Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Channel Estimation and Data Detection for Hybrid RIS Aided Millimeter Wave OTFS Systems

For high mobility communication scenario, the recently emerged orthogonal time frequency space (OTFS) modulation introduces a new delay-Doppler domain signal space, and can provide better communication performance than traditional orthogonal frequency division multiplexing system. This article focuses on the joint channel estimation and data detection (JCEDD) for hybrid reconfigurable intelligent surface (HRIS) aided millimeter wave (mmWave) OTFS systems. Firstly, a new transmission structure is designed. Within the pilot durations of the designed structure, partial HRIS elements are alternatively activated. The time domain channel model is then exhibited. Secondly, the received signal model for both the HRIS over time domain and the base station over delay-Doppler domain are studied. Thirdly, by utilizing channel parameters acquired at the HRIS, an HRIS beamforming design strategy is proposed. For the OTFS transmission, we propose a JCEDD scheme over delay-Doppler domain. In this scheme, message passing (MP) algorithm is designed to simultaneously obtain the equivalent channel gain and the data symbols. On the other hand, the channel parameters, i.e., the Doppler shift, the channel sparsity, and the channel variance, are updated through expectation-maximization (EM) algorithm. By iteratively executing the MP and EM algorithm, both the channel and the unknown data symbols can be accurately acquired. Finally, simulation results are provided to validate the effectiveness of our proposed JCEDD scheme.
Widespread partisan gerrymandering mostly cancels nationally, but reduces electoral competition

Significance Legislative redistricting plans determine how voters’ preferences are translated into representatives’ seats. Political parties may manipulate the redistricting process to gain additional seats and insulate incumbents from electoral competition, a process known as gerrymandering. But detecting gerrymandering is difficult without a representative set of alternative plans that comply with the same geographic and legal constraints. Harnessing recent algorithmic advances, we study such a collection of alternative redistricting plans that can serve as a nonpartisan baseline. This methodological approach can distinguish electoral bias due to partisan effects from electoral bias due to other factors. Studying the U.S. House of Representatives, a legislature of 435 seats, We find that Democrats are structurally and geographically disadvantaged in by eight seats, while partisan gerrymandering disadvantages them by two seats.
Population study for gamma-ray pulsars: (III) Radiation characteristics and viewing geometry

We have performed a Monte-Calro simulation for Galactic population of pulsars and for the $\gamma$-ray observations. We apply outer gap model for the $\gamma$-ray emission process, and study the radiation characteristics as a function of the magnetic inclination angle $(\alpha)$ and the Earth viewing angle ($\zeta$). In our model, the $\gamma$-ray flux and the spectral cut-off energy tend to decrease as the inclination and viewing angles deviate from $90^{\circ}$. The emerging spectrum above 100 MeV becomes soft with a photon index $p\sim 1.8-2$ for $\zeta \rightarrow 90^{\circ}$ and $p\sim 1.2-1.3$ for $\zeta \ll 90^{\circ}$. Our simulation predicts that the pulsars with larger inclination angles ($\alpha=70-90^{\circ}$) and larger viewing angles ($\zeta=70-90^{\circ}$) have been preferentially detected by the $Fermi$ $\gamma$-ray telescope, and hence the observed pulse profiles of the $\gamma$-ray pulsars have the double peak structure rather than single peak. In the simulation, most $\gamma$-ray millisecond pulsars are categorized as the radio-quiet $\gamma$-ray pulsars, because its radio fluxes are under the sensitivities of the major radio surveys. Even we drastically increase the radio sensitivity by a factor of ten, the number of radio-selected millisecond pulsars detected by the $Fermi$ ten years observations is still much less than the expected $\gamma$-ray-selected millisecond pulsars, indicating the radio-quiet millisecond pulsars must contribute to the $Fermi$ unidentified sources and/or the $\gamma$-ray background radiations. The Unique radiation properties of the low-efficient $\gamma$-ray pulsar, PSR J0659+1414, can be explained by the present our gap model with a viewing geometry of $\alpha\sim \zeta=40^{\circ}-50^{\circ}$.
Orthogonal Gated Recurrent Unit with Neumann-Cayley Transformation

In recent years, using orthogonal matrices has been shown to be a promising approach in improving Recurrent Neural Networks (RNNs) with training, stability, and convergence, particularly, to control gradients. While Gated Recurrent Unit (GRU) and Long Short Term Memory (LSTM) architectures address the vanishing gradient problem by using a variety of gates and memory cells, they are still prone to the exploding gradient problem. In this work, we analyze the gradients in GRU and propose the usage of orthogonal matrices to prevent exploding gradient problems and enhance long-term memory. We study where to use orthogonal matrices and we propose a Neumann series-based Scaled Cayley transformation for training orthogonal matrices in GRU, which we call Neumann-Cayley Orthogonal GRU, or simply NC-GRU. We present detailed experiments of our model on several synthetic and real-world tasks, which show that NC-GRU signiﬁcantly outperforms GRU as well as several other RNNs.
Memory-Driven Text-to-Image Generation

We introduce a memory-driven semi-parametric approach to text-to-image generation, which is based on both parametric and non-parametric techniques. The non-parametric component is a memory bank of image features constructed from a training set of images. The parametric component is a generative adversarial network. Given a new text description at inference time, the memory bank is used to selectively retrieve image features that are provided as basic information of target images, which enables the generator to produce realistic synthetic results. We also incorporate the content information into the discriminator, together with semantic features, allowing the discriminator to make a more reliable prediction. Experimental results demonstrate that the proposed memory-driven semi-parametric approach produces more realistic images than purely parametric approaches, in terms of both visual fidelity and text-image semantic consistency.
Double Auctions with Two-sided Bandit Feedback

Double Auction enables decentralized transfer of goods between multiple buyers and sellers, thus underpinning functioning of many online marketplaces. Buyers and sellers compete in these markets through bidding, but do not often know their own valuation a-priori. As the allocation and pricing happens through bids, the profitability of participants, hence sustainability of such markets, depends crucially on learning respective valuations through repeated interactions. We initiate the study of Double Auction markets under bandit feedback on both buyers' and sellers' side. We show with confidence bound based bidding, and `Average Pricing' there is an efficient price discovery among the participants. In particular, the regret on combined valuation of the buyers and the sellers -- a.k. a. the social regret -- is $O(\log(T)/\Delta)$ in $T$ rounds, where $\Delta$ is the minimum price gap. Moreover, the buyers and sellers exchanging goods attain $O(\sqrt{T})$ regret, individually. The buyers and sellers who do not benefit from exchange in turn only experience $O(\log{T}/ \Delta)$ regret individually in $T$ rounds. We augment our upper bound by showing that $\omega(\sqrt{T})$ individual regret, and $\omega(\log{T})$ social regret is unattainable in certain Double Auction markets. Our paper is the first to provide decentralized learning algorithms in a two-sided market where \emph{both sides have uncertain preference} that need to be learned.
Spectral analysis of 22 radio pulsars using SKA-Low precursor stations

Abstract We present the first observational study of pulsars performed with the second-generation precursor stations to the low-frequency component of the Square Kilometre Array (SKA-Low): the Aperture Array Verification System 2 (AAVS2) and the Engineering Development Array 2 (EDA2). Using the SKA-Low stations, we have observed 100 southern-sky pulsars between 70–350 MHz, including follow-up observations at multiple frequencies for a selected sample of bright pulsars. These observations have yielded detections of 22 pulsars, including the lowest-frequency detections ever published for 6 pulsars, despite the modest sensitivity of initial system where the recording bandwidth is limited to ${\sim}{1}\,\mathrm{MHz}$ . By comparing simultaneous flux density measurements obtained with the SKA-Low stations and performing rigorous electromagnetic simulations, we verify the accuracy of the SKA-Low sensitivity simulation code presented in Sokolowski (2022, PASA, 39, e015). Furthermore, we perform model fits to the radio spectra of the detected pulsars using the method developed by Jankowski (2018, MNRAS, 473, 4436), including nine pulsars which were not fitted in the original work. We robustly classify the spectra into five morphological classes and find that all but one pulsar exhibit deviations from simple power-law behaviour. These findings suggest that pulsars with well-determined spectra are more likely to show spectral flattening or turnover than average. Our work demonstrates how SKA-Low stations can be meaningfully used for scientifically useful measurements and analysis of pulsar radio spectra, which are important inputs for informing pulsar surveys and science planned with the SKA-Low.
Handling Interference in Integrated HAPS-Terrestrial Networks Through Radio Resource Management

Vertical heterogeneous networks (vHetNets) are promising architectures to bring significant advantages for 6G and beyond mobile communications. High altitude platform station (HAPS), one of the nodes in the vHetNets, can be considered as a complementary platform for terrestrial networks to meet the ever-increasing dynamic capacity demand and provide sustainable wireless networks for future. However, the problem of interference is the bottleneck for the optimal operation of such an integrated network. Thus, designing efficient interference management techniques is inevitable. In this letter, we aim to design a joint power-subcarrier allocation scheme in order to achieve fairness for all users. We formulate the max-min fairness (MMF) optimization problem and develop a rapid converging iterative algorithm to solve it. Numerical results validate the superiority of the proposed algorithm and show better performance over other conventional network scenarios.
Intuitive joint priors for Bayesian linear multilevel models: The R2D2M2 prior

The training of high-dimensional regression models on comparably sparse data is an important yet complicated topic, especially when there are many more model parameters than observations in the data. From a Bayesian perspective, inference in such cases can be achieved with the help of shrinkage prior distributions, at least for generalized linear models. However, real-world data usually possess multilevel structures, such as repeated measurements or natural groupings of individuals, which existing shrinkage priors are not built to deal with. We generalize and extend one of these priors, the R2D2 prior by Zhang et al. (2020), to linear multilevel models leading to what we call the R2D2M2 prior. The proposed prior enables both local and global shrinkage of the model parameters. It comes with interpretable hyperparameters, which we show to be intrinsically related to vital properties of the prior, such as rates of concentration around the origin, tail behavior, and amount of shrinkage the prior exerts. We offer guidelines on how to select the prior's hyperparameters by deriving shrinkage factors and measuring the effective number of non-zero model coefficients. Hence, the user can readily evaluate and interpret the amount of shrinkage implied by a specific choice of hyperparameters. Finally, we perform extensive experiments on simulated and real data, showing that our inference procedure for the prior is well calibrated, has desirable global and local regularization properties and enables the reliable and interpretable estimation of much more complex Bayesian multilevel models than was previously possible.
A Multifilters Approach to Adaptive Event-Triggered Control of Uncertain Nonlinear Systems With Global Output Constraint

This article focuses on the problem of adaptive event-triggered output feedback control for a class of uncertain nonlinear systems under the output constraint. Different from the existing works, the time-varying parameters and the global output constraint are taken into account. First, by means of multifilters, the unmeasurable state variables are reconstructed, under which the unknown time-varying parameters and sensor sensitivity are transformed into the estimation problem of unknown parameters. Second, based on a barrier function, a novel constraint algorithm is established to make the output enter into asymmetric time-varying constraint boundaries, which is independent of the initial value of the output. To avoid continuous sampling of the controller, an event-triggered mechanism is proposed without the Zeno phenomenon. By means of the Lyapunov stability theory, it is strictly proved that the output enters into the pregiven asymmetric constraint boundaries, and never exceeds. Finally, the validity of our proposed control algorithm is illustrated by a numerical simulation.
Is biologic therapy effective for antibiotic-refractory pouchitis?

Abstract Main text introduction The use of biologic therapy for antibiotic-refractory pouchitis is controversial, due to few studies on the subject and lack of convincing results. Objectives To study the efficacy of biologic therapy for refractory pouchitis. Materials and methods In this retrospective study, patient records at the Medical and Surgical departments in our hospital during an eleven-year period were scrutinized. 25 patients treated with biologics for refractory pouchitis were identified. Results The majority of these patients (n = 19, 76%) had either good or partial effect of biologic therapy for refractory pouchitis. Six of these patients did not respond until the second or third-line treatment. All naïve patients (n = 14) had good or partial response regardless if the diagnosis was idiopathic or Crohn’s-like pouchitis. In comparison, only 45% (n = 5) of the patients with prior exposure to biologics (n = 11) had a positive response. Six of ten patients treated with second or third-line therapy had a good or partial response. All not naïve patients who had previously been treated with Infliximab (n = 9) had adverse reactions when the same drug was given for pouchitis. Conclusions This retrospective study suggests that biologic therapy may be effective for both idiopathic and Crohn’s-like refractory pouchitis. Naïve patients seem to respond more successfully than not naïve patients. In cases without response on first-line treatment should second-line treatment be considered. Due to the high risk of adverse reactions Infliximab should be avoided to not naïve patients.
Simultaneous Confidence Bands for Linear Regression with Covariates Constrained in Intervals

Abstract. The focus of this article is on simultaneous confidence bands over a rectangular covariate region for a linear regression model with k>1 covariates, for which only conservative or approximate confidence bands are available in the statistical literature stretching back to Working & Hotelling (J. Amer. Statist. Assoc.24, 1929; 73–85). Formulas of simultaneous confidence levels of the hyperbolic and constant width bands are provided. These involve only a k‐dimensional integral; it is unlikely that the simultaneous confidence levels can be expressed as an integral of less than k‐dimension. These formulas allow the construction for the first time of exact hyperbolic and constant width confidence bands for at least a small k(>1) by using numerical quadrature. Comparison between the hyperbolic and constant width bands is then addressed under both the average width and minimum volume confidence set criteria. It is observed that the constant width band can be drastically less efficient than the hyperbolic band when k>1. Finally it is pointed out how the methods given in this article can be applied to more general regression models such as fixed‐effect or random‐effect generalized linear regression models.
Player-labelling as a solution to overcome maturation selection biases in youth football

ABSTRACT The fact that potentially skilled, but biologically later-maturing athletes are less likely to be selected into talent development programmes (TDP) can represent a failure of Talent Identification (TID) in sports. To overcome maturation selection biases, maturation independent TID should be established to include less mature, but talented athletes in TDP more frequently. Using a randomised parallel-group design, this study aimed to evaluate the effect of labelling under-11 (U11) Swiss male youth football players (n = 24, age = 11.0 ± 0.3 years) via maturation-ordered shirt numbers during rank assessment by talent scouts (n = 83, scout experience = 4.8 ± 2.4 years). Following observation of video recorded selection tournaments, player-labelling “informed” scouts were significantly more likely to rank less mature players higher on their player potential, t(81) = 2.57, p = . 012, d = −0.6, 95% CI [−1.00, −0.13], than “uninformed” scouts. As altered rankings assisted less mature players, player-labelling may offer a practical and feasible strategy to improve TID by removing possible maturation selection biases. To address maturation selection biases and the potential positive impact of player-labelling more broadly, further research on both male and female athletes in various age categories and sports contexts is recommended.
Hope and mental health problems among orphans and vulnerable children in South Africa

ABSTRACT There are over three million orphaned and vulnerable children (OVC) currently living in South Africa. OVC are at high risk for a number of negative outcomes, including poor mental health. Hope has been associated with well-being among youth, including youth in South Africa. However, the relationships between hope and mental health in high-adversity populations such as OVC has not been adequately described. The present study sought to address this research gap by evaluating the relationship between hope and mental health, controlling for gender, age, and orphan status, among OVC. This study includes 8- to 12-year-old OVC (N = 61) in Manguang, Free State, South Africa. Hope was assessed using the Children’s Hope Scale (CHS) and mental health outcomes were assessed using the Strengths and Difficulties Questionnaire (SDQ). Hope was significantly, inversely associated with mental health outcomes after controlling for other variables in linear regression analysis. In contrast to previous research, this study found that increased hope scores were associated with adverse mental health outcomes among OVC in South Africa. Hope may be contextualized differently in this population due to resource scarcity and high rates of adversity including HIV-AIDS related stigma and poverty.
EFFECT OF SEQUENCE AND INTERVAL OF FEEDING CONCENTRATE SUPPLEMENT AND ROUGHAGE ON PERFORMANCE OF YANKASA WEANER RAMS

A THESIS SUBMITTED TO THE POSTGRADUATE SCHOOL, AHMADU BELLO UNIVERSITY, ZARIA, NIGERIA, IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN ANIMAL SCIENCE DEPARTMENT OF ANIMAL SCIENCE, FACULTY OF AGRICULTURE, AHMADU BELLO UNIVERSITY, ZARIA, NIGERIA.
Neutrophil-to-lymphocyte ratio predicts coronary artery lesion severity and long-term cardiovascular mortality in patients with unstable angina pectoris

Abstract Objectives Neutrophil-to-lymphocyte ratio (NLR), one of the composite biomarker of systemic inflammatory status, was proved promising in predicting clinical outcomes of acute coronary syndrome (ACS). However, there were no evidences that NLR was directly relative to the clinical outcomes of unstable angina pectoris (UAP). Therefore, this study was aimed to detect whether NLR could predict the coronary artery lesion severity (indicated as SYNTAX score) and clinical outcomes (especially long-term cardiovascular mortality) in patients with. Methods In the single-centre retrospective study, 4110 patients with UAP were enrolled and divided into two groups according to their primary NLR values and followed up at a median time duration of 36 months. The differences of SYNTAX score and cardiovascular mortality between groups were analysed, and the predictive value of NLR was determined. Results NLR was positively and linearly correlated with SYNTAX score (r = 0.270). Diabetes (p = 0.049), lymphocyte (p = 0.004), NLR (p = 0.002) and SYNTAX score (p < 0.001) were independent predictors of long-term cardiovascular mortality in patients with UAP. Kaplan–Meier analysis revealed higher occurrence of cardiovascular mortality when NLR > 2.38 (p = 0.015). Receiver operating characteristic (ROC) analysis showed that NLR = 2.76 is an effective cut point for predicting cardiovascular mortality (69.2% sensitivity, 64.8% specificity). Conclusions NLR value was positively related to the severity of coronary artery lesion and proved to be an independent predictor of cardiovascular mortality in patients with UAP. This study would contribute to therapy and prognosis optimisation of UAP.
Event-Triggered Impulsive Quasisynchronization of Coupled Dynamical Networks With Proportional Delay

The quasisynchronization of nonidentically coupled dynamical networks (NCDNs) with proportional delay is achieved by the event-triggered mechanism (ETM). Heterogeneity and proportional delay greatly increase the difficulty on synchronization of NCDNs. As an unbounded delay in the coupling term, proportional delay is dealt with by the comparison principle, constructing parameter equations, and contradiction method. Moreover, different impulsive effects based on ETM are taken into account to reduce the burden of communication, and the quasisynchronization criteria for NCDNs are derived by the impulsive comparison principle and extended variable parameter formula. The synchronization errors and the exponential convergence rates under different impulsive effects are obtained. It is proven that the proposed ETM can avoid Zeno behavior. Finally, examples show the effectiveness of the proposed control scheme.