapidly rotating, stably stratified fluids permeated by magnetic fields. We use the short-wavelength stability method to propose a comprehensive (local) theory of tidal instability at the linear onset, discussing damping effects. Then, we propose a mixing-length theory for the mixing generated by tidal instability in the nonlinear regime. We successfully assess our theoretical predictions against proof-of-concept, direct numerical simulations. Finally, we compare our predictions with the observations of short-period, double-lined spectroscopic binary systems.Results. Using new analytical results, cross-validated by a direct integration of the stability equations, we show that tidal instability can be generated by nonlinear couplings of inertia-gravity waves with the equilibrium tidal flow in short-period massive binaries, even against the Joule diffusion. In the nonlinear regime, a fossil magnetic field can be dissipated by the turbulent magnetic diffusion induced by the saturated tidal flows.Conclusions. We predict that the turbulent Joule diffusion of fossil fields would occur in a few million years for several short-period massive binaries. Therefore, turbulent tidal flows could explain the observed dearth of some short-period magnetic binaries.
Dynamic SFC Embedding Algorithm Assisted by Federated Learning in Space–Air–Ground-Integrated Network Resource Allocation Scenario

Traditional terrestrial wireless communication networks cannot support the requirements for high-quality services for artificial intelligence applications such as smart cities. The space–air–ground-integrated network (SAGIN) could provide a solution to address this challenge. However, SAGIN is heterogeneous, time-varying, and multidimensional information sources, making it difficult for traditional network architectures to support resource allocation in large-scale complex network environments. This article proposes a service provision method based on service function chaining (SFC) to solve this problem. Network function virtualization (NFV) is essential for efficient resource allocation in SAGIN to meet the resource requirements of user service requests. We propose a federated learning (FL)-based algorithm to solve the embedding problem of SFCs in SAGIN. The algorithm considers different characteristics of nodes and resource load to balance resource consumption. Then, an SFC scheduling mechanism is proposed that allows SFC reconfiguration to reduce the service blocking rate. Simulation results show that our proposed FL-VNFE algorithm is more advantageous compared to other algorithms, with 12.9%, 2.52%, and 10.5% improvement in long-term average revenue, acceptance rate, and long-term average revenue–cost ratio, respectively.
Modeling and Prediction of Environmental Factors and Chlorophyll a Abundance by Machine Learning Based on Tara Oceans Data

It is of great theoretical and practical significance to understand the inherent relationship and evolution patterns among various environmental factors in the oceans. In this study, we used scientific data obtained by the Tara Oceans Project to conduct a comprehensive correlation analysis of marine environmental factors. Using artificial intelligence and machine learning methods, we evaluated different methods of modeling and predicting chlorophyll a (Chl-a) concentrations at the surface water layer of selected Tara Oceans data after the raw data processing. Then, a Pearson correlation and characteristic importance analysis between marine environmental factors and the Chl-a concentrations was conducted, and thus a comprehensive correlation model for environmental factors was established. With these obtained data, we developed a new prediction model for the Chl-a abundance based on the eXtreme Gradient Boosting (XGBoost) algorithm with intelligent parameter optimization strategy. The proposed model was used to analyze and predict the abundance of Chl-a abundance of TOP. The obtained predicted results were also compared with those by using other three widely-used machine learning methods including the random forest (RF), support vector regression (SVR) and linear regression (LR) algorithms. Our results show that the proposed comprehensive correlation evaluation model can identify the effective features closely related to Chl-a, abundance, and the prediction model can reveal the potential relationship between environmental factors and the Chl-a concentrations in the oceans.
Analytical Methods for Mathematical Modeling of Dye-Sensitized Solar Cells (DSSCs) Performance for Different Local Natural Dye Photosensitizers

In this paper, a new approach to generate the modified ideal diode factor of solar cells was developed which overcomes the problem of assuming its value a constant. Five models were employed to calculate the five-model parameters of one standard solar cell and fourteen DSSCs with varying photosensitizers. The results exhibit the conversion efficiencies of the solar cells studied lies in the range 2.57% ≤ η ≤ 0.03%. In particular, the standard cell has the highest efficiency 3.02% followed by DSSCs with photosensitizers: bitter gourd (2.57%), mango (1%), and bougainvillea (0.83%). Also, the five model parameters calculated are all positive for El Tayyan model and the rest of the models show discrepancies of varying degrees. Furthermore, despite the existence of these discrepancies, the results reveal good fit between the model data and experimental data I-V curves. This suggests the tendency or possibility that irregular parameters may be desirable for some applications. Thus, the discrepancies found in the estimated parameters can serve as a vital assessment criterion and tool for researchers and engineers in selecting the appropriate parameter estimation method for their applications. Keywords: Analytical methods, Mathematical modeling, DSSCs, Photosensitizers, Irregular parameters, Conversion efficiency.
A heuristic gait template planning and dynamic motion control for biped robots

Abstract Biped robots with dynamic motion control have shown strong robustness in complex environments. However, many motion planning methods rely on models, which have difficulty dynamically modifying the walking cycle, height, and other gait parameters to cope with environmental changes. In this study, a heuristic model-free gait template planning method with dynamic motion control is proposed. The gait trajectory can be generated by inputting the desired speed, walking cycle, and support height without a model. Then, the stable walking of the biped robot can be realized by foothold adjustment and whole-body dynamics model control. The gait template can be changed in real time to achieve gait flexibility of the biped robot. Finally, the effectiveness of the method is verified by simulations and experiments of the biped robot BHR-B2. The research presented here helps improve the gait transition ability of biped robots in dynamic locomotion.
Hand hygiene practices among Jordanian nurses in Amman

Background Hand hygiene is a simple and effective practice that helps to reduce the spread of hospital-acquired infections. However, health care professionals' adherence to hand hygiene guidelines is low. The purpose of this study is to evaluate hand hygiene practices among Jordanian nurses working in hospitals. Methodology The standardized version of the World Health Organization (WHO) questionnaire was given to Jordanian nurses from two hospitals in Amman. Result The response rate was 76 percent, with 173 nurses contacted to enroll 226 participants. According to the study, 65.5 percent (113) of the participants have a good practice hand hygiene, while 11 percent (19) practiced poor hand hygiene. The percentage of female participants who practiced good hand hygiene was found to be significantly higher (70 percent) than the percentage of male participants (30 percent). Conclusion To improve compliance with hand hygiene practices, male nurses and nurses working in the department of internal medicine and pediatrics need in-service educational intervention. Posters and other visual aids emphasizing the importance of hand hygiene should be displayed in all departments to raise awareness of the importance of hand hygiene among nurses.
Vulnerability and Exposure of Mediterranean Coastal Cities to Climate Change-Related Phenomena

: The extreme events that the planet is experiencing are indisputable proof of climate change. Effective strategies are required to reduce the exposure and vulnerability of cities to such risks. This work aims to contribute to the cultural and technical debate on the governance of urban transformations for limiting the impacts related to global warming, focusing on the cities of the Mediterranean Sea. The research shows how social and economic characteristics inﬂuence the response of cities to climate change-related hazards. This consideration reinforces the idea of seeking integrated solutions to improve the resilience of coastal urban areas within the entire basin.
A new algorithm for image denoising

The differences between the wavelet denoising method and traditional denoising method have been analyzed in this paper. Wavelet coefficients of the neighborhood characteristics have been analyzed on the basis of original global threshold value. A new algorithm based on the characteristics of the neighborhood has been proposed by establishing windows for each coefficient. It is found that the new algorithm is more effective than traditional algorithms at the aspect of improving the quality of the denoised images.
Weak-lensing analysis of galaxy pairs using CS82 data

Here we analyze a sample of close galaxy pairs (relative projected separation < 25 h−1 kpc and relative radial velocities < 350 km s−1) using a weak-lensing analysis based on the Canada-France-Hawaii Telescope Stripe 82 Survey (CS82). We determine halo masses for the total sample of pairs as well as for interacting, red, and higher-luminosity pair subsamples with ∼3σ confidence. The derived lensing signal for the total sample can be fitted either by a Singular Isothermal Sphere (SIS) with σV = 223 ± 24 km s−1 or a Navarro–Frenk–White (NFW) profile with R200 = 0.30 ± 0.03 h−1 Mpc. The pair total masses and total r band luminosities imply an average mass-to-light ratio of ∼200 h M⊙/L⊙. On the other hand, red pairs which include a larger fraction of elliptical galaxies, show a larger mass-to-light ratio of ∼345 h M⊙/L⊙. Derived lensing masses were compared to a proxy of the dynamical mass, obtaining a good correlation. However, there is a large discrepancy between lensing masses and the dynamical mass estimates, which could be accounted for by astrophysical processes such as dynamical friction, by the inclusion of unbound pairs, and by significant deviations of the density distribution from SIS and NFW profiles in the inner regions. We also compared lensing masses with group mass estimates, finding very good agreement with the sample of groups with two members. Red and blue pairs show large differences between group and lensing masses, which is likely due to the single mass-to-light ratio adopted to compute the group masses.
No-cloning theorem and teleportation criteria for quantum continuous variables

We discuss the criteria presently used for evaluating the eﬃciency of quantum teleportation schemes for continuous variables. Using an argument based upon the diﬀerence between 1-to-2 quantum cloning (quantum duplication) and 1-to-inﬁnity cloning (classical measurement), we show that a ﬁdelity value larger than 2/3 is required for successful quantum teleportation of coherent states. This value has not been reached experimentally so far.
A Compensation and Calibration Technique for Lumped Hybrid Couplers in Integrated Image-Reject Architectures

This paper presents a compensation and calibration technique for lumped-element Lange hybrid couplers. The target of the compensation is the reduction of the quadrature error introduced by lossy reactive components. An approximated, but reasonably accurate, analysis links the finite quality factor of the passive components to the quadrature error. A simple compensation technique, that corrects for the quadrature error, is proposed along with a calibration procedure. To verify the effectiveness of the proposed technique, a lumped-element Lange hybrid coupler working at an intermediate frequency of 3GHz is embedded in a fully integrated image-reject up/down-converter implemented in a 28nm bulk CMOS technology. Measurements show that the proposed technique yields an increase of the image rejection ratio from 24dB to 45dB for an up converted signal at 28GHz.
Stripe order and magnetic transitions in La 2-x Sr x NiO 4

Magnetic order has been investigated in stripe-ordered La(2-x)Sr(x)NiO(4) (x = 0.275, 0.37, 0.4) by d.c. magnetization and by polarized- and unpolarized-neutron diffraction. In the magnetically ordered phase, all three compositions exhibit a magnetic transition consistent with a spin reorientation in the ab plane. For x = 0.37, the spin axes rotate from an angle of 37.7 +/- 0.3 degrees to the stripe direction at 71 K, to 52.3 +/- 0.2 degrees at 2 K. The x = 0.275 and 0.4 compounds were found to undergo a similar spin reorientation. A spin reorientation has now been observed to occur for five different doping levels in the range x = 0.275 - 0.5, suggesting that this spin transition is an intrinsic property of the stripe phase.
Monopole-antimonopole interaction potential

We numerically study the interactions of twisted monopole-antimonopole pairs in the 't Hooft-Polyakov model for a range of values of the scalar to vector mass ratio. We also recover the sphaleron solution at maximum twist discovered by Taubes, and map out its energy and size as functions of parameters.
Evaluation of heating effects on atoms trapped in an optical trap

We solve a stochastic master equation based on the theory of Savard et al. [T. A. Savard. K. M. O'Hara, and J. E. Thomas, Phys, Rev. A 56, R1095 (1997)] for heating arising from fluctuations in the trapping laser intensity. We compare with recent experiments of Ye et al. [J. Ye, D. W. Vernooy, and H. J. Kimble, Phys. Rev. Lett. 83, 4987 (1999)], and find good agreement with the experimental measurements of the distribution of trap occupancy times. The major cause of trap loss arises from the broadening of the energy distribution of the trapped atom, rather than the mean heating rate, which is a very much smaller effect.
Spectral determinant method for interacting N-body systems including impurities

A general expression for the Green's function of a system of N particles (bosons/fermions) interacting by contact potentials, including impurities with Dirac-delta-type potentials, is derived. In one dimension for $Ng2$ bosons from our spectral determinant method the numerically calculated energy levels agree very well with those obtained from the exact Bethe ansatz solutions while they are an order-of-magnitude more accurate than those found by direct diagonalization. For $N=2$ bosons the agreement is shown analytically. In the case of $N=2$ interacting bosons and one impurity, the energy levels are calculated numerically from the spectral determinant of the system. The spectral determinant method is applied to an interacting fermion system including an impurity to calculate the persistent current at the presence of magnetic field.
Dual-wavelength square pulses fiber laser based on nonlinear effect

In this paper, a dual-wavelength square pulses fiber laser with tunable pulse width based on nonlinear polarization rotation and nonlinear effect was studied. The fiber laser containing a 1050-m highly nonlinear fiber operated at central wavelengths of 1533 nm and 1569 nm and the repetition rate was 194.7 kHz. While the polarization state of the laser was unchanged, the pump power was increased from 100 mW to 300 mW, and the pulse width was extended from 163.6 ns to 558.2 ns. In this process, the maximum energy of a single pulse was 8.57 nJ. The simple, compact square pulse dual wavelength fiber laser with tunable pulse width can meet great potential for applications.
Theoretical study of a four-level EIT-type system in the presence of structured coupling light for microwave field detection.

In this work, we have theoretically studied the four-level atomic system for the measurement of a microwave (MW) field. We employed the electromagnetically induced transparency (EIT) technique for finding the MW field in the presence of a Laguerre-Gaussian (LG) beam as a coupling light. We have shown that, by the application of LG modes, narrower dips for the probe absorption spectrum can be generated, which can be easily identified and gives better resolution compared with the Gaussian mode. An exact location of dips in the probe absorption spectrum is found, and it is useful in the measurement of MW fields. We have estimated the FWHM of the probe absorption spectrum for Gaussian and LG coupling cases as 3.74×105 H z and 1.07×105 H z, respectively. Based on FWHM, we have found that minimum change in MW electric field in the order of 3. 32µV c m -1 will be detectable in the case of the LG mode as a coupling beam.
EoR Foregrounds: the Faint Extragalactic Radio Sky

Abstract A wealth of new data from upgraded and new radio interferometers are rapidly improving and transforming our understanding of the faint extra-galactic radio sky. Indeed the mounting statistics at sub-mJy and μJy flux levels is finally allowing us to get stringent observational constraints on the faint radio population and on the modeling of its various components. In this paper I will provide a brief overview of the latest results in areas that are potentially important for an accurate treatment of extra-galactic foregrounds in experiments designed to probe the Epoch of Reionization.
Avian influenza (H5N1) virus, epidemiology and its effects on backyard poultry in Indonesia: a review

Avian influenza (AI) is a zoonotic viral endemic disease that affects poultry, swine, and mammals, including humans. Highly pathogenic avian influenza (HPAI) is caused by influenza type A virus subtypes H5, and H7 which are naturally carried by a wild bird and often affect domestic poultry. Avian influenza (AI) is a major problem worldwide that causes significant economic losses in the poultry sector. Since 2003, the widespread H5N1 HPAI in poultry has led to high mortalities resulting in huge economic losses in the poultry sector in Indonesia. Domestic poultry is a key source of income that contributes to economic growth, both directly and indirectly, by reducing poverty among the people living in rural communities. Furthermore, in many developing countries, including Indonesia, rural people meet a portion of their food needs through backyard poultry. Nevertheless, this sector is strongly affected by biosecurity hazards, particularly in Indonesia by HPAI infections. Avian influenza (AI), subtype H5N1 has zoonotic significance, posing major risks to public health and poultry. Due to close interaction between wild migratory birds and ducks, the domestic poultry sector in Indonesia is directly affected by this virus. This virus continues to be ubiquitous in Indonesia as a result of the unpredictable mutations produced by antigenic drift and shift, which can persist from a few days to several years. In this review, the epidemiology and impact, of highly pathogenic avian influenza H5N1 subtype virus infection on backyard poultry in Indonesia were discussed.
Mapping the Literature on Diet and Multiple Sclerosis: A Data-Driven Approach

Multiple sclerosis (MS) is a chronic neurological disease of the central nervous system that is currently incurable. Diet may influence the onset and progression of MS. A variety of literature reviews have been conducted in the field of diet and MS. However, conventional reviews mostly focus on specific topics rather than delivering a holistic view of the literature landscape. Using a data-driven approach, we aimed to provide an overview of the literature on diet and MS, revealing gaps in knowledge. We conducted citation network analysis to identify clusters of all available publications about diet and MS over the past 50 years. We also conducted topic analysis of each cluster and illustrated them in word clouds. Four main clusters were identified from 1626 publications: MS risk and symptom management; mouse models of MS; gluten sensitivity; and dysphagia. Citation network analysis revealed that in this emerging field, articles published after 1991 were more likely to be highly cited. Relatively few studies focused on MS disease progression compared to risk factors, and limited evidence was available for many foods and nutrients in relation to MS. Future studies could focus on filling these identified knowledge gaps.
A low-cost remote driver sleep monitoring system

Today, the use of smart transportation systems has become widespread due to the change in the structure of cities, technological developments, and the increase in the number of vehicles. It aims at targets such as reducing the damage to people and the environment by increasing traffic safety with smart transportation systems. In addition, one of the big problems of long-distance drivers is falling asleep while driving. This is an event that puts both the driver’s life, the passengers in the vehicle, and the vehicles on the road in danger, and puts the company in a difficult situation if it works for a company. In this direction, the driver sleep alarm project has been developed. This project is a control system based on monitoring the user, measuring, and analyzing their movements. Literature research, which is the first stage of the project, was conducted and research continued throughout the project process. Within the scope of this project, a headset was designed for the driver’s sleep alarm and a mobile application was created. The first prototype of the project was built. First, in the project, the angle values made by the driver's head were produced with the IMU connected to the microcontroller. 10° to 20° margins identified as sleeping state for roll, pitch, and yaw angles. Later, a wearable headset was designed for the driver. Based on these angles produced in the microcontroller, an algorithm has been created that detects whether the driver is asleep. These generated angle values and status information were transferred from the headset to the mobile application via Bluetooth. This data transferred in the mobile application is reflected on the screen. In addition, an algorithm has been created in the mobile application, which sends a notification to the driver when sleep status is detected and sends an informative SMS to the headquarters if the driver is unresponsive to this notification. For the second prototype, it was aimed to produce a PCB for the headset and thus make a new mechanical design. Data mining applications are planned with the collected data from drivers for future works.