Miracle-dz/UniFAR-FTUs huggingface dataset:
The TeV-emitting radio galaxy 3C 264

Context.In March 2018, the detection by VERITAS of very-high-energy emission (VHE > 100 GeV) from 3C 264 was reported. This is the sixth, and second most distant, radio galaxy ever detected in the TeV regime.Aims. In this article we present a radio and X-ray analysis of the jet in 3C 264. We determine the main physical parameters of the parsec-scale flow and explore the implications of the inferred kinematic structure for radiative models of thisγ-ray emitting jet.Methods. The radio data set is comprised of VLBI observations at 15 GHz from the MOJAVE program, and covers a time period of about two years. Through a segmented wavelet decomposition method (WISE code), we estimated the apparent displacement of individual plasma features; we then performed a pixel-based analysis of the stacked image to determine the jet shape. The X-ray data set includes all available observations from theChandra, XMM, andSwiftsatellites, and is used, together with archival data in the other bands, to build the spectral energy distribution (SED). Results.Proper motion is mostly detected along the edges of the flow, which appears strongly limb brightened. The apparent speeds increase as a function of distance from the core up to a maximum of ∼11.5 c. This constrains the jet viewing angle to assume relatively small values (θ ≲ 10°). In the acceleration region, extending up to a de-projected distance of ∼4.8 × 104Schwarzschild radii (∼11 pc), the jet is collimating (r ∝ z0.40 ± 0.04), as predicted for a magnetically-driven plasma flow. By assuming that the core region is indeed magnetically dominated (UB/Ue > 1), the SED and the jet power can be well reproduced in the framework of leptonic models, provided that the high-energy component is associated to a second emitting region. The possibility that this region is located at the end of the acceleration zone, either in the jet layer or in the spine, is explored in the modeling.
X2CT-GAN: Reconstructing CT From Biplanar X-Rays With Generative Adversarial Networks

Computed tomography (CT) can provide a 3D view of the patient's internal organs, facilitating disease diagnosis, but it incurs more radiation dose to a patient and a CT scanner is much more cost prohibitive than an X-ray machine too. Traditional CT reconstruction methods require hundreds of X-ray projections through a full rotational scan of the body, which cannot be performed on a typical X-ray machine. In this work, we propose to reconstruct CT from two orthogonal X-rays using the generative adversarial network (GAN) framework. A specially designed generator network is exploited to increase data dimension from 2D (X-rays) to 3D (CT), which is not addressed in previous research of GAN. A novel feature fusion method is proposed to combine information from two X-rays. The mean squared error (MSE) loss and adversarial loss are combined to train the generator, resulting in a high-quality CT volume both visually and quantitatively. Extensive experiments on a publicly available chest CT dataset demonstrate the effectiveness of the proposed method. It could be a nice enhancement of a low-cost X-ray machine to provide physicians a CT-like 3D volume in several niche applications.
Design and Experimental Validation of Tube-based MPC for Timed-constrained Robot Planning

This paper deals with the design and experimental validation of a state-of-the art tube-based Model Predictive Control (MPC) for achieving time-constrained tasks. Given the uncertain nonlinear dynamics of the robot as well as a high-level task written in Metric Interval Temporal Logic (MITL), the goal is to design a feedback control law that guarantees the satisfaction of the task. The workspace is divided into Regions of Interest (RoI) and contains also unsafe regions (obstacles) that the robot should not visit. The feedback control law consists of two terms: a control input which is the outcome of a Finite Horizon Optimal Control (FHOCP); and a state feedback law that guarantees that the nominal trajectories are bounded within a tube centered along the nominal trajectories. The aforementioned control law guarantees that the robot is safely navigated through the RoI within certain time bounds. The proposed framework can handle the rich expressiveness of MITL and is experimentally tested with a Nexus mobile robot in our lab facilities. The experimental results show that the proposed framework is promising for solving real-life robotic as well as industrial problems.
Covers, Orientations and Factors

Given a graph $G$ with only even degrees, let $\varepsilon(G)$ denote the number of Eulerian orientations, and let $h(G)$ denote the number of half graphs, that is, subgraphs $F$ such that $d_F(v)=d_G(v)/2$ for each vertex $v$. Recently, Borbényi and Csikvári proved that $\varepsilon(G)\geq h(G)$ holds true for all Eulerian graphs, with equality if and only if $G$ is bipartite. In this paper we give a simple new proof of this fact, and we give identities and inequalities for the number of Eulerian orientations and half graphs of a $2$-cover of a graph $G$.
Efficiently generating geometric inhomogeneous and hyperbolic random graphs

Abstract Hyperbolic random graphs (HRGs) and geometric inhomogeneous random graphs (GIRGs) are two similar generative network models that were designed to resemble complex real-world networks. In particular, they have a power-law degree distribution with controllable exponent $\beta$ and high clustering that can be controlled via the temperature $T$ . We present the first implementation of an efficient GIRG generator running in expected linear time. Besides varying temperatures, it also supports underlying geometries of higher dimensions. It is capable of generating graphs with ten million edges in under a second on commodity hardware. The algorithm can be adapted to HRGs. Our resulting implementation is the fastest sequential HRG generator, despite the fact that we support non-zero temperatures. Though non-zero temperatures are crucial for many applications, most existing generators are restricted to $T = 0$ . We also support parallelization, although this is not the focus of this paper. Moreover, we note that our generators draw from the correct probability distribution, that is, they involve no approximation. Besides the generators themselves, we also provide an efficient algorithm to determine the non-trivial dependency between the average degree of the resulting graph and the input parameters of the GIRG model. This makes it possible to specify the desired expected average degree as input. Moreover, we investigate the differences between HRGs and GIRGs, shedding new light on the nature of the relation between the two models. Although HRGs represent, in a certain sense, a special case of the GIRG model, we find that a straightforward inclusion does not hold in practice. However, the difference is negligible for most use cases.
A robust feedback linearization approach for tracking control of flexible-link manipulators using an EKF disturbance estimator

This paper proposes a composite control approach based on the robust feedback linearization and Extended Kalman Filter (EKF) to improve the tracking performance for the flexible link manipulators in the presence of torque disturbances. In this regard, first an EKF is employed to estimate the disturbances, utilizing the uncertain nonlinear model of flexible link system in addition to noisy measurement data. The estimate is then used in the control strategy in order to eliminate the destructive effects of the disturbances. It can also be used as interaction data in some applications such as telerobotics. In the next step, a Lyapunov Redesign Feedback Linearization (LRFL) approach is utilized in order to alleviate the effect of model uncertainties, disturbance estimation error as well as nonlinearities presented in the dynamics of the redefined output. This output is selected as a point close to the tip to avoid the difficulties associated with the non-minimum phase behavior of the tip position. Simulation results performed on a single-link flexible manipulator are presented to illustrate the significant capability of this technique in tracking performance as well as disturbance estimation ability in uncertain and noisy situations.
Quality of life index: development and psychometric properties

The purpose of the study on which this article is based was to assess the validity and reliability of an instrument designed to measure quality of life. Sixty-four items applicable to both healthy subjects and dialysis patients were tested with graduate students (n = 88); six items relative to dialysis were added, and the instrument was administered to dialysis patients (n = 37). Items were based on literature review, which supported content validity. Correlations between the instrument and an overall satisfaction with life question of 0.75 (graduate students) and 0.65 (dialysis patients) supported criterion-related validity. Support for reliability was provided by test-retest correlations of 0.87 (graduate students) and 0.81 (dialysis patients) and Cronbach's alphas of 0.93 (graduate students) and 0.90 (dialysis patients).
CSF biomarkers in relationship to cognitive profiles in Alzheimer disease

Objective: To investigate the relationship between CSF biomarkers and cognitive profiles in Alzheimer disease (AD). Methods: We included 177 patients with AD. Digit Span, Visual Association Test (VAT), VAT object naming, Trail Making Test (TMT), and category fluency were used to assess cognitive functions. Disease severity was assessed using Mini-Mental State Examination; functional impairment was rated by Clinical Dementia Rating. In CSF, levels of amyloid-beta 1-42 (Aβ1-42), tau, and tau phosphorylated at threonine 181 (p-tau) were measured. K-means cluster analysis was performed with the three biomarkers to obtain three clusters. Multivariate analysis of variance for repeated measures was performed with CSF cluster as between-subjects factor, neuropsychological z scores as within-subjects variable, and age, sex, and education as covariates. Results: Cluster 1 consisted of 88 patients (49%) with relatively high levels of Aβ1-42 and low levels of tau and p-tau. Cluster 2 contained 72 patients (41%) with relatively low levels of Aβ1-42 and high levels of tau and p-tau. Cluster 3 was made up of 17 patients (10%) with low levels of Aβ1-42 and very high levels of tau and p-tau. No differences between clusters on age, sex, education, APOE genotype, disease duration, functional impairment, or disease severity were found. Patients in cluster 3 performed worse on VAT, TMT-A and -B, and fluency. Conclusions: Clusters of CSF biomarker levels are related to cognitive profiles in Alzheimer disease. A subgroup of patients with extremely high CSF levels of tau and tau phosphorylated at threonine 181 shows a distinct cognitive profile with more severe impairment of memory, mental speed, and executive functions, which cannot be explained by disease severity.
Recent Advances in Diversified Recommendation

With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not. In recent years, diversity has gained tremendous attention in recommender systems research, which has been recognized to be an important factor for improving user satisfaction. On the one hand, diversified recommendation helps increase the chance of answering ephemeral user needs. On the other hand, diversifying recommendation results can help the business improve product visibility and explore potential user interests. In this paper, we are going to review the recent advances in diversified recommendation. Specifically, we first review the various definitions of diversity and generate a taxonomy to shed light on how diversity have been modeled or measured in recommender systems. After that, we summarize the major optimization approaches to diversified recommendation from a taxonomic view. Last but not the least, we project into the future and point out trending research directions on this topic.
First Results from ABRACADABRA-10cm: A Search for Low-Mass Axion Dark Matter

The presence of dark matter provides some of the most tangible evidence for the existence of physics beyond the Standard Model. One compelling dark matter candidate is the axion, a light boson that was originally postulated as a solution to another outstanding issue, the strong CP problem in QCD. ABRACADABRA is an experimental program to search for sub-$\mu$eV axion and axion-like dark matter. It searches for axion-induced modifications to Maxwell's equations with a toroidal magnet and SQUID magnetometer. This contribution will present the first results from the prototype detector, ABRACADABRA-10cm.
Predicting breakdowns in cloud services (with SPIKE)

Maintaining web-services is a mission-critical task where any down- time means loss of revenue and reputation (of being a reliable service provider). In the current competitive web services market, such a loss of reputation causes extensive loss of future revenue. To address this issue, we developed SPIKE, a data mining tool which can predict upcoming service breakdowns, half an hour into the future. Such predictions let an organization alert and assemble the tiger team to address the problem (e.g. by reconguring cloud hardware in order to reduce the likelihood of that breakdown). SPIKE utilizes (a) regression tree learning (with CART); (b) synthetic minority over-sampling (to handle how rare spikes are in our data); (c) hyperparameter optimization (to learn best settings for our local data) and (d) a technique we called “topology sampling” where training vectors are built from extensive details of an individual node plus summary details on all their neighbors. In the experiments reported here, SPIKE predicted service spikes 30 minutes into future with recalls and precision of 75% and above. Also, SPIKE performed relatively better than other widely-used learning methods (neural nets, random forests, logistic regression).
Weak endpoint bounds for matrix weights

We prove quantitative matrix weighted endpoint estimates for the matrix weighted Hardy-Littlewood maximal operator, Calder\'on-Zygmund operators, and commutators of CZOs with scalar BMO functions, when the matrix weight is in the class $A_1$ introduced by M. ~Frazier and S. ~Roudenko.
Marine biogenic source of atmospheric organic nitrogen in the subtropical North Atlantic

Significance Global models indicate that the human-derived nitrogen emissions that reach the ocean through atmospheric transport and deposition directly impact biology and the oceanic carbon dioxide (CO2) sink. Here, we find that the organic nitrogen in marine aerosols derives predominantly from biological production in the surface ocean rather than from pollution on land. Our previous work has shown significant anthropogenic influence on North Atlantic nitrate deposition, whereas ammonium cycles dynamically between the upper ocean and lower atmosphere. Collectively, these findings indicate that the ocean is not a passive recipient of anthropogenic nitrogen deposition, as it has previously been considered. This implies that the contribution of atmospheric nitrogen deposition to ocean fertility, oceanic CO2 removal, and nitrous oxide emissions has been overestimated. Global models estimate that the anthropogenic component of atmospheric nitrogen (N) deposition to the ocean accounts for up to a third of the ocean’s external N supply and 10% of anthropogenic CO2 uptake. However, there are few observational constraints from the marine atmospheric environment to validate these findings. Due to the paucity of atmospheric organic N data, the largest uncertainties related to atmospheric N deposition are the sources and cycling of organic N, which is 20–80% of total N deposition. We studied the concentration and chemical composition of rainwater and aerosol organic N collected on the island of Bermuda in the western North Atlantic Ocean over 18 mo. Here, we show that the water-soluble organic N concentration ([WSON]) in marine aerosol is strongly correlated with surface ocean primary productivity and wind speed, suggesting a marine biogenic source for aerosol WSON. The chemical composition of high-[WSON] aerosols also indicates a primary marine source. We find that the WSON in marine rain is compositionally different from that in concurrently collected aerosols, suggesting that in-cloud scavenging (as opposed to below-cloud “washout”) is the main contributor to rain WSON. We conclude that anthropogenic activity is not a significant source of organic N to the marine atmosphere over the North Atlantic, despite downwind transport from large pollution sources in North America. This, in conjunction with previous work on ammonium and nitrate, leads to the conclusion that only 27% of total N deposition to the global ocean is anthropogenic, in contrast to the 80% estimated previously.
Classification of Perceived Human Stress using Physiological Signals

In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals. These include electroencephalography (EEG), galvanic skin response (GSR), and photoplethysmography (PPG). We conducted experiments consisting of steps including data acquisition, feature extraction, and perceived human stress classification. The physiological data of 28 participants are acquired in an open eye condition for a duration of three minutes. Four different features are extracted in time domain from EEG, GSR and PPG signals and classification is performed using multiple classifiers including support vector machine, the Naive Bayes, and multi-layer perceptron (MLP). The best classification accuracy of 75% is achieved by using MLP classifier. Our experimental results have shown that our proposed scheme outperforms existing perceived stress classification methods, where no stress inducers are used.
Effects Without Monads: Non-determinism - Back to the Meta Language

We reflect on programming with complicated effects, recalling an undeservingly forgotten alternative to monadic programming and checking to see how well it can actually work in modern functional languages. We adopt and argue the position of factoring an effectful program into a first-order effectful DSL with a rich, higher-order 'macro' system. Not all programs can be thus factored. Although the approach is not general-purpose, it does admit interesting programs. The effectful DSL is likewise rather problem-specific and lacks general-purpose monadic composition, or even functions. On the upside, it expresses the problem elegantly, is simple to implement and reason about, and lends itself to non-standard interpretations such as code generation (compilation) and abstract interpretation. A specialized DSL is liable to be frequently extended; the experience with the tagless-final style of DSL embedding shown that the DSL evolution can be made painless, with the maximum code reuse. We illustrate the argument on a simple but representative example of a rather complicated effect -- non-determinism, including committed choice. Unexpectedly, it turns out we can write interesting non-deterministic programs in an ML-like language just as naturally and elegantly as in the functional-logic language Curry -- and not only run them but also statically analyze, optimize and compile. The richness of the Meta Language does, in reality, compensate for the simplicity of the effectful DSL. The key idea goes back to the origins of ML as the Meta Language for the Edinburgh LCF theorem prover. Instead of using ML to build theorems, we now build (DSL) programs.
Eruption chronology of primary teeth in Nigerian children.

UNLABELLED The eruption chronology of the primary dentition has been studied in some populations, however; only few studies from Nigeria and other African countries have been reported. OBJECTIVE To determine the appropriate reference standard for eruption of primary teeth in Nigerian children. SUBJECTS AND METHODS A cross sectional study consisting of 1,013 clinically healthy babies, infants and preschool children between the ages of 4 to 36 months from the community health centers immunization clinics in Ife Central and Ife East Local Government Areas. RESULTS Boys erupted primary teeth earlier than girls in both arches except the first molars. However girls had a shorter duration of eruption (from the first tooth to erupt to the last tooth to erupt) when compared to boys. In addition, boys had a systematic tendency for earlier eruption on the left side. CONCLUSION Within the limitations of this study, a baseline data for eruption of primary teeth among Nigerian children has been established. Nigerian children experienced an earlier eruption of primary teeth when compared to their Arabian and American counterparts and a later eruption when compared to children from Iceland.
Experimental investigation of the nonlocal advantage of quantum coherence

Nonlocal advantage of quantum coherence (NAQC) based on coherence complementarity relations is generally viewed as a stronger nonclassical correlation than Bell nonlocality. An arbitrary two-qubit state with NAQC must be an entangled state, which demonstrates that the criterion of NAQC can also be regarded as an entanglement witness. In this paper, we experimentally investigate the NAQC for Bell-diagonal states with high fidelity in an optics-based platform. We perform local measurements on a subsystem in three mutually unbiased bases and reconstruct the density matrices of the measured states by quantum state tomography process. By analyzing characteristic of the $l_1$ norm, relative entropy and skew information of coherence with parameters of quantum states, NAQC for the quantum states is accurately captured, and it shows that our experimental results are well compatible with the theoretical predictions. It is worth mentioning that quantum states with NAQC would have higher entanglement, and thus NAQC could be expected to be a kind of useful physical resource for quantum information processing.
Trapping laser excitation during collisions limits the lifetime of ultracold molecules

Arthur Christianen, Martin W. Zwierlein, Gerrit C. Groenenboom, and Tijs Karman ∗ Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands MIT-Harvard Center for Ultracold Atoms, Research Laboratory of Electronics, and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA ITAMP, Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, 02138, USA
InfoRest: Restricting Privacy Leakage to Online Social Network App

In recent years, Online Social Networks (OSNs) have become immensely popular as social interaction services among worldwide Internet users. OSNs facilitate Third-party applications (TPAs) which provide many additional functionalities to users. While providing the extended services TPAs access the users data which would raise serious concerns to user privacy. This is due to the lack of user data protection mechanisms by OSN and none of the present OSN platforms offers satisfactory protection mechanisms to users private data. In this paper, we propose an access control framework called InfoRest to restrict user data to TPA in OSN, considering users privacy preferences and attribute generalization. Further, we propose a relation based access control (ReBAC) policy model and use predicate calculus to represent access conditions. The usability and correctness of the proposed policy model are demonstrated with the help of a logical model developed using answer set programming.