Miracle-dz/UniFAR-FTUs huggingface dataset:
Translation, cross-cultural adaptation and validation of the Persian version of selected PROMIS measures for use in lumbar canal stenosis patients

BACKGROUND: The National Institutes of Health (NIH) developed a new measurement system called the Patient-Reported Outcomes Measurement Information System (PROMIS) which can be used for multiple health conditions. The 29-item short form (PROMIS-29) with seven domains was more often used by clinical researchers to measure the physical function, mood and sleeping status of patients with low back pain (LBP). Translation of the PROMIS into multiple languages and adaptation of its application in different cultural diversities can help to further standardize clinical research studies and make them comparable to each other. This study aimed to cross-culturally adapt the PROMIS-29 into Persian (P-PROMIS-29) and evaluate the construct validity and reliability of the translated questionnaire among patients with lumbar canal stenosis. MATERIALS AND METHODS: The translation was conducted by using the multilingual translation methodology guideline. Construct validity, internal consistency, and test–retest reliability at a two-week interval for the P-PROMIS-29 were calculated. Construct validity was assessed by calculating correlations between the P-PROMIS-29 with Oswestry Disability Index (ODI) and Roland–Morris results. RESULTS: The study sample included 70 participants with lumbar canal stenosis. Internal consistencies were moderate to good with Cronbach's alpha ranging from 0.2 to 0.94. The test–retest reliability evaluation was excellent with intraclass correlation coefficients (ICCs) ranging from 0.885 to 0.986. Construct validity of different domains of P-PROMIS-29 were moderate to good, with Pearson's correlation coefficient results ranging from 0.223 to 0.749. CONCLUSION: Our results showed that P-PROMIS-29 is a valid and reliable measurement tool for evaluation of patients with lumbar canal stenosis.
Fitting growth curves of coffee plants in the nursery stage of growth: A functional approach

The growth patterns of coffee plants are determined by interactions between genetic, physiological, and climate factors. The objective of this study was to evaluate the growth patterns of coffee plants in the nursery under the climatic conditions of Chinchiná, Caldas, Colombia, during the first semester of 2019. Measurements were carried out in the Cenicafé 1 variety during six months. Growth parameters such as leaf area, number of leaves, height, stem diameter, and length of the main root were evaluated every 15 d after transplanting (DAT) in 20 plants and the averages of absolute growth (Ĝ) rate of each growth variable were calculated. For the total leaf area, total number of leaves, and stem height, a sigmoidal-type growth curve was adjusted, while the growth curve was linear for the stem diameter (R2 = 0.97) and main root length (R2 = 0.95). Average values were obtained for 520 cm2 for total leaf area, with an Ĝ of 3.31 cm2 d-1, 11 for total leaves (Ĝ 0.055 leaves d-1), 30.23 cm for height (Ĝ 0.155 cm d-1), 4.87 mm for stem diameter (Ĝ 0.199 mm d-1), and 28.80 cm for main root length (Ĝ 0.087 cm d-1) at 180 DAT. These results suggest that growth curves could be a useful tool for describing the growth patterns of coffee seedlings during the nursery stage of growth.
Method of Neighborhood Formation in Collaborative Filtering

In collaborative filtering,sparsity in ratings makes inaccurate neighborhood formation,thereby resulting in poor recommendations. To address this issue,a method of neighborhood formation,two-phase neighbor selection method( TPNS),is proposed. The definition of neighbor tendency is given. Based on the neighbor tendency,the preliminary neighborhood is formed. Then,the equivalence relation similarity is applied to modify the preliminary neighborhood,which makes the neighborhood formation more accurate. Experimental results on MovieLens dataset show that compared with the existing algorithms,TPNS performs better in the application of personalized recommendation.
Ab initio study on the electronic states and laser cooling of AlCl and AlBr

We investigate whether AlCl and AlBr are promising candidates for laser cooling. We report new ab initio calculations on the ground state X1Σ+ and two low-lying states (A1Π and a3Π) of AlCl and AlBr. The calculated spectroscopic constants show good agreement with available theoretical and experimental results. We also obtain the permanent dipole moments (PDMs) curve at multi-reference configuration interaction (MRCI) level of theory. The transition properties of A1Π and a3Π states are predicted, including the transition dipole moments (TDMs), Franck–Condon factors (FCFs), radiative times and radiative width. The calculated radiative lifetimes are of the order of a nanosecond, implying that they are sufficiently short for rapid laser cooling. Both AlCl and AlBr have highly diagonally distributed FCFs which are crucial requirement for molecular laser cooling. The results demonstrate the feasibility of laser cooling AlCl and AlBr, and we propose laser cooling schemes for AlCl and AlBr.
Probabilistic Value-Centric Optimization Design for Fractionated Spacecrafts Based on Unscented Transformation

Fractionated spacecrafts are of particular interest for pointing-intensive missions because of their ability to decouple physically the satellite bus and some imaging payloads, which possess a lesser lifecycle cost than a comparable monolithic spacecraft. Considering the probabilistic uncertainties during the mission lifecycle, the cost assessment or architecture optimization is essentially a stochastic problem. Thus, this research seeks to quantitatively assess different spacecraft architecture strategies for remote-sensing missions. A dynamical lifecycle simulation and parametric models are developed to evaluate the lifecycle costs, while the mass, propellant usage, and some other constraints on spacecraft are assessed using nonparametric, physics-based computer models. Compared with the traditional Monte Carlo simulation to produce uncertain distributions during the lifecycle, the unscented transformation is employed to reduce the computational overhead, just as it does in improving the extended Kalman filter. Furthermore, the genetic algorithm is applied to optimize the fractionated architecture based on the probabilistic value-centric assessments developed in this paper.
Enabling Scalable, Ultralow-Voltage Flexible Organic Field-Effect Transistors via Blade-Coated Cross-Linked Thick Polyvinyl Alcohol Gate Dielectric

A scalable ultralow-voltage flexible organic field-effect transistor (OFET) design has been accomplished through utilization of a blade-deposited thick cross-linked polyvinyl alcohol (c-PVA) dielectric. This blade-deposited thick c-PVA dielectric film is capable of suppressing device leakage, enabling high-performing OFETs with benchmark electrical properties of ultr- alow operation voltage (< 1 V), high field-effect mobility close to 10 cm2/<inline-formula> <tex-math notation="LaTeX">$\text{V}\cdot \text{s}$ </tex-math></inline-formula>, and excellent subthreshold swing < 100 mV/decade. In addition, the OFETs with blade-deposited c-PVA gate dielectric have exhibited excellent mechanical stress stability, with only minimum performance degradation after 2 h of static bending or <inline-formula> <tex-math notation="LaTeX">$10^{{3}}$ </tex-math></inline-formula> cycles of bending. These results will enable realization of a simple low-cost manufacturing process for high-performance, low-voltage flexible OFETs for a great variety of organic electronics.
Allometry, Isometry and Shape in Principal Components Analysis

Morphological variation in size and shape has physiological, ecological and taxonomic significance (e.g., Peters, 1983; Schmidt-Nielsen, 1984; Bookstein et al., 1985). As a result, there is considerable interest in partitioning components of variation associated with size from components associated with shape (e.g., Mosimann and James, 1979; Humphries et al., 1981; Reist, 1985; Sampson and Siegel, 1985; Somers, 1986; Corruccini, 1987). Size-related variation is often evaluated within a bivariate framework involving logarithmic transformations and regression (e.g., Smith, 1980; Seim and Saether, 1983). As such, log-log regressions with slopes equal to 1.0 indicate bivariate changes in size with no concomitant change in shape (i.e., isometry), whereas slopes differing from 1.0 reflect bivariate changes in shape that are correlated with changes in size (i.e., allometry). This bivariate conceptualization of size and shape has been extrapolated to a multivariate model summarized by principal components analysis (PCA; e.g., see Jolicoeur, 1963). A PCA of a variance-covariance matrix of logarithmically transformed morphometric data generally extracts a first component (i.e., PC1) that summarizes variation associated with size, both isometric and allometric size (e.g., see Jolicoeur and Mosimann, 1960; Mosimann, 1970; Pimentel, 1979:56-63). Because allometric size represents bivariate shape that is correlated with isometric size, PC1 frequently contains information in both size and shape (e.g., Hopkins, 1966; Mosimann, 1970; Jungers and German, 1981; Hills, 1982; Corruccini, 1983). The multivariate principal-component model also introduced a multidimensional concept of shape independent of size (i.e., the second and subsequent components where size-correlated variation is incorporated into PC1; e.g., Jolicoeur and Mosimann, 1960). The bivariate analogue of multivariate shape is the pattern displayed by the log-log regression residuals. Just as in regression, multivariate shape is contingent on the analytical approach and associated transformations, as well as the spatial pattern of the data. In addition, the study of multivariate shape is further complicated by the problem of deciding how many shape components contain non-trivial information (e.g., Linn, 1968; Horn and Engstrom, 1979; Gauch, 1982; Gibson et al., 1984; Stauffer et al., 1985).
Finite-dimensional filter for a class of nonlinear systems with correlated noises

ABSTRACT The purpose of this article is to compute an explicit formula for the unnormalized conditional density for the filter associated with a nonlinear filtering problem with correlated noises and a signal process with nonlinear terms in the drift. This article extends the result of Daum to nonlinear filtering systems with correlated noises and incorporates both the Kalman–Bucy and Beneš filters as particular cases.
Dose calculation of different eye substructures using a realistic eye model when treating ocular tumors with electron therapy

One of the most frequent types of intraocular melanoma in adults is choroidal uveal melanoma. The most commonly used forms of radiation therapy are ophthalmic plaque brachytherapy and charged particle external radiation therapy. In the absence of adequate facilities for brachytherapy and proton therapy, electron therapy would be an efficient radiation therapy technique for treating eye melanomas. In the present work, the Monte Carlo code MCNPX 2.6. 0 was used to calculate the dose distribution to substructures of the eye in electron therapy of three common choroidal tumors. The simulations were performed for 6 electron beams with nominal energies between 5 MeV and 10 MeV and also for 10 incidence angles. To identify suitable treatment plans, the tumor-to-sensitive zone dose ratios were estimated. Moreover, the equivalent doses delivered to healthy substructures of the eye were also calculated. The results indicate that for the treatment of tumors located at the posterior part of the eye, an electron beam with energy of 10 MeV and incident angle of 45° relative to the eye axis provides the best tumor coverage while optimally sparing other eye substructures. In addition, for tumors positioned on the upper and lower parts of the vitreous, electron beams with energy of 10 MeV, an azimuthal angle of 270°, and polar incident angles of 90° and 105°, respectively, lead to appropriate dose delivery.
To Drop or to Select: Reduce the Negative Effects of Disturbance Features for Point Cloud Classification From an Interpretable Perspective

The perturbation features limit the performance of point cloud classification models, both for clean point clouds and those obtained from the real world. In this paper, we propose two methods to enhance models by reducing the negative impact of the nuisance features from the perspective of interpretability, respectively, dropping the nuisance points before inputting the point cloud into models and adaptively selecting the important features during the training process. The former is achieved by saliency analysis of models, the perturbation points are those with low contribution to models. For each sample, dropping the low contribution points based on the saliency scores is equivalent to filtering the perturbation features. We design a generic framework for generating saliency maps for various models and datasets, and obtain empirical values for the number of dropped points on each set of them. Then we apply the unsupervised dropping process to improve the robustness of models. The latter is achieved by adaptive downsampling, and we design a multi-stage learnable class-attention-based downsampling module to replace the commonly used Farthest Point Sampling (FPS). As the training progresses, the downsampling module tends to select the common features for each category, thus eliminating the nuisance features to improve the learning efficiency of the model. For dropping points (DP), we generate saliency maps for PointNet&++, DGCNN and PointMLP on ModelNet40 and ScanObjectNN, PointNet+DP reaches an overall accuracy (OA) of 92.5% and 72% on ModelNet40 and ScanObjectNN, surpassing the original model by 3.4% and 5.3%, the OA of PointNet++ with DP on ModelNet40 object classification can be raised from 91.8% to 93.7%. For adaptive feature selection (AFS), PointMLP-elite+AFS reaches an OA of 92.5% and a mean accuracy (mAcc) of 72% on ScanObjectNN, surpassing the original model by 0.8% and 1%. It reaches the level of PointMLP with 6.3% of the number of parameters. Considering the difficulty of the deployment of deep models, PointMLP-elite+AFS is the most cost-effective classification model known on ScanObjectNN.
Antibacterial Activity of the Green Synthesized Plasmonic Silver Nanoparticles with Crystalline Structure against Gram-Positive and Gram-Negative Bacteria

Nanoparticles (NPs) have attracted considerable interest in numerous fields, including agriculture, medicine, the environment, and engineering. The use of green synthesis techniques that employ natural reducing agents to reduce metal ions and form NPs is of particular interest. This study investigates the use of green tea (GT) extract as a reducing agent for the synthesis of silver NPs (Ag NPs) with crystalline structure. Several analytical techniques, including UV-visible spectrophotometry, Fourier transform infrared (FTIR) spectroscopy, high-resolution transmission electron microscopy (HR-TEM), and X-ray diffraction (XRD), were used to characterize the synthesized Ag NPs. The results of UV-vis revealed that the biosynthesized Ag NPs exhibited an absorbance plasmonic resonance peak at 470 nm. According to FTIR analyses, the attachment of Ag NPs to polyphenolic compounds resulted in a decrease in intensity and band shifting. In addition, the XRD analysis confirmed the presence of sharp crystalline peaks associated with face-centered cubic Ag NPs. Moreover, HR-TEM revealed that the synthesized particles were spherical and 50 nm in size on average. The Ag NPs demonstrated promising antimicrobial activity against Gram-positive (GP) bacteria, Brevibacterium luteolum and Staphylococcus aureus, and Gram-negative (GN) bacteria, Pseudomonas aeruginosa and Escherichia coli, with a minimal inhibitory concentration (MIC) of 6.4 mg/mL for GN and 12.8 mg/mL for GP. Overall, these findings suggest that Ag NPs can be utilized as effective antimicrobial agents.
Service Restoration of Distribution Networks Considering Switching Operation Costs and Actual Status of the Switching Equipment

Minimization of the de-energized consumers load and reduction of the service restoration costs are considered in the proposed heuristic graph-based approach for finding the solution of the service restoration in distributed networks. The approach is based on the logic of the modified Prim's algorithm that finds the minimum spanning trees (i.e., a forest). Operation costs including an actual status (“open” or “close”) of the switching equipment in a de-energized area is represented by the switching cost coefficients. The cost coefficients are assigned to all branches in a de-energized area. The switching action is performed by switching equipment with minimal switching costs coefficient in each iteration of the algorithm. The results confirm that the service restoration costs are decreased by the consideration of the actual status of the switching equipment.
Kinetic Energy Release in Fission of U238, U235, Th232 and Bi209 by High Energy Neutrons

The ionization produced by single fission fragments was observed in an ionization chamber using electron collection. If fission is induced by 90 Mev neutrons, the distribution of kinetic energy of the fission fragment versus the n~1ber of fragments is found to haye a single peak in contrast to the double-peaked curve corresponding to the fission made by thermal neutrons. Fission induced by 45 Mev neutrons gives a distribution in which two peaks appear. The dip between the two peaks is about twenty percent of the height of the peaks. kinetic if 45 Mev for 80 Mev 83 Mev for Th232 1 75 Mev Bi209 the case of fission 90 Mev neutrons.
Capabilities of fluorescence spectroscopy using 5-ALA and optical coherence tomography for diagnosis of neoplastic processes in the uterine cervix and vulva

A new approach for improving the diagnostic value of optical methods is suggested. It is based on the complementary use of different optical parameters of biotissues. The goal of this paper is the comparative study of the capabilities of two optical methods-fluorescence spectroscopy and optical coherence tomography-for visualization of borders of neoplastic processes in the uterine cervix and vulva. Fluorescence spectroscopy provides information on biochemical properties, and optical coherence tomography, on morphological properties of healthy and pathological tissues. Optical borders detected employing these techniques were verified histologically. The OCT and fluorescence borders of tumors are 1-4 mm farther than the colposcopically detectable borders. The borders of tumors detected by OCT are in good agreement with the results of biopsy. In 40% of cases, there were no coincident fluorescence and OCT borders of tumors. In several clinical cases, it was difficult to interpret OCT images (due to scarry, metaplastic, or acanthotic changes in the uterine cervix) and fluorescence spectroscopy data (due to inflammatory changes).
Sparsity-Constrained Kernel Recursive Generalized Maximum Versoria Criterion Algorithm

This letter proposes a novel random Fourier features (RFF) based sparsity-aware Kernel recursive adaptive filtering algorithm which employs generalized maximum Versoria criterion (GMVC) as an adaptation cost and generalized Versoria zero attraction (GVZA) as a sparsifying-norm. The proposed RFF-based GVZA kernel recursive GMVC (RFF-GVZA-KRGMVC) algorithm is robust for nonlinear sparse channel estimation under non-Gaussian noise over both stationary and non-stationary environments. Simulations indicate that the proposed RFF-GVZA-KRGMVC approach delivers better convergence and bit error rate performance over the existing stochastic gradient based RFF-ZA-kernel-MVC (RFF-ZA-KMVC) algorithm at the cost of increased computational complexity. Furthermore, detailed convergence analysis is also performed for the proposed algorithm and corroborated by Monte-Carlo simulations.
Immunological Features of LRRK2 Function and Its Role in the Gut-Brain Axis Governing Parkinson’s Disease

Emerging evidence implicates intestinal involvement in the onset and/or progression on the selective degeneration of dopaminergic neurons characterizing Parkinson’s disease (PD). On the one hand, there are studies supporting the Braak hypothesis that holds that pathologic α-synuclein, a hallmark of PD, is secreted by enteric nerves into intestinal tissue and finds its way to the central nervous system (CNS) via retrograde movement in the vagus nerve. On the other hand, there is data showing that cells bearing leucine-rich repeat kinase 2 (LRRK2), a signaling molecule with genetic variants associated with both PD and with inflammatory bowel disease, can be activated in intestinal tissue and contribute locally to intestinal inflammation, or peripherally to PD pathogenesis via cell trafficking to the CNS. Importantly, these gut-centered factors affecting PD development are not necessarily independent of one another: they may interact and enhance their respective pathologic functions. In this review, we discuss this possibility by analysis of studies conducted in recent years focusing on the ability of LRRK2 to shape immunologic responses and the role of α-synuclein in influencing this ability.
The Effect of Apertures Position on Shielding Effectiveness of Metallic Enclosures based on Modal Method of Moments

In this study, an effective numerical method suitable for determination of electric field Shielding Effectiveness (SE) of rectangular enclosure with multiple rectangular apertures is presented. Assuming appropriate electric field distribution on the aperture, Electromagnetic fields inside the enclosure are determined using rectangular cavity Green's function. Electromagnetic fields outside the enclosure and scattered due to the aperture are obtained using the free space Green's function. Matching the tangential magnetic field across the apertures, the integral equation with aperture fields as unknown variables is obtained. The integral equation is solved for unknown aperture fields using the Method of Moments. From the aperture fields the electromagnetic SE of the rectangular enclosure is determined. The numerical results of the proposed technique are in very good agreement with data available in the literature and experimental results. It is shown that apertures' position and shape, aperture' number, polarization have noticeable effect on the electric field SE.
Estimation of Conditional Moment Restrictions without Assuming Parameter Identiability

A well known difficulty in estimating conditional moment restrictions is that the parameters of interest need not be globally identified by the implied unconditional moments. In this paper, we propose an approach to constructing a continuum of unconditional moments that can ensure parameter identifiability. These unconditional moments depend on the “instruments” generated from a “generically comprehensively revealing” function and are projected along the exponential Fourier series. The objective function is based on the resulting Fourier coefficients, from which a consistent estimator can be easily obtained. A novel feature of our method is that the full continuum of unconditional moments is incorporated into each Fourier coefficient. We show that, when the number of Fourier coefficients in the objective function grows at a proper rate, the proposed estimator is consistent and asymptotically normally distributed. An efficient estimator is also readily obtained via a conventional GMM method. Our simulations confirm that the proposed consistent estimator compares favorably with that of Dominguez and Lobato (2004, Econometrica) in terms of bias, standard error and mean squared error. JEL classification: C12, C22