Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical investigation of inlet section structure effect on wear characteristic of particle condition in centrifugal slurry pump by CFD-DEM coupling

Abstract To improve the wear resistance of the centrifugal slurry pump, the inlet structure is optimized, and an equal-diameter inlet section structure is designed. Considering the particle-particle and particle-wall interactions, a two-phase flow simulation model based on CFD-DEM (computational fluid dynamics-discrete element method) coupling is established under the sparse particle condition. The Archard wear model and Relative wear model are used for quantitative and qualitative wear analysis. The flow field and particle trajectory analysis are carried out under an equal-diameter inlet section structure and a different-diameter inlet section structure. The wear characteristics of the flow-passing parts are carried out. The results show that the simulation model has good accuracy. The error between the numerical simulation results and the experimental results is less than 5%. Under the equal-diameter inlet section structure, the overall wear of the slurry pump is reduced by 15%, the wear of the volute chamber is reduced by 17.5%, and the wear of the inlet section is reduced by 93.8%. The equal-diameter inlet section structure can reduce the turbulent intensity and make the flow field stable. And the equal-diameter inlet section structure helps to reduce the wear degree and wear area of the pump.
Yield Forecasting by Machine Learning Algorithm: Evidence from China’s A-share Market

ABSTRACT This study uses five machine learning algorithms (Stochastic gradient descent (SGD), Decision tree, Random forest, Gradient boosting decision tree (GBDT), and Convolutional neural networks (CNN)) to explore their prediction effects on China’s stock market. It constructs a monthly rolling model for stock return prediction. Selecting stocks of the CSI 300 index from January to June 2021 as specific monthly samples and classifying three factors – fundamentals, volatility(risk) and technical indicators, the results demonstrate that (1) machine learning brings favorable investment returns in simulated quantitative trading of China’s A-share market (2) the technical indicator factor is the most valuable, with the momentum technical factor having greatest influence, followed by the volatility (risk) factor and fundamental factors. Therefore, this study has a critical reference value and is significant in guiding yield forecasting in intricate stock markets.
Many-body calculation of autoionization rates in atoms and molecules

A method to make ab initio predictions of electronic autoionization rates in atoms and molecules by use of many-body theory in the discrete basis set approximation is presented. The method is applied to the autoionizing states and in He and Ne, respectively, and to the state in the HF molecule. The many-body expansion is carried through the third order in the electronic interaction, which means that the leading correlation terms are included. Correlation effects were found to be important in all the three cases investigated, and very good agreement with experiment was obtained for He and Ne where experimental values are available.
A novel event correlation scheme for X-ray photon correlation spectroscopy

X-ray photon correlation spectroscopy (XPCS) was employed to measure the time-dependent intermediate scattering function in an organic molecular glass former. Slow translational dynamics were probed in the glassy state and the correlation functions were calculated from two-dimensional speckle patterns recorded by a CCD detector. The image frames were analysed using a droplet algorithm together with an event correlation scheme. This method provides results analogous to standard intensity correlation algorithms but is much faster, hence addressing the recurrent problem of insufficient computing power for online analysis in XPCS. The event correlator has a wide range of potential future applications at synchrotrons and free-electron laser sources.
Student perceptions of digital distraction prevention and student–instructor rapport

ABSTRACT The present study investigated how course policies and enforcement strategies designed to curb classroom digital distraction affect undergraduates' perceptions of student-instructor rapport. Data gathered from online surveys completed by undergraduates at four United States universities revealed that student perceptions of rapport can be influenced by digital distraction prevention. Participants endorsed course technology policies that are developed in collaboration between students and instructors and that are targeted at curbing the use of digital devices for social, rather than educational, purposes. Findings indicate that such policies can improve student buy-in and improve student perceptions of rapport. Although participants identified confrontational enforcement strategies (e.g., calling students out, grade reductions, phone confiscation) as most effective for reducing the amount of digital distraction during class when policies are violated, these strategies were also identified as being most harmful to their perceptions of rapport with instructors. Despite regularly using devices for off-task purposes during class, most participants are not worried about getting caught because they do not believe their instructors are particularly concerned about the amount of ongoing digital distraction in the classroom. Recommendations for addressing student digital distraction while protecting the quality of student-instructor rapport are provided through the lens of self-determination theory.
Fixed Points of Loopy Belief Propagation as Zero Gradients of a Function of Reparameterizations

The existing view on loopy belief propagation sees it as an algorithm to find a common zero of a system of non-linear functions, not explicitly related to each other. We show that these functions are in fact related – they are the partial derivatives of a single function of reparameterizations. Thus, belief propagation searches for a zero gradient of a single function. We show that belief propagation fixed points are in one-to-one correspondence with zero gradient points of this function and that every such point is a saddle.
Organic host analogues and the search for life on Mars

Abstract Mars analogue sites represent vital tools in our continued study of the Red Planet; the similar physico-chemical processes that shape a given analogue environment on Earth allow researchers to both prepare for known Martian conditions and uncover presently unknown relationships. This review of organic host analogues – sites on Earth that mimic the putatively low organic content of Mars – examines specific locations that present particular Mars-like obstacles to biological processes. Low temperatures, aridity, high radiation and oxidizing soils characterise modern-day Mars, while acid–saline waters would have presented their own challenges during the planet's warmer and wetter past. By studying each of these hurdles to life on Earth, scientists can prepare instruments headed for Mars and identify the best locations and approaches with which to look for biological signatures. As our use of organic host analogues becomes increasingly sophisticated, researchers will work to identify terrestrial sites exhibiting multiple Mars-like conditions that are tailored to the distinct mineralogical and physical characteristics of Martian locations. Making use of organic host analogues in these ways will enhance the search for signs of past or present life on Mars.
Observations of suppressed retention and blistering for tungsten exposed to deuterium–helium mixture plasmas

Blister formation and D retention in W have been investigated for low energy (∼55 ± 15 eV), high flux (∼1022 m−2 s−1), high fluence (⩽4.5 × 1026 m−2) ion bombardment at moderate temperature (∼573 K) in mixed species D+He plasmas in the linear divertor plasma simulator PISCES-A. The amount of D retained in W is found to decrease significantly when compared with that in W exposed to pure D plasmas, as measured with high resolution thermal desorption spectroscopy. Scanning electron microscopy observations reveal the suppression of the blisters, a surface feature known to drive up retention, in the D + He mixture plasma exposed W samples. Reduced D retention is accompanied by the formation of nano-sized high density He bubbles in the near surface, observed with a transmission electron microscope (TEM). It is believed that the nano-bubbles act as a diffusion barrier to implanted D atoms and consequently reduce the amount of uptake in the W material. This newly observed effect implies that current predictions of D retention in W, in actual fusion devices, may be overestimated, since there will be He ash in fusion plasma. Toughness enhanced, fine-grained (grain size of ∼1 µm) W–TiC samples, exposed to pure D plasma conditions, also show little or no evidence of blistering. The measured D retention in the W–TiC samples was approximately 1 × 1019 D m−2 corresponding to about 2 × 10−7 of the implanted D fluence, and is very low compared with the retention in pure stress relieved W, which exhibited surface blisters and had a D retention of about 1 × 1021 D m−2.
A multi-center, double-blind, randomized parallel-group Phase IV study comparing the efficacy and safety of thiocolchicoside ointment versus placebo in patients with chronic mechanical low back pain and an acute muscle spasm

Objectives This study aims to evaluate the efficacy and safety of thiocolchicoside (TCC) ointment treatment compared to placebo in patients with chronic mechanical low back pain (LBP) accompanied by acute muscle spasms. Patients and methods A total of 292 adult patients (106 males, 186 females; mean age: 38.5±11.2 years; range, 18 to 64 years) were randomized to TCC group (n=147) and placebo group (n=145) in 12 centers between March 2020 and March 2021. Eight patients from each group were excluded from the analysis. The primary endpoint was pressure pain threshold (PPT) on Day 3, which was measured using a pressure algometer. Secondary endpoints were PPT on Day 7, patient, and physician Visual Analog Scales-pain (VAS-pain) on Days 3 and 7, and safety. Results The PPT values on Day 3 was not significantly different between the treatment groups (p=0.701). Similarly, TCC and placebo group had similar VAS-pain scores over trial period (p=0.577 or higher for comparisons). Significantly higher PPT values and lower VAS-pain scores on Days 3 and 7 were observed in both groups (p<0.001 for all). In patients with a PPT value of ≥3.87, TCC arm had higher PPT on Day 3 compared to placebo (p=0.029). Three patients (two in the TCC arm and one in the placebo arm) discontinued the trial due to an adverse event. Conclusion Topical TCC can be an appropriate option in a subset of patients with mild chronic LBP accompanied by muscle spasms. In a subset of patients with milder pain intensity, topical TCC may improve pain earlier. The results of this trial are compatible with the treatment approaches used in daily practice.
Material Extrusion of Helical Shape Memory Polymer Artificial Muscles for Human Space Exploration Apparatus

Astronauts suffer skeletal muscle atrophy in microgravity and/or zero-gravity environments. Artificial muscle-actuated exoskeletons can aid astronauts in physically strenuous situations to mitigate risk during spaceflight missions. Current artificial muscle fabrication methods are technically challenging to be performed during spaceflight. The objective of this research is to unveil the effects of critical operating conditions on artificial muscle formation and geometry in a newly developed helical fiber extrusion method. It is found that the fiber outer diameter decreases and pitch increases when the printhead temperature increases, inlet pressure increases, or cooling fan speed decreases. Similarly, fiber thickness increases when the cooling fan speed decreases or printhead temperature increases. Extrusion conditions also affect surface morphology and mechanical properties. Particularly, extrusion conditions leading to an increased polymer temperature during extrusion can result in lower surface roughness and increased tensile strength and elastic modulus. The shape memory properties of an extruded fiber are demonstrated in this study to validate the ability of the fiber from shape memory polymer to act as an artificial muscle. The effects of the operating conditions are summarized into a phase diagram for selecting suitable parameters for fabricating helical artificial muscles with controllable geometries and excellent performance in the future.
The Kernel Estimate of a Regression Function in Likelihood-Based Models

Abstract Smoothing splines have a penalized likelihood motivation (Good and Gaskins 1971) allowing direct application to nonparametric regression in likelihood-based models. The notion of a weighted likelihood for the nonparametric kernel estimation of a regression function is proposed, generalizing the local likelihood theory of Tibshirani and Hastie (1987). Let the data be of the form (xi, Yi ) (i = 1, …, n), where xi ∈ [0, 1] d are lattice points and the Yi are independent random variables from a family of distributions with parameter λi = g(xi ), with g having continuous partial derivatives of order k ≥ 2. The goal is to arrive at a nonparametric estimate λ o of λ o = g(xo ) for a fixed point xo ∈ [0, 1] d. We consider the estimator λ o that maximizes the weighted likelihood function W(λ) = Σ n i=1 W[(xo – xi )/b] log f(Yi :λ), with f the density of Yi, W a symmetric kernel with compact support, and b the bandwidth that controls the degree of smoothing. Sufficient conditions for consistency and asympt.
Willingness, Attitude, and Associated Factors towards Adverse Drug Reaction Reporting among Healthcare Providers in Mizan Tepi University Teaching Hospital, Southwest Ethiopia

Background An adverse drug reaction (ADR) is harm that arises from the use of a drug. Adverse drug reactions have a huge impact on the health system since they result in drug-related morbidity and mortality as well as indirect costs such as loss of productivity at work. Reporting of adverse drug reactions to a relevant authority is one of the methods of enhancing medication safety; however, underreporting of adverse drug reactions by health workers is a major challenge in enhancing medicines safety. The aim of this study was to assess the willingness, attitude, and associated factors of healthcare providers towards ADRs reporting at Mizan Tepi University Teaching Hospital (MTUTH). Methods A cross-sectional mixed method was conducted among healthcare providers working in Mizan Tepi University Teaching Hospital from August to September 2021. A total of 190 healthcare providers and five key informants were participated in the study. The quantitative data were collected using self-administered structured questionnaires, and for the qualitative study, data from the key informant interviews were collected using a semistructured questionnaire containing open-ended questions. The collected data were coded, entered, and analyzed using a Statistical Package for Social Sciences (SPSS, version 21). Furthermore, the logistic regression model was fitted to see the association between attitude items and demographic characteristics. Variables with P value <0.05 were considered as statistically significant. Analysis of the qualitative data was done by sorting the data into categories and examining the emerging themes. Results The majority of individuals in the study (81.6%) were willing to report adverse drug reactions. High percent (57.9%) of the study participants knew how to report ADR to responsible body and 66 (34.7%) of the study participants believe that ADR reporting is the responsibility of all healthcare professionals. 86 (45.3%) of respondents encountered ADR cases during their professional career. It was found that the majority of participants (53.7%) had a positive attitude toward ADR reporting. The professional distribution and work experiences of healthcare professionals had a significant impact on their attitude toward ADR reporting (P < 0.05). Conclusion A large percentage of study subjects were willing to report adverse drug reactions to the appropriate authorities. The majority of healthcare providers were found to have a good attitude towards ADR reporting. Professional distribution and work experiences were significantly associated with attitude of healthcare providers towards ADR reporting. In order to improve the ADR reporting practices of the healthcare professionals and increase the ADR reporting load at the national level, the national regulatory body should collaborate with health facilities.
Two new Eresus species (Araneae, Eresidae) from Xinjiang, China

Abstract Background Eresidae C. L. Koch, 1845 contains nine genera and 102 species, of which 24 species belong to Eresus Walckenaer, 1805. Four species of the family are known from China: E.granosus Simon, 1895 (Beijing), E.kollari Rossi, 1846 (Hebei), E.lishizheni Lin, Marusik & Li, 2021 (Xinjiang) and Stegodyphustibialis (O. Pickard-Cambridge, 1869) (Yunnan). New information Two new species of Eresus are described from Xinjiang, China: Eresusda Lin & Li sp. n. and E.yukuni Lin & Li sp. n. Photos and morphological descriptions of new species are given.
Operational calculus for tensor products of linear operators in Banach spaces

eigenvalue of B. The aim of the present paper is to extend this result and to prove the spectral mapping theorem for tensor products of densely defined closed linear operators in complex Banach spaces. We develop an operational calculus defined for holomorphic functions of several variables in a neighbourhood of the product of the extended spectra of those operators, which may be considered roughly as the tensor product of the operational calculi defined for holomorphic functions of one variable developed by I. Gelfand, Dunford and Taylor ([15], [3], [20], [8]). Brown and Pearcy [2] have proved for bounded operators A and B on a Hilbert space and P(\xi, \eta)=\xi\cdot\eta that the spectrum of the tensor product A\otimes B is the set of the products of the spectra of A and B. Ichinose [9] has extended it for some unbounded operators A and B in Banach spaces. The result of St\’ephanos for several bounded operators in Banach spaces has also been obtained by Schechter [19]. Our results include those of Brown and Pearcy, Schechter and partly Ichin The spectral mapping theorem enables us, in particular, to find the resolvent of a polynomial operator defined for tensor products of closed operators, from the knowledge of the spectra of those operators. Section 1 deals with the basic notions about linear operators, their maximal extensions and their spectra, and tensor products of spaces and operators.
Data-Driven Passivity-Based Control of Underactuated Robotic Systems

Classical control strategies for robotic systems are based on the idea that feedback control can be used to override the natural dynamics of the machines. Passivity-based control (Pbc) is a branch of nonlinear control theory that follows a similar approach, where the natural dynamics is modified based on the overall energy of the system. This method involves transforming a nonlinear control system, through a suitable control input, into another fictitious system that has desirable stability characteristics. The majority of Pbc techniques require the discovery of a reasonable storage function, which acts as a Lyapunov function candidate that can be used to certify stability. There are several challenges in the design of a suitable storage function, including: 1) what a reasonable choice for the function is for a given control system, and 2) the control synthesis requires a closed-form solution to a set of nonlinear partial differential equations. The latter is in general difficult to overcome, especially for systems with high degrees of freedom, limiting the applicability of Pbc techniques. A machine learning framework that automatically determines the storage function for underactuated robotic systems is introduced in this dissertation. This framework combines the expressive power of neural networks with the systematic methods of the Pbc paradigm, bridging the gap between controllers derived from learning algorithms and nonlinear control theory. A series of experiments demonstrates the efficacy and applicability of this framework for a family of underactuated robots.
Formation of ring patterns surrounded by ripples by single-shot laser irradiation with ultrashort pulse width at the solid/liquid interface

A single pulse (pulse width: 200 fs) was irradiated onto a water/silicon interface. The processed surface had many ring patterns surrounded by sinusoidal patterns within the irradiated spot. The diameter of their rings ranged from 500 nm to 10 μm. It was proposed that the oscillation of a bubble at the interface emitted an acoustic wave around itself and that the melted silicon surface, deformed due to acoustic pressure, solidified instantaneously in the course of the propagation of the acoustic wave on the silicon surface.
Traffic Mosaic: Traffic Data Imputation Method Inspired by Image Super Resolution

Missing data is a major problem in data-driven intelligent transportation systems. This study presents an imputation method, called TrafficMosaic, for effective imputation of lost traffic flow data. If we consider traffic data as a image, then the missing data in it can be regarded as a mosaic. The design of TrafficMosaic is inspired by super resolution techniques. First, a deep neural network (DNN) is employed to recover the lost data by a suite of techniques inspired from image super resolution. This DNN method combines the temporal relevance of historical flow with spatial correlation of current fragmented flow data, and uses the imputation result as input for recursive calculation. Second, a data-driven road network matrixing algorithm is proposed to mine location relations from trajectory data and reconstruct a road network flow into matrixes of road network flow pictures. Convolutional local calculation in a convolutional neural network is introduced to extract local spatial features of the road network, thereby reducing the computational complexity and improving the generalization ability. The final step is to extract the local temporal features of the flow data. Traffic flows at adjacent moments have strong temporal characteristics, and we splice several historical road network traffic pictures in chronological order so that our model can capture temporal information from the sequence. The experimental evaluation used a real automatic number plate recognition dataset for experiments, and the results show the effectiveness of TrafficMosaic for lost data imputation.