Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Semi-Online Optimization for Cooperative MIMO Networks With Information Parsing

We consider cooperative multiple-input multiple-output (MIMO) precoding design with multiple access points (APs) assisted by a central controller (CC) in a fading environment. Even though each AP may have its own local channel state information (CSI), due to the communication delay in the backhaul, neither the APs nor the CC has timely global CSI. Under this hierarchical semi-online setting, our goal is to minimize the accumulated precoding deviation, between the actual local precoders executed by the APs and an ideal cooperative precoder based on timely and perfect global CSI, subject to per-AP transmit power limits. We propose an efficient algorithm, termed Semi-Online Precoding with Information Parsing (SOPIP), which accounts for the network heterogeneity in information timeliness and computational capacity. SOPIP does not require the CC to send the full global CSI to each AP. Instead, it takes advantage of the precoder structure to substantially lower the communication overhead, while allowing each AP to effectively combine its own timely local CSI with the delayed global CSI to enable adaptive precoder updates. We analyze the performance of SOPIP in the presence of multi-slot communication delay, CSI inaccuracy, and gradient estimation error, showing that it has a bounded performance gap from an offline optimal solution. Simulation results under typical cellular system settings further demonstrate the substantial performance gain of SOPIP over other centralized and distributed schemes.
Actionability Judgments Cause Knowledge Judgments

Researchers recently demonstrated a strong direct relationship between judgments about what a person knows and judgments about how a person should act. But it remains unknown whether actionability judgments cause knowledge judgments, or knowledge judgments cause actionability judgments. This paper uses causal modeling to help answer this question. Across two experiments, we found evidence that actionability judgments cause knowledge judgments.
Are citizens responsive to interest groups? A field experiment on lobbying and intended citizen behaviour

The ability to mobilise public opinion is central to interest group politics. Yet, whether and how groups succeed in swaying the public remains inconclusive. The article assesses this by conducting a field experiment in which a consumer group sent different versions of campaign material to a representative sample of over 5000 citizens. Relying on a two-wave panel survey, it shows that while the campaign affected intended consumer behaviour, it did not influence attitudes. Surprisingly, material by the organisation alone was more effective than material sent with a partner. Moreover, campaign references to personal experiences and facts were not more effective than material referring to public opinion. The findings challenge existing evidence on how sender and message characteristics affect the likelihood of influencing citizens. At the same time, they underline that public opinion is hard to change and have important implications for understanding political representation and interest groups in democratic politics.
Flow Structure around a Multicopter Drone: A Computational Fluid Dynamics Analysis for Sensor Placement Considerations

This study presents a computational fluid dynamics (CFD) based approach to determine the optimal positioning for an atmospheric turbulence sensor on a rotary-wing uncrewed aerial vehicle (UAV) with X8 configuration. The vertical (zBF) and horizontal (xBF) distances of the sensor to the UAV center to reduce the effect of the propeller-induced flow are investigated by CFD simulations based on the k−ϵ turbulence model and the actuator disc theory. To ensure a realistic geometric design of the simulations, the tilt angles of a test UAV in flight were measured by flying the drone along a fixed pattern at different constant ground speeds. Based on those measurement results, a corresponding geometry domain was generated for the CFD simulations. Specific emphasis was given to the mesh construction followed by a sensitivity study on the mesh resolution to find a compromise between acceptable simulation accuracy and available computational resources. The final CFD simulations (twelve in total) were performed for four inflow conditions (2.5 m s−1, 5 m s−1, 7.5 m s−1 and 10 m s−1) and three payload configurations (15 kg, 20 kg and 25 kg) of the UAV. The results depend on the inflows and show that the most efficient way to reduce the influence of the propeller-induced flow is mounting the sensor upwind, pointing along the incoming flow direction at xBF varying between 0.46 and 1.66 D, and under the mean plane of the rotors at zBF between 0.01 and 0.7 D. Finally, results are then applied to the possible real-case scenario of a Foxtech D130 carrying a CSAT3B ultrasonic anemometer, that aims to sample wind with mean flows higher than 5 m s−1. The authors propose xBF=1.7 m and zBF=20 cm below the mean rotor plane as a feasible compromise between propeller-induced flow reduction and safety. These results will be used to improve the design of a novel drone-based atmospheric turbulence measurement system, which aims to combine accurate wind and turbulence measurements by a research-grade ultrasonic anemometer with the high mobility and flexibility of UAVs as sensor carriers.
ENSEMBLE LEARNING METHOD FOR OUTLIER DETECTION AND ITS APPLICATION TO ASTRONOMICAL LIGHT CURVES

Outlier detection is necessary for automated data analysis, with specific applications spanning almost every domain from financial markets to epidemiology to fraud detection. We introduce a novel mixture of the experts outlier detection model, which uses a dynamically trained, weighted network of five distinct outlier detection methods. After dimensionality reduction, individual outlier detection methods score each data point for “outlierness” in this new feature space. Our model then uses dynamically trained parameters to weigh the scores of each method, allowing for a finalized outlier score. We find that the mixture of experts model performs, on average, better than any single expert model in identifying both artificially and manually picked outliers. This mixture model is applied to a data set of astronomical light curves, after dimensionality reduction via time series feature extraction. Our model was tested using three fields from the MACHO catalog and generated a list of anomalous candidates. We confirm that the outliers detected using this method belong to rare classes, like Novae, He-burning, and red giant stars; other outlier light curves identified have no available information associated with them. To elucidate their nature, we created a website containing the light-curve data and information about these objects. Users can attempt to classify the light curves, give conjectures about their identities, and sign up for follow up messages about the progress made on identifying these objects. This user submitted data can be used further train of our mixture of experts model. Our code is publicly available to all who are interested.
Predicting Japanese sport tourist behaviour: an extension of theory of planned behaviour with tourism ideal affect

ABSTRACT Theoretically-informed studies and theoretical integration remain overdue in the field of sport tourism. This study focused on the theory of planned behaviour (TPB) for a critical engagement with the theory that researchers have already been employing in sport tourism research, and tourism ideal affect developed based on the affect valuation theory for those that have yet to be critically applied in sport tourism. The study aimed to investigate (a) TPB’s predictive power of intention and actual behaviour in sport tourism contexts, and (b) whether such predictive power can be enhanced by adding tourism ideal affect. Two-wave data collection was implemented in Japan, involving 418 adults. The findings demonstrated that TPB could significantly predict intention and actual behaviour in sport tourism contexts. Subjective norm predicted intention, while intention predicted sport tourism behaviour. Although adding tourism ideal affect did not improve the predictive power of intention and actual behaviour, tourism ideal low-arousal positive affect was found to be negatively related to sport tourism behaviour. Along with theoretical contributions, this research suggests that strengthening promotions involving tourists’ significant others (e.g. adding family components) by targeting Japanese people who have a lower level of tourism ideal low-arousal positive affect may be an effective approach to further sport tourism development in Japan.
A thermodynamic framework for bulk–surface partitioning in finite-volume mixed organic–inorganic aerosol particles and cloud droplets

Abstract. Atmospheric aerosol particles and their interactions with clouds are among the largest sources of uncertainty in global climate modeling. Aerosol particles in the ultrafine size range with diameters less than 100 nm have very high surface-area-to-volume ratios, with a substantial fraction of molecules occupying the air–droplet interface. The partitioning of surface-active species between the interior bulk of a droplet and the interface with the surrounding air plays a large role in the physicochemical properties of a particle and in the activation of ultrafine particles, especially those of less than 50 nm diameter, into cloud droplets. In this work, a novel and thermodynamically rigorous treatment of bulk–surface equilibrium partitioning is developed through the use of a framework based on the Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model in combination with a finite-depth Guggenheim interface region on spherical, finite-volume droplets. We outline our numerical implementation of the resulting modified Butler equation, including accounting for challenging extreme cases when certain compounds have very limited solubility in either the surface or the bulk phase. This model, which uses a single, physically constrained interface thickness parameter, is capable of predicting the size-dependent surface tension of complex multicomponent solutions containing organic and inorganic species. We explore the impacts of coupled surface tension changes and changes in bulk–surface partitioning coefficients for aerosol particles ranging in diameters from several micrometers to as small as 10 nm and across atmospherically relevant relative humidity ranges. The treatment of bulk–surface equilibrium leads to deviations from classical cloud droplet activation behavior as modeled by simplified treatments of the Köhler equation that do not account for bulk–surface partitioning. The treatments for bulk–surface partitioning laid out in this work, when applied to the Köhler equation, are in agreement with measured critical supersaturations of a range of different systems. However, we also find that challenges remain in accurately modeling the growth behavior of certain systems containing small dicarboxylic acids, especially in a predictive manner. Furthermore, it was determined that the thickness of the interfacial phase is a sensitive parameter in this treatment; however, constraining it to a meaningful range allows for predictive modeling of aerosol particle activation into cloud droplets, including cases with consideration of co-condensation of semivolatile organics.
A Novel Fractal RDRA for C-Band Applications

In this article, the authors propose a novel fractal dielectric resonator antenna (DRA) design using the golden ratio approach. The proposed antenna is evolved using a Minkowski fractal first iteration and the Fibonacci series sequence. The proposed antenna is fed with a conformal square-shaped strip for impedance matching, and to further improve the impedance bandwidth (BW) a rectangular slot is etched in the ground plane which results in defected ground structure (DGS) at the bottom. With the help of the self-similar property of fractals, higher order resonant three broadside modes first TE111 mode at 4 GHz, TE113 mode at 6.8 GHz, and TE115 mode at 8.3 GHz are brought close which leads to wider impedance BW. For experimental validation, a prototype is fabricated, and return loss, radiation pattern, and antenna gain are measured. Furthermore, reasonable agreement between the measured and simulated results is observed with an impedance BW <inline-formula> <tex-math notation="LaTeX">$S_{11}\leq -10$ </tex-math></inline-formula> dB of 82% (3.80–8.70 GHz) and a maximum gain of 7.62 dBi. The proposed antenna is best suitable for the entire <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula>-band (4–8 GHz) applications.
Evaluation of Cesarean Deliveries by using Ten Group Classification System in a Tertiary Care Centre: A Cross-Sectional Study

Introduction: Cesarean section has three times increased risk of maternal and fetal morbidities compared to vaginal delivery. The rising trend of cesarean deliveries across the globe led the WHO to recommend the use of the Ten Group classification system to monitor cesarean rate over time as well as between facilities. The cesarean section rate is increasing in our centre, so the study was conducted to evaluate the cesarean deliveries and identify the group with a major contribution to the cesarean rate so that policies could be formulated to decrease it in our centre. Method: It was a cross-sectional descriptive study conducted in the Department of Obstetrics and Gynecology, Manipal Teaching Hospital, Nepal for six months after ethical approval. All women who delivered at or beyond 28 weeks were included in the study after their consent and were classified according to Robson's classification based on their obstetric parameters. The total cesarean section rate, the size of each group, the cesarean rate in each group and the absolute contribution of each group to the overall cesarean rate were calculated and analyzed. Results: Out of 711 deliveries during the study period, the cesarean rate was 51% (n=362). Group 1(26%) was the major obstetric population followed by Group 3(20%) and Group 2(16%). Group 5(10.97%) had a major contribution to the overall cesarean rate followed by Group 1(10.68%) and Group 2 (9.7%). Conclusion: The cesarean rate in our study was high and it could be decreased by encouraging the trial of labor after cesarean and revisiting the indication of induction and cesarean in Group 1 and Group 2.
Adaptation of the sources of the mathematics self-efficacy scale for Oman: A validation study

The current study aims to adapt sources of middle school mathematics scale developed by Usher and Pajares (2009) to the Omani context. The study sample consisted of 700 students (379 girls and 321 boys) from the eighth grade in middle schools in Oman. The results of this study showed that sources of middle school mathematics self-efficacy scale (SMES) (adaption) resemble the original version of which developed by Usher and Pajares (2009). Confirmatory factor analysis showed good fit indices, with χ2=767.8, df=224, comparative fit index=. 928, standardized root mean square residual=. 0478, and root mean square error approximation=. 059. The scale also displayed a robust internal consistency–Cronbach’s alpha coefficient was above 0.8 and for its subscales as well. The indices of convergent and divergent validity for this scale were all significant (p<0.001). Therefore, SMES is psychometrically sound and can be applied to the Omani context.
Factors Influencing the Performance of Accounting Information Systems University Public Services Agency

In particular, this study aimed to determine the ability of organizational commitment and top management support to moderate the influence of factors such as: user capabilities, user workshops, formalization of IS development, IS controlling committee. Qualitative and quantitative data types from primary sources were collected by distributing questionnaires (which had met the validity and reliability tests) to 125 respondents throughout the Udayana University Public Service Board who were directly and actively involved in the implementation of SIAKU. Then the response data that has been collected is tabulated and then tested for compliance with the classical assumption test. Next, the model feasibility test and termination coefficient analysis were carried out, the research hypothesis was tested using the MRA technique. Based on the results of the MRA analysis that has been done, it can be concluded that personal capabilities and workshops / user training have a negative but not significant effect on AIS performance; organizational commitment and IS controlling committee have a positive and significant effect on AIS performance; IS development formalization and top management support has a positive but not significant effect on AIS performance; organizational commitment is able to moderate the influence of the IS controlling committee on AIS performance; organizational commitment is unable to moderate the influence of personal capabilities, workshops /training, formalization of IS development on AIS performance; top management support was not able to moderate the influence of personal capabilities, workshops /training, IS development formalization, and IS control committee on AIS performance.
Phase mixing of Alfvén waves in two-dimensional magnetic plasma configurations with exponentially decreasing density

We study damping of phase-mixed Alfvén waves propagating in axisymmetric magnetic plasma configurations. We use the linear magnetohydrodynamic (MHD) equations in the cold plasma approximation. The only dissipative process that we take into account is shear viscosity. We reduce the MHD equations describing the Alfvén wave damping to a Klein–Gordon-type equation. We assume that the two terms in this equation, one describing the effect of inhomogeneity and the other the effect of viscosity, are small. Then we use the WKB method to derive the expression describing the wave energy flux attenuation with the height. We apply the general theory to particular equilibria with the exponentially divergent magnetic field lines with the characteristic scale H. The plasma density exponentially decreases with the height with the characteristic scale Hρ. We study the wave damping for typical parameters of coronal plumes and various values of the wave period, the characteristic scale of the magnetic field variation H, and kinematic shear viscosity ν. We show that to have an appreciable wave damping at the height 6H we need to increase shear viscosity by at least six orders of magnitude in comparison with the value given by the classical plasma theory. Another important result is that the efficiency of wave damping strongly depends on the ratio H/Hρ. It increases fast when H/Hρ decreases. We present a physical explanation of this phenomenon.
Frequency stabilization of DFB laser via modulation transfer spectroscopy

We demonstrate frequency stabilization of DFB laser via modulation transfer spectroscopy, which avoids the interference of Doppler absorption spectrum. By modulating the frequency of laser beam(pump laser beam), the other laser beam(probe laser beam) overlap pump laser beam is modulated as the same frequency by nonlinear interaction. By demodulating the signal from detection beam, an error signal is generated through the low pass filter. The frequency is stabilized at the 0 point position of the MTS frequency discrimination curve by PID loop which shows frequency fluctuation is less than 149 kHz, and the relative frequency stability is improved by nearly two orders of magnitude.
Modeling of non‐Fickian diffusion and dissolution from a thin polymeric coating: An application to drug‐eluting stents

In this paper, we present a general model for non‐Fickian diffusion and drug dissolution from a controlled drug delivery device coated with a thin polymeric layer. First, we study the stability and deduce an analytic solution to the problem. Then, we consider this solution and provide suitable boundary conditions to replace the problem of mass transport in the coating of a coronary drug‐eluting stent. With this approach, we reduced the computational cost of performing numerical simulations in complex 3‐dimensional geometries. The model for mass transport by a coronary drug‐eluting stent is coupled with a non‐Newtonian blood model flow. In order to show the effectiveness of the method, numerical experiments and a model validation with experimental data are also included. In particular, we investigate the influence of the non‐Newtonian flow regime on the drug deposition in the arterial wall.
Research note: The educational gradient of divorce in the Czech Republic during the late post-socialist transition

Objective: This study aims to describe the educational gradient and the role of educational homogamy in divorce risk in the Czech Republic. Background: The Czech Republic underwent a social transformation in the 1990s, which resulted in a significant change in many demographic trends. In contrast, the divorce trend seems to have been less affected. My aim is to describe the evolution of the patterns of the educational gradient of divorce during the late phase of the post-communist transformation. Method: Register data on marriages contracted in 1995, 2000, and 2005 were supplemented with divorce register records up to 2020. Besides the duration of the marriage, the data contains information on the education, age, and marital status of both partners at the time of marriage. The Kaplan-Meier curves and the Cox regression are used for the analysis. Results: The risk of divorce is substantially higher for the less educated, and this holds across all three marriage cohorts observed here. Homogamous marriages are not the most stable ones. From an individual's perspective, marriage with a more educated partner shows the highest stability. Conclusion: This analysis confirmed the stability of the negative educational gradient of marriages contracted during the late phase of the post-communist transition period in the Czech Republic. It refutes the notion that the higher relative education of the woman or man in the couple destabilises partnerships.
An open-source method of constructing cloud-free composites of forest understory temperature using MODIS

ABSTRACT Surface air temperature (Tair) is a critical driver of ecosystem processes and phenological dynamics, and can be estimated in near-real time with satellite remote sensing. However, persistent cloud cover often creates large spatial and temporal gaps in our observation records. Previous studies have successfully mapped Tair; however, the challenges of mapping forest understory temperatures (Tust) are relatively unexplored. This study describes a methodology for constructing cloud-free composites of Tust at 250 m spatial resolution. We used generalized linear models to correlate daily average Tust with ground-surveyed forest structural characteristics and land surface temperature (LST) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). Models were applied to all four daily MODIS overpasses and combined in to a single image to maximize cloud-free spatial coverage. Pixel temperatures within the remaining cloud gaps were estimated using a temporal averaging algorithm that incorporated a novel approach for factoring the relative cloudiness between days. Models predicted Tust to within 1.5°C (R2 ~ 0.87), with an overall final map accuracy having a mean absolute error of 2.2°C. Maps were produced for two growing seasons using in situ observation data from forested sites throughout the Rocky Mountains of Alberta, Canada. By avoiding complex physical models, our procedure is computationally efficient and capable of processing large volumes of data using open-source programming languages and desktop computers.