Miracle-dz/UniFAR-FTUs huggingface dataset:
Equivalence and limitations of error suppression techniques for adiabatic quantum computing.

While adiabatic quantum computation (AQC) possesses some intrinsic robustness to noise, it is expected that a form of error control will be necessary for large scale computations. Error control ideas developed for circuit-model quantum computation do not transfer easily to the AQC model and to date there have been two main proposals to suppress errors during an AQC implementation: energy gap protection and dynamical decoupling. Here we show that these two methods are essentially equivalent and can be analyzed within the same formalism. We analyze the effectiveness of such error suppression techniques and identify critical constraints on the performance of error suppression in AQC, suggesting that error suppression by itself is insufficient for fault-tolerant, large-scale AQC and that a form of error correction is needed.
The Psychological Impact of Aesthetic Surgery: A Mini-Review

Abstract The purpose of this summary is to outline the available research on the psychological factors associated with aesthetic surgery. Aesthetic procedures such as abdominoplasty, breast augmentation, face lift, and rhinoplasty are shown to have unique preoperative and postoperative psychological factors. Depression and anxiety may occur after aesthetic procedures with an increased incidence in patients with certain depression prone personality traits. The pre-existing psychology of patients is also an important contributing factor to consider when evaluating surgical candidates. Pre-existing mood disorders such as depression and anxiety are shown with higher incidence in individuals pursuing aesthetic procedures and can predispose such individuals to worsening mood symptoms postoperatively. This article aims to equip surgeons with a better understanding of the common psychological factors seen in the field of aesthetic surgery, so patients can be better supported throughout all parts of the surgical process. Level of Evidence: Therapeutic 5
The Release of Pollutants through the Bleeding of Cemented Phosphogypsum Backfill: Link to Protocols for Slurry Preparation

The present study investigated the effects of protocols for slurry preparation on the release of pollutants into bleeding water from cemented phosphogypsum (PG) backfill. Backfill slurry was prepared using four different protocols in which different parameters varied, including binder/PG ratio, solid concentration, binder type and mixing procedure. The concentrations of phosphate, fluoride and sulfate and the pH values of the obtained bleeding water were measured. The results demonstrated that the slurry preparation protocols affected the quantities of pollutants through the concentrations of pollutants in bleeding water and the bleeding rate. On the one hand, the binder/PG ratio was the key factor influencing the concentrations of all pollutants in bleeding water. Comparatively speaking, the binder type and mixing procedure had an obvious influence on the fluoride concentration but had little influence on the phosphate and sulfate concentrations in the bleeding water. On the other hand, the protocols for slurry preparation affected the bleeding rate by determining the water retention and water content of the backfill slurry. The most effective protocol for slurry preparation for cemented PG backfill could reduce the bleeding rate and enhance the immobilization of pollutants, minimizing the phosphate concentration in bleeding water to below 0.2 mg/L. However, it appeared that the fluoride concentration was still tens of milligrams per liter (over the limit of 10 ten milligrams per liter), to which attention should be paid.
Research and Analysis on the Cultivation of Intelligent Transportation Technology Professionals under the Background of Integration of Production and Education

In order to improve the training effect of transportation technology professionals, this paper combines the intelligent digital signal processing method to process the data of the integration of production and education, and explores the training process of transportation technology professionals. In the process of data processing of industry-education fusion, this paper demodulates the nuclear magnetic resonance signal obtained after A/D conversion from the carrier frequency signal and places it at zero frequency. At the same time, this paper realizes the separation of the real part and the imaginary part of the nuclear magnetic resonance signal and constructs the digital sine table and digital cosine table of the carrier reference frequency. In addition, the data output by the ADC is subjected to quadrature detection to become two data signals, which are the in-phase component and the quadrature component. Finally, this paper constructs an intelligent analysis model. The simulation results show that the talent training method of intelligent transportation technology based on the integration of production and education has good effects, which can effectively improve the training effect of transportation technology professionals.
Edge Computing and Microservices Middleware for Home Energy Management Systems

A middleware software can be seem as an abstraction layer between hardware and user applications, that facilitates the development and deployment of services in various scenarios, such as those found in Home Energy Management Systems (HEMS). There are several middleware proposals for HEMS, with most of them taking the cloud computing approach. This approach is unconcerned about computing resources but raises a dependency on external connections. This paper presents a middleware for energy management systems, based on the concept of edge computing for smart homes. The paper presents a reference model for the proposed architecture, considering specific requirements for this type of application. The proposed architecture employs the concept of microservices for data access and system configuration. The proposed middleware is designed to work with embedded systems under computational constraints, such as processing capability and storage, to reduce costs and allow its application closer to the user. The middleware is open and customizable to meet the developer’s needs. The proposed solution was implemented and tested in a university laboratory, as well as at the Eldorado Research Institute to confirm the effectiveness of the middleware. The proposal stands out from others found in the literature as it can be implemented using low cost hardware. In addition to using microservices concepts, the proposed middleware is a valuable option for applications that need an edge computing approach. A performance analysis was carried out, using low cost hardware with limited resources. The results show that the proposal can handle a significant number of devices, offering low latency and low error rate, and consuming few processing resources and memory.
A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems

This paper proposes a novel maximum power point tracking (MPPT) method inspired by the horse racing game for standalone photovoltaic (PV) power systems, such that the highest PV power conversion efficiency is obtained. From the horse racing game rules, we develop the horse racing algorithm (HRA) with the qualifying stage and final ranking stage. The MPP can be searched even if there exist multiple local MPPs for the PV power system. Moreover, from the proposed horse racing algorithm, the calculation is reduced, so that the transient searching points are less than traditional methods, i.e., the transient oscillation is less during the MPPT control. Therefore, the HRA based MPPT method avoids local maximum power traps and achieves the MPP quickly even if considering partial shading influence and varying environment for PV panels. Evidence of the accuracy and effectiveness of the proposed HRA method is exhibited by simulation results. These results are also compared with typical particle swarm optimization (PSO) and grey wolf optimization (GWO) methods and shown better convergence time as well as transient oscillation. Within the range from 0.34 to 0.58 s, the proposed method has effectively tracked the global maximum power point, which is from 0.42 to 0.48 s faster than the conventional PSO technique and from 0.36 to 0.74 s faster than the GWO method. Finally, the obtained findings proved the effectiveness and superiority of the proposed HRA technique through experimental results. The fast response in terms of good transient oscillation and global power tracking time of the proposed method are from 0.40 to 1.0 s, while the PSO and GWO methods are from 1.56 to 1.6 s and from 1.9 to 2.2 s, respectively.
UB CCD PHOTOMETRY OF THE OLD, METAL-RICH, OPEN CLUSTERS NGC 6791, NGC 6819, AND NGC 7142

We report on a UV-oriented imaging survey in the fields of the old, metal-rich open clusters NGC 6791, NGC 6819, and NGC 7142. With their super-solar metallicity and ages ≳ 3–8 Gyr, these three clusters represent both very near and ideal stellar aggregates to match the distinctive properties of the evolved stellar populations, as in elliptical galaxies and bulges of spirals. Following a first discussion of NGC 6791 observations in an accompanying paper, here we complete our analysis, also presenting for NGC 6819 and NGC 7142 the first-ever U CCD photometry. The color–magnitude diagram of the three clusters is analyzed in detail, with special emphasis on the hot stellar component. We report, in this regard, one new extreme horizontal-branch star candidate in NGC 6791. For NGC 6819 and 7142, the stellar luminosity function clearly points to a looser radial distribution of faint lower main sequence stars, either as a consequence of cluster dynamical interaction with the Galaxy or as an effect of an increasing fraction of binary stars toward the cluster core, as also observed in NGC 6791. Compared to a reference theoretical model for the Galaxy disk, the analysis of the stellar field along the line of sight of each cluster indicates that a more centrally concentrated thick disk, on a scale length shorter than ∼2.8 kpc, might better reconcile the lower observed fraction of bright field stars and their white-dwarf progeny.
Lensing degeneracies and mass substructure

The inversion of gravitational lens systems is hindered by the fact that multiple mass distributions are often equally compatible with the observed properties of the images. Besides using clear examples to illustrate the effect of the so-called monopole and mass-sheet degeneracies, this paper introduces the most general form of said mass-sheet degeneracy. While the well-known version of this degeneracy rescales a single source plane, this generalization allows any number of sources to be rescaled. Furthermore, it shows how it is possible to rescale each of those sources with a different scalefactor. Apart from illustrating that the mass-sheet degeneracy is not broken by the presence of multiple sources at different redshifts, it will become apparent that the newly constructed mass distribution necessarily alters the existing mass density precisely at the locations of the images in the lens system, and that this change in mass density is linked to the factors with which the sources were rescaled. Combined with the fact that the monopole degeneracy introduces a large amount of uncertainty about the density in between the images, this means that both degeneracies are in fact closely related to substructure in the mass distribution. An example of a simulated lensing situation based on an elliptical version of a Navarro–Frenk–White profile explicitly shows that such degeneracies are not easily broken by observational constraints, even when multiple sources are present. Instead, the fact that each lens inversion method makes certain assumptions, implicit or explicit, about the smoothness of the mass distribution means that in practice the degeneracies are broken in an artificial manner rather than by observed properties of the lens system.
Seasonal Variations of Fine Root Dynamics in Rubber-Flemingia macrophylla Intercropping System in Southwestern China

Intercropping cover crops with trees enhance land productivity and improves the soil’s physio-chemical properties while reducing the negative environmental impact. However, there is a lack of quantitative information on the relationships between fine root biomass and available soil nutrients, e.g., nitrogen (N), phosphorus (P), and potassium (K), especially in the rubber-Flemingia macrophylla intercropping system. Therefore, this study was initiated to explore the seasonal variation in fine root biomass and available soil nutrients at different stand ages (12, 15, and 24 years) and management systems, i.e., rubber monoculture (mono) and rubber-Flemingia macrophylla intercropping. In this study, we sampled 900 soil cores over five seasonal intervals, representing one year of biomass. The results showed that the total fine root biomass was greater in 12-year-old rubber monoculture; the same trend was observed in soil nutrients P and K. Furthermore, total fine root biomass had a significant positive correlation with available N (p < 0.001) in rubber monoculture and intercropping systems. Thus, it suggests that fine root growth and accumulation is a function of available soil nutrients. Our results indicate that fine root biomass and soil nutrients (P and K) may be determined by the functional characteristics of dominant tree species rather than collective mixed-species intercropping and are closely linked to forest stand type, topographic and edaphic factors. However, further investigations are needed to understand interspecific and complementary interactions between intercrop species under the rubber-Flemingia macrophylla intercropping system.
UPPER LIMITS FROM FIVE YEARS OF BLAZAR OBSERVATIONS WITH THE VERITAS CHERENKOV TELESCOPES

Between the beginning of its full-scale scientific operations in 2007 and 2012, the VERITAS Cherenkov telescope array observed more than 130 blazars; of these, 26 were detected as very-high-energy (VHE; E > 100 GeV) γ-ray sources. In this work, we present the analysis results of a sample of 114 undetected objects. The observations constitute a total live-time of ∼570 hr. The sample includes several unidentified Fermi-Large Area Telescope (LAT) sources (located at high Galactic latitude) as well as all the sources from the second Fermi-LAT catalog that are contained within the field of view of the VERITAS observations. We have also performed optical spectroscopy measurements in order to estimate the redshift of some of these blazars that do not have spectroscopic distance estimates. We present new optical spectra from the Kast instrument on the Shane telescope at the Lick observatory for 18 blazars included in this work, which allowed for the successful measurement or constraint on the redshift of four of them. For each of the blazars included in our sample, we provide the flux upper limit in the VERITAS energy band. We also study the properties of the significance distributions and we present the result of a stacked analysis of the data set, which shows a 4σ excess.
Prevalence and Determinants of Non-psychotic Mental Illness among Primary Health Care Centers Attendees in Doha, Qatar

Background: Mental illness places a severe physical and social burden on an individual and the whole Family. Undetected mental illness is a serious health problem at PHC level, often leading to waste of resources. Objective: This study aimed to measure the prevalence of non-psychotic-mental illness among PHC centers attendees in Qatar, to identify the determinants of non-psychotic mental illness, and to assess factors affecting patients’ disclosure of their psychological problems. Results: This study showed a prevalence of 26.7% for non-psychotic mental illness among primary health care attendees in Qatar. A statistically significant relations were determined between gender, education, occupation
Compositional Network Embedding

Network embedding has proved extremely useful in a variety of network analysis tasks such as node classification, link prediction, and network visualization. Almost all the existing network embedding methods learn to map the node IDs to their corresponding node embeddings. This design principle, however, hinders the existing methods from being applied in real cases. Node ID is not generalizable and, thus, the existing methods have to pay great effort in cold-start problem. The heterogeneous network usually requires extra work to encode node types, as node type is not able to be identified by node ID. Node ID carries rare information, resulting in the criticism that the existing methods are not robust to noise. To address this issue, we introduce Compositional Network Embedding, a general inductive network representation learning framework that generates node embeddings by combining node features based on the principle of compositionally. Instead of directly optimizing an embedding lookup based on arbitrary node IDs, we learn a composition function that infers node embeddings by combining the corresponding node attribute embeddings through a graph-based loss. For evaluation, we conduct the experiments on link prediction under four different settings. The results verified the effectiveness and generalization ability of compositional network embeddings, especially on unseen nodes.
Method for Profile-Guided Optimization of Android Applications Using Random Forest

When choosing a smartphone, many users are guided by the performance of smartphones and the speed of applications. Because it is difficult to measure the application speed directly, the speed of the application startup is considered and used for comparison. Android runtime (ART) uses several technologies to speed up applications. The first approach is the just-in-time (JIT) compilation of frequently used methods at runtime. The second approach is to compile entire application code ahead of time (AOT). The performance profile is a way to strike a balance between JIT and AOT. The runtime optimization features were introduced in Android Nougat in form of profile-guided optimization (PGO). By aggregating data from a multiplicity of users and devices in Play Store, ART profiling significantly speeds up this process and makes its outcome available to all users alike. We propose a machine learning based method called SPMLGen for generating application profiles used in the optimization. We avoid time delays caused by the need to collect information in advance to perform optimization and ensure user privacy. With profiles generated by SPMLGen, we obtain approximately the same application launch time as with profiles from Play Store. Measurements were taken on Samsung Galaxy S22 and A52 devices with Android 12 firmware and several dozen Samsung applications.
Light wave driven electron dynamics in clusters

The dynamics of solid‐density nanoplasmas driven by intense lasers takes place in the strongly‐coupled plasma regime, where collisions play an important role. The microscopic particle‐in‐cell method has enabled the complete classical electromagnetic description of these processes. The theoretical foundation of the approach and its relation to existing methods are reviewed. Selected applications to laser cluster processes are presented that have been inaccessible to numerical simulation so far.
PROBING PRIMORDIAL NON-GAUSSIANITY WITH WEAK-LENSING MINKOWSKI FUNCTIONALS

We study the cosmological information contained in the Minkowski functionals (MFs) of weak gravitational lensing convergence maps. We show that the MFs provide strong constraints on the local-type primordial non-Gaussianity parameter fNL. We run a set of cosmological N-body simulations and perform ray-tracing simulations of weak lensing to generate 100 independent convergence maps of a 25 deg2 field of view for fNL = −100, 0 and 100. We perform a Fisher analysis to study the degeneracy among other cosmological parameters such as the dark energy equation of state parameter w and the fluctuation amplitude σ8. We use fully nonlinear covariance matrices evaluated from 1000 ray-tracing simulations. For upcoming wide-field observations such as those from the Subaru Hyper Suprime-Cam survey with a proposed survey area of 1500 deg2, the primordial non-Gaussianity can be constrained with a level of fNL ∼ 80 and w ∼ 0.036 by weak-lensing MFs. If simply scaled by the effective survey area, a 20,000 deg2 lensing survey using the Large Synoptic Survey Telescope will yield constraints of fNL ∼ 25 and w ∼ 0.013. We show that these constraints can be further improved by a tomographic method using source galaxies in multiple redshift bins.
Probability and random processes (4th edition) by Geoffrey R. Grimmett and David R. Stirzaker, pp. 669, £40 (paper), ISBN 978-019884759, Oxford University Press (2020)

manipulate. The set of equivalence classes of integers mod is denoted, logically but rather messily, by . That said, the chapter has the expected ingredients, including public key cryptography, and contains many interesting and challenging exercises (for example showing in several steps that if is a number of at most 100 decimal digits then by the Euclidean algorithm takes at most 479 divisions). Chapter 8 on infinite sets is quite ambitions and covers the inclusion-exclusion formula and the uncountability of the power set of the positive integers, leading to the same for the real numbers, and the Cantor-Schröder-Bernstein theorem. m Z / ≡m
Proenkephalin as a novel prognostic marker in heart failure patients: a meta-analysis

Proenkephalin (PENK), a novel biomarker, sequentially activates delta-opioid receptors in heart tissue causing reduced myocardial contractility, blood pressure, and heart rate. PENK has several prognostic abilities for patients with myocardial infarction, stroke, and impaired renal function. However, its prognostic value in heart failure patients is still inconclusive. To evaluate the association between plasma PENK level at the time of admission and all-cause mortality in patients with heart failure. We collected studies from MEDLINE and EMBASE databases until January 2022 to perform a meta-analysis. High level of PENK is defined as plasma PENK level more than 99th percentile of the general population. Separated pooling hazard ratio (HR) for all-cause mortality among high and normal levels of PENK was performed using a random-effect model, generic inverse variance method of DerSimonian and Laird. Sources of heterogeneity including clinical and methodological variations were explored using a meta regression and subsequent subgroup analysis. A total of six observational studies composed of 6,929 patients with either acute heart failure or chronic heart failure were included in this analysis. There are five studies involving heart failure patients with both reduced ejection fraction and preserved ejection fraction and another one concerning those with only preserved ejection fraction. High level of PENK was found in 70.9% of patients. The high level of PENK compared with normal levels was associated with a higher prevalence of all-cause mortality with pooled HRs of 1.72 (95% CI, 1.62–1.84; I2=84%). The analyzed data were shown in the Figure 1. This study demonstrates the association between high levels of PENK and all-cause mortality in heart failure patients. These findings suggest that the opioid system might be involved in deteriorating cardiovascular function in heart failure. Type of funding sources: None.