Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of First Metatarsal Phalangeal Joint Fusion for Hallux Rigidus With Patient-Reported Pain and Mental Health Outcomes in Patients Taking Psychotropic Medications

Background: Limited literature examines the relationship between surgical outcomes in chronic foot and ankle conditions and concurrent psychiatric care. The present study aimed to investigate patient-reported and surgical outcomes of patients treated for a psychiatric disorder undergoing first metatarsophalangeal (MTP) fusion for hallux rigidus. We hypothesized that patients on psychotropic medications would have greater subjective pain preoperatively and less improvement in physical and mental functionality postoperatively when compared with nonmedicated patients. Methods: A single-center, retrospective review of prospectively collected data was conducted on 92 patients undergoing first MTP fusion with a preoperative diagnosis of hallux rigidus from 2015 to 2019. At their preoperative, 6-month postoperative, and 1-year postoperative visits, patients were administered visual analog pain scale (VAS) and 36-Item Short Form Health Survey (SF-36) functionality surveys. Patients were subsequently identified by chronic use of psychotropic medication preoperatively and grouped for analysis (MED, n = 42; NO MED, n = 50). Results: Postoperative mean VAS pain scores were lower for all studied patients at 6 months (VAS = 1.6 ± 2.3) and 1 year postoperatively (VAS = 1.1± 1.8) relative to the preoperative visit (VAS = 4.7 ± 2.8) (P ≤ .0001 and P ≤ .0001, respectively). No differences in mean VAS pain scores nor SF-36 physical component summary scores were detected at preoperative, 6-month, or 1-year visits between NO MED and MED groups. Mean SF-36 mental component summary scores for those in the MED group were lower at preoperative (NO MED = 83.8, MED = 71.8, P = .006) and 6-month postoperative (NO MED = 86.1, MED = 72.7, P = .037) visits than those in the NO MED group, a trend not observed at the 1-year postoperative mark (NO MED = 84.1, MED = 76.8, P = .228). There were no observed differences in operative time (P = .219), tourniquet time (P = .359), nor time to full weightbearing (P = .512) between MED and NO MED groups. Additionally, no differences in postoperative complication rates were observed between groups. Conclusion: In patients treated with psychotropically active medications with hallux rigidus, MTP Fusion appears to be a reasonable treatment choice with similar outcomes for patients requiring psychotropically active medications to the outcomes of those patients not requiring psychotropically active medications. Level of Evidence: Level III, retrospective comparative study.
Prediction of Electromagnetic Performance for IPMSM Based on Improved Analytical Model Considering Saturation Effects

Unlike surface-mounted permanent magnet synchronous motors (SPMSM), the rotor structure of interior permanent magnet synchronous motor (IPMSM) is irregular and relatively complex. This makes the analytical calculation for IPMSM quite complicated. Except for the use of some equivalent methods to make irregular permanent magnets (PMs) regular, existing subdomain models often cannot effectively and directly account for the complex rotor structure and cannot be easily applied to IPMSM. For this reason, an improved analytical model applicable to IPMSM is presented, studied, and developed in this article. First, a novel subdomain model division method is innovatively introduced. Complex rotor structure can be well-accounted for. This not only facilitates the expression of vector potential and satisfies the establishment of subdomain model, but also recovers the original rotor topology to the maximum extent and effectively avoids many uncertainties and unreliability caused by over-equivalence. Afterward, the magnetic equivalent circuit and equivalent surface current method are combined to fully consider the saturation effects of magnetic isolation bridges, rotor ribs, and cores. Model analysis accuracy is well-guaranteed. Further, the precise subdomain method is investigated to achieve fast prediction of key electromagnetic performance. Both finite-element analysis (FEA) and prototype experiment strongly highlight the validity of the improved analytical model. In addition, compared to FEA, the improved analytical model does not require tens of thousands of computation cells, which saves a lot of time and storage while ensuring the same prediction accuracy. This opens up unlimited possibilities for the design and optimization of IPMSM.
SOLAR WIND CHARGE EXCHANGE EMISSION FROM THE HELIUM FOCUSING CONE: MODEL TO DATA COMPARISON

A model for heliospheric solar wind charge exchange (SWCX) X-ray emission is applied to a series of XMM-Newton observations of the interplanetary focusing cone of interstellar helium. The X-ray data are from three coupled observations of the South Ecliptic Pole (SEP; to observe the cone) and the Hubble Deep Field-North (HDF-N, to monitor global variations of the SWCX emission due to variations in the solar wind (SW)) from the period 2003 November 24 to December 15. There is good qualitative agreement between the model predictions and the data, after the SEP data are corrected using the HDF-N data, with the maximum SWCX flux observed at an ecliptic longitude of ∼72°, consistent with the central longitude of the He cone. We observe a total excess of 2.1 ± 1.3 line unit (LU) in the O vii line and 2.0 ± 0.9 LU in the O viii line. However, the SWCX emission model, which was adjusted for SW conditions appropriate for late 2003, predicts an excess from the He cone of only 0.5 LU and 0.2 LU, respectively, in the O vii and O viii lines. We discuss the model to data comparison and provide possible explanations for the discrepancies. We also qualitatively re-examine our SWCX model predictions in the keV band with data from the ROSAT All-Sky Survey toward the North Ecliptic Pole and SEP, when the He cone was probably first detected in soft X-rays.
Estudo de Superfícies Seletivas de Frequência com o Uso deInteligência Computacional

The main objective of this work is to optimize the performance of frequency selective surfaces (FSS) composed of crossed dipole conducting patches. The optimization process is performed by determining proper values for the width of the crossed dipoles and for the FSS array periodicity, while the length of the crossed dipoles is kept constant. Particularly, the objective is to determine values that provide wide bandwidth using a search algorithm with representation in bioinspired real numbers. Typically FSS structures composed of patch elements are used for band rejection filtering applications. The FSS structures primarily act like filters depending on the type of element chosen. The region of the electromagnetic spectrum chosen for this study is the one that goes from 7 GHz to 12 GHz, which includes mostly the X-band. This frequency band was chosen to allow the use of two X-band horn antennas, in the FSS measurement setup. The design of the FSS using the developed genetic algorithm allowed increasing the structure bandwidth.
Robustness in the presence of mixed parametric uncertainty and unmodeled dynamics

Continuing the development of the structured singular value approach to robust control design, the authors investigate the problem of computing mu in the case of mixed real parametric and complex uncertainty. The problem is shown to be equivalent to a smooth constrained finite-dimensional optimization problem. In view of the fact that the functional to be maximized may have several local extrema, an upper bound on mu whose computation is numerically tractable is established; this leads to a sufficient condition of robust stability and performance. A historical perspective on the development of the mu theory is included. >
Large‐scale 3D fast Fourier transform computation on a GPU

We propose a novel graphics processing unit (GPU) algorithm that can handle a large‐scale 3D fast Fourier transform (i.e., 3D‐FFT) problem whose data size is larger than the GPU's memory. A 1D FFT‐based 3D‐FFT computational approach is used to solve the limited device memory issue. Moreover, to reduce the communication overhead between the CPU and GPU, we propose a 3D data‐transposition method that converts the target 1D vector into a contiguous memory layout and improves data transfer efficiency. The transposed data are communicated between the host and device memories efficiently through the pinned buffer and multiple streams. We apply our method to various large‐scale benchmarks and compare its performance with the state‐of‐the‐art multicore CPU FFT library (i.e., fastest Fourier transform in the West [FFTW]) and a prior GPU‐based 3D‐FFT algorithm. Our method achieves a higher performance (up to 2.89 times) than FFTW; it yields more performance gaps as the data size increases. The performance of the prior GPU algorithm decreases considerably in massive‐scale problems, whereas our method's performance is stable.
An analysis of the structural and energetic properties of deoxyribose by potential energy methods

We discuss the three fundamental issues of a computational approach in structure prediction by potential energy minimization, and analyze them for the nucleic acid component deoxyribose. Predicting the conformation of deoxyribose is important not only because of the molecule's central conformational role in the nucleotide backbone, but also because energetic and geometric discrepancies from experimental data have exposed some underlying uncertainties in potential energy calculations. The three fundamental issues examined here are: (i) choice of coordinate system to represent the molecular conformation; (ii) construction of the potential energy function; and (iii) choice of the minimization technique. For our study, we use the following combination. First, the molecular conformation is represented in cartesian coordinate space with the full set of degrees of freedom. This provides an opportunity for comparison with the pseudorotation approximation. Second, the potential energy function is constructed so that all the interactions other than the nonbonded terms are represented by polynomials of the coordinate variables. Third, two powerful Newton methods that are globally and quadratically convergent are implemented: Gill and Murray's Modified Newton method and a Truncated Newton method, specifically developed for potential energy minimization. These strategies have produced the two experimentally‐observed structures of deoxyribose with geometric data (bond angles and dihedral angles) in very good agreement with experiment. More generally, the application of these modeling and minimization techniques to potential energy investigations is promising. The use of cartesian variables and polynomial representation of bond length, bond angle and torsional potentials promotes efficient second‐derivative computation and, hence, application of Newton methods. The truncated Newton, in particular, is ideally suited for potential energy minimization not only because the storage and computational requirements of Newton methods are made manageable, but also because it contains an important algorithmic adaptive feature: the minimization search is diverted from regions where the function is nonconvex and is directed quickly toward physically interesting regions.
Photon-number-resolved heralded-photon source for improved quantum key distribution

We have suppressed multiphoton probability of a heralded-photon source, which is vital for quantum key distribution with a higher secure key generation rate. It is accomplished by utilizing a practical photon-number-resolving detector for triggering resulting in an important step for improved practical quantum key distribution. Heralded-photon source and a practical photon-number-resolving detector capable of real-time processed multiphoton rejection are stably operable at room temperature and enable us to generate a secure key at a distance as long as an ideal single photon source is used.
Exploration and Clinical Verification of the Blood Co-Expression Genes of Type 2 Diabetes Mellitus and Mild Cognitive Dysfunction in the Elderly

With the development of society, the incidence of dementia and type 2 diabetes (T2DM) in the elderly has been increasing. Although the correlation between T2DM and mild cognitive impairment (MCI) has been confirmed in the previous literature, the interaction mechanism remains to be clarified. To explore the co-pathogenic genes in the blood of MCI and T2DM patients, clarify the correlation between T2DM and MCI, achieve the purpose of early disease prediction, and provide new ideas for the prevention and treatment of dementia. We downloaded T2DM and MCI microarray data from GEO databases and identified the differentially expressed genes associated with MCI and T2DM. We obtained co-expressed genes by intersecting differentially expressed genes. Then, we performed GO and KEGG enrichment analysis of co-DEGs. Next, we constructed the PPI network and found the hub genes in the network. By constructing the ROC curve of hub genes, the most valuable genes for diagnosis were obtained. Finally, the correlation between MCI and T2DM was clinically verified by means of a current situation investigation, and the hub gene was verified by qRT-PCR. A total of 214 co-DEGs were selected, 28 co-DEGs were up-regulated, and 90 co-DEGs were down-regulated. Functional enrichment analysis showed that co-DEGs were mainly enriched in metabolic diseases and some signaling pathways. The construction of the PPI network identified the hub genes in MCI and T2DM co-expression genes. We identified nine hub genes of co-DEGs, namely LNX2, BIRC6, ANKRD46, IRS1, TGFB1, APOA1, PSEN1, NPY, and ALDH2. Logistic regression analysis and person correlation analysis showed that T2DM was correlated with MCI, and T2DM increased the risk of cognitive impairment. The qRT-PCR results showed that the expressions of LNX2, BIRC6, ANKRD46, TGFB1, PSEN1, and ALDH2 were consistent with the results of bioinformatic analysis. This study screened the co-expressed genes of MCI and T2DM, which may provide new therapeutic targets for the diagnosis and treatment of diseases.
Wire Rope Defect Recognition Method Based on MFL Signal Analysis and 1D-CNNs

The quantitative defect detection of wire rope is crucial to guarantee safety in various application scenes, and sophisticated inspection conditions usually lead to the accurate testing of difficulties and challenges. Thus, a magnetic flux leakage (MFL) signal analysis and convolutional neural networks (CNNs)-based wire rope defect recognition method was proposed to solve this challenge. Typical wire rope defect inspection data obtained from one-dimensional (1D) MFL testing were first analyzed both in time and frequency domains. After the signal denoising through a new combination of Haar wavelet transform and differentiated operation and signal preprocessing by normalization, ten main features were used in the datasets, and then the principles of the proposed MFL and 1D-CNNs-based wire rope defect classifications were presented. Finally, the performance of the novel method was evaluated and compared with six machine learning methods and related algorithms, which demonstrated that the proposed method featured the highest testing accuracy (>98%) and was valid and feasible for the quantitative and accurate detection of broken wire defects. Additionally, the considerable application potential as well as the limitations of the proposed methods, and future work, were discussed.
Morphological dependence in the spatial orientations of Local Supercluster galaxies

We have compiled a database of 4073 morphologically identified galaxies with radial velocity <3000 km s −1 and examined the alignments of the spin vectors of these galaxies in the Local Supercluster (LSC). Our aim is to test the morpho- logical dependence of galaxy orientation. The "position angle - inclination" method is used to find the polar and azimuthal angles of the galaxy rotation axes. The spatial isotropic distribution is assumed to examine the non-random effects. We have carried out chi-square, Fourier, and auto correlation tests to examine non-random effects in the distributions of the polar and azimuthal angles of the galaxy rotation axes. We suspect that the orientations of galaxies in the LSC could be closely related to galactic morphology. The spiral galaxies exhibit anisotropy although not at a very high significance level. It is found that the spin vector orientations of the spiral galaxies in the LSC tend to lie perpendicular to the LSC plane. No preferred orientation is found in the spin vector orientations of barred spiral and irregular galaxies. The orientations of early-type and late-type spirals and barred spirals are discussed.
A theory of agreement and its application to Serbo-Croatian

1. OVERVIEW OF A THEORY OF AGREEMENT. Any treatment of morphosyntactic agreement must face those aberrant cases of HYBRID or MIXED agreement. In certain situations for example a noun triggers one set of agreement features on adjectives but the NP headed by that noun triggers a different set of agreement features on verbs or coreferential pronouns; or a noun triggers masculine features on adjectives and pronouns but belongs to the declension class normally reserved for feminine nouns, and so on. These exceptional cases also shed light on regular agreement processes. We present a theory of agreement and apply it to Serbo-Croatian, which, like its Slavic relatives, is richly endowed with regular and hybrid agreement. The mixed agreement patterns that are predicted by the theory, and no others, are attested in that language. Our theory may be summarized as follows. An inflected noun has two different feature sets that determine the agreement values it triggers: CONCORD features (case, number, and gender, for Serbo-Croatian); and the person, number, and gender features of the REFERENTIAL INDEX (Pollard & Sag 1994). 1 The concord feature of gender for a given noun is closely related to that noun's declension class, as schematized in 1.
Input-to-state stability of discrete-time singular systems based on quasi-min–max model predictive control

This study is concerned with robust quasi-min–max model predictive control (MPC) for a class of discrete-time singular systems with persistent disturbance and input constrains. To deal with the persistent disturbance, the authors introduce the notion of input-to-state stability (ISS) of discrete-time singular system for the first time. The optimal control can be obtained by solving a quasi-min–max optimal problem of a finite horizon cost function. On the basis of the proposed dual-mode MPC approach, it can be proved that the closed-loop discrete-time singular system is ISS, regular and causal. Finally, a numerical simulation shows the feasibility and effectiveness of the proposed method.
Impact of Adjuvant Hormone Therapy on Sleep, Physical Activity, and Quality of Life in Premenopausal Breast Cancer: 12-Month Observational Study

Purpose This study aimed to investigate the differences in sleep disturbance changes between patients receiving two hormone therapies (“tamoxifen plus ovarian function suppression group [T+OFS group]” versus “tamoxifen group [T group]”) and the chronological changes in sleep disturbances in each group. Methods Premenopausal women with unilateral breast cancer who underwent surgery and were scheduled to receive hormone therapy (HT) with tamoxifen alone or with tamoxifen plus gonadotropin-releasing hormone (GnRH) agonist for ovarian function suppression were included. The enrolled patients wore an actigraphy watch for two weeks and completed questionnaires (insomnia, sleep quality, physical activity [PA], and quality of life [QOL]) at five time points: immediately before HT and 2, 5, 8, and 11 months after HT. Results Among the 39 enrolled patients (21 and 18 patients in the T+OFS group and T group, respectively), 25 (17 and 8 patients in the T+OFS group and T group, respectively) were finally analyzed. There were no differences between the two groups in time-dependent changes in insomnia, sleep quality, total sleep time, rapid eye movement sleep rate, QOL, and PA; however, the severity of hot flashes was significantly higher in the T+OFS group than in the T group. Although the interaction between group and time was not significant, insomnia and sleep quality significantly worsened at 2–5 months of HT when changes over time were analyzed within the T+OFS group. In both the groups, PA and QOL were maintained without significant changes. Conclusion Unlike tamoxifen alone, tamoxifen plus GnRH agonist initially worsened insomnia and sleep quality, but gradually improved with long-term follow-up. Patients who initially experience insomnia during tamoxifen plus GnRH agonist administration can be reassured based on the results of this study, and active supportive care may be used during this period. Trial Registration ClinicalTrials.gov Identifier: NCT04116827
Mass transfer in a nonuniform impinging jet: Part I. Stagnation flow-velocity and pressure distribution

A theoretical solution for the impingement flow of a jet with a parabolic velocity distribution is given. Viscous generation and diffusion of vorticity in the jet were neglected. Experimental velocity and pressure distributions measured in an impinging jet of air originating with Poiseuille flow compare well with theory, thus justifying the assumption of inviscid flow. Pressure distributions on the deflecting surface were independent of nozzle height in the range 1 to 12 nozzle radii. For lower nozzle heights the effect of the constriction of flow between the nozzle and the surface followed the predicted behavior.
Interpretable Multiattribute Predictive Analysis Model Based on Rough Fuzzy Sets and Logistic Regression

The interpretability of prediction models is very important for decision management. The vast majority of existing prediction analysis models based on rough set theory lack a certain interpretability. To break through the existing framework, this article deeply integrates rough fuzzy sets and logistic regression to construct an interpretable prediction model for multiattribute information systems. First, the Jensen–Shannon divergence with statistical interpretability is used to capture the attribute information with strong correlation under on a level, and then an fresh attribute-oriented $\delta$-rough fuzzy set model is presented. The pessimistic and optimistic decision concepts of the proposed rough fuzzy set model are used to interpretability enhancement of data information. On this basis, an interpretable predictive analysis model is constructed by combining logistic regression model. The construction process of the prediction model is supported by sufficient interpretable information. The predicted result is a result of development trend with a certain interpretability. Finally, to assess the effectiveness and viability of the proposed prediction model, we conduct comparative experiments with other three prediction models accompanied with four prediction performance indexes. Experimental results display that the proposed prediction model has well-pleasing prediction performance and antinoise ability.