The SPSS-based Analysis of Reading Comprehension—Take Grade Eight English Mid-term Test for Example

Based on some language testing theories, an analysis of an English Mid-term Examination of grade eight students of JingZhi Middle School is made in this paper. By means of SPSS statistical software, the former study firstly makes a whole analysis of the test paper, which covers descriptive statistics, reliability and validity. Subsequently, on the basis of the former study, this study mainly makes an analysis of the relationship of all the items in reading comprehension from the perspective of facility value, discrimination index, reliability and validity. The research aims to find some problems in reading comprehension in this test paper. Thus, according to the results of this analysis, the quality of test papers can be improved and some advice can be given to language teaching

Tribological performances of fabric self-lubricating liner with different weft densities under severe working conditions

Several woven fabric self-lubricating liners with weft densities of 200-450 root/10cm in a spacing of 50 root/10cm have been prepared to investigate the tribological performances of the liner under severe working conditions, such as low velocity and heavy load (110, 179 and 248 MPa) and high velocity and light load (9, 18 and 27 m/min) by utilizing the self-lubricating liner performance assessment tester, and MMU-5G friction and wear tester respectively. The worn surface is characterized using confocal laser scanning microscopy. The tribological results show that the fabric self-lubricating liners with different weft densities share almost the same tribological property variation tendency. Fabric tightness affects the wear rate and the stability of wear resistance of liners under severe working conditions. The overall level of friction coefficient and the wear rate of liners with different weft densities are influenced by the cold flow degree of the polymer. In addition, proper weft density improves the tribological properties of liner and a preferred weft density for the liner under severe working conditions is found to be 300-350 root/10cm

Multi-Source-Data-Oriented Ensemble Learning Based PM 2.5 Concentration Prediction in Shenyang

Shenyang where is surrounded by smokestack industries and depends on coal heating in winter, is a classical one of cities in China northeastern which has suffered from serious air pollution, especially PM2.5. The existing research on machine learning, based on historical air-monitoring data and meteorological data, does neither forecast accurately nor identify key pollutants for PM2.5. This paper presents a multi-source-data-oriented ensemble learning for predicting PM2.5 concentration. The proposed framework incorporates not only air quality data and weather data, but also industrial emission data, especially those of winter heating enterprises, in Shenyang and nearby cities; the model also takes into account location and emission frequency of pollution sources. All these data are entered into an ensemble learning model based on Extreme Gradient Boosting (XGBoost) in order to predict PM2.5 concentration, which not only improves prediction accuracy effectively, but also provides contribution analysis of different pollutants. Experimental results show that the top two factors affecting PM2.5 concentration are: (1) air pollutant emission quantities and (2) distance from pollution sources to air-monitoring stations. According to the importance of these two factors, we refine feature selection and re-train the ensemble learning model and find that the new model performs better on 72% of evaluation indexes

Evaluating Emergency Response Solutions for Sustainable Community Development by Using Fuzzy Multi-Criteria Group Decision Making Approaches: IVDHF-TOPSIS and IVDHF-VIKOR

Emergency management is vital in implementing sustainable community development, for which community planning must include emergency response solutions to potential natural and manmade hazards. To help maintain such solution repository, we investigate effective fuzzy multi-criteria group decision making (FMCGDM) approaches for the complex problems of evaluating alternative emergency response solutions, where weights for decision makers and criteria are unknown due to problem complexity. We employ interval-valued dual hesitant fuzzy (IVDHF) set to address decision hesitancy more effectively. Based on IVDHF assessments, we develop a deviation maximizing model to compute criteria weights and another compatibility maximizing model to calculate weights for decision makers. Then, two ideal-solution-based FMCGDM approaches are proposed: (i) by introducing a synthesized IVDHF group decision matrix into TOPSIS, we develop an IVDHF-TOPSIS approach for fuzzy group settings; (ii) when emphasizing both maximum group utility and minimum individual regret, we extend VIKOR to develop an IVDHF-VIKOR approach, where the derived decision makers’ weights are utilized to obtain group decision matrix and the determined criteria weights are integrated to reflect the relative importance of distances from the compromised ideal solution. Compared with aggregation-operators-based approach, IVDHF-TOPSIS and IVDHF-VIKOR can alleviate information loss and computational complexity. Numerical examples have validated the effectiveness of the proposed approaches

Experimental and Analytical Investigations on Tribological Properties of PTFE/AP Composites

The tribological properties of polytetrafluoroethylene (PTFE)/AP (poly(para-phenyleneterephthalamide) (PPTA) pulp) composites under different test conditions (load: 2N,10N; frequency: 1 Hz, 4 Hz; amplitude: 2 mm, 8 mm) were holistically evaluated. PTFE/AP composites with different AP mass ratios of 3%, 6%, and 12% as a skeleton support material were prepared. The coefficient of friction (COF) and wear rate were determined on a ball-on-disk tribometer. Furthermore, the morphology, element composition, and chemical structure of the transfer membrane were analyzed accordingly. The relationships between load, frequency, amplitude, and tribological properties were further investigated. According to the wear mechanism, AP enables effective improvement in the stiffness and wear resistance, which is also conducive to the formation of transfer films

Wear mechanism of TC4 titanium alloy with TiN coating against self-lubricating fabric

Vapor deposition technology can improve the surface wear resistance of titanium alloys, and prepare lightweight and corrosion-resistant self-lubricating spherical plain bearings made of titanium alloys. However, titanium alloys with hard films can be worn by soft self-lubricating fabrics. This paper focuses on the wear problem of TiN coating on the surfaces of self-lubricating spherical plain bearings based on titanium alloys. Ring-to-plate wear tests were carried out to study the tribological properties of TiN coating on TC4 titanium alloy against self-lubricating fabric under different working conditions (load: 500–2000 N and speed: 100–500 r/min), along with the investigation of the wear mechanism of TiN coating, and the evaluation of applicable working conditions of GE15 type self-lubricating spherical plain bearings through swing tests. The results have revealed that TiN coatings can maintain a certain friction distance without wear. Increasing friction speed and load can make TiN coatings more prone to wear. A thick transfer film can protect the TiN coating from wear. The main wear mechanism is attributed to fatigue wear induced by the repeated formation and peeling of transfer films. The GE15 bearing has achieved a self-lubricating fabric wear of approximately 0.04 mm when the swinging for 500 m (25,000 times) is under a specific condition of 27 kN and 0.2 Hz without damaging the inner ring of the bearing. The bearing is suitable for swing conditions with applied loads below 27 kN. This study provides a fundamental understanding of designing self-lubricating spherical plain bearings made of titanium alloys

Converting brownmillerite to alternate layers of Oxygen-deficient and conductive nano-sheets with enhanced thermoelectric properties

Introducing large oxygen deficiencies while retaining low resistivity is important for enhancing the overall thermoelectric properties in 3d transition-metal oxides. In this study, a new synthesis route to reconstruct the insulating brownmillerite SrCoO2.5 is adapted. Through a step-by-step nano-blocks modification, a series of highly-conductive layered structures is evolved, which are [Sr2O2H2]0.5CoO2, [Sr2O2]0.4CoO2, and [Sr2CoO3]0.57CoO2, while still retaining considerable Seebeck coefficient (˜100 µV K-1). Coexistence of low resistivity and high oxygen deficiency is realized in the latter two polymorphs by forming a majority of sintered oxygen vacancies in the rock-salt layer and a minority of normal oxygen vacancies in the CoO2 layer. A room-temperature in-plane power factor of 3.6 mW K-2 m-1, power output density of 4.5 W m-2 at a temperature difference of 28 K, and an out-of-plane thermal conductivity of 0.33 W K-1 m-1 are obtained in the [Sr2O2]0.4CoO2 thin film that exhibits the highest oxygen deficiency (d = 2.95), which is on par with Bi2Te3, the benchmark. It is pointed out that proper distribution of oxygen vacancy is essential in tailoring the physical and chemical properties of transition-metal oxides. The sintered/normal oxygen vacancy layer model provides guidance to the exploration of materials with both low electric resistivity and thermal conductivity.Peer ReviewedPostprint (author's final draft

Effects of Kevlar® 29 yarn twist on tensile and tribological properties of self-lubricating fabric liner

Yarn twist in textile technology is an important characteristic since it considerably affects the properties of knitted or woven fabrics. Many researchers have investigated the effect of staple-spun yarn twist on the properties of the yarns and fabrics. However, the effects of twist level of Kevlar® 29 filament yarn on the properties of yarn and its resin-impregnated self-lubricating fabric liner are not fully known yet. In this study, we have investigated the effects of Kevlar® 29 twist level on the tensile and tribological properties of the fabric liner (Kevlar® 29/polytetrafluoroethylene fabric-resin composite). Two unexpected findings about the effect of yarn twist have been observed, namely (1) asynchronous twist effect on the yarn’s and the liner’s tensile strength and (2) dissimilar yarn twist effect on the liner’s performance. These findings are mainly attributed to the synergic contributions of the yarn twist and strength and the interaction of the resin with the yarn orientation in the woven fabric structure of the liner

Atomic-scale observation of localized phonons at FeSe/SrTiO3 interface

In single unit-cell FeSe grown on SrTiO3, the superconductivity transition temperature features a significant enhancement. Local phonon modes at the interface associated with electron-phonon coupling may play an important role in the interface-induced enhancement. However, such phonon modes have eluded direct experimental observations. Indeed, the complicated atomic structure of the interface brings challenges to obtain the accurate structure-phonon relation knowledge from either experiment or theory, thus hindering our understanding of the enhancement mechanism. Here, we achieve direct characterizations of atomic structure and phonon modes at the FeSe/SrTiO3 interface with atomically resolved imaging and electron energy loss spectroscopy in a scanning transmission electron microscope. We find several phonon modes highly localized (~1.3 nm) at the unique double layer Ti-O termination at the interface, one of which (~ 83 meV) engages in strong interactions with the electrons in FeSe based on ab initio calculations. The electron-phonon coupling strength for such a localized interface phonon with short-range interactions is comparable to that of Fuchs-Kliewer (FK) phonon mode with long-rang interactions. Thus, our atomic-scale study provides new insights into understanding the origin of superconductivity enhancement at the FeSe/SrTiO3 interface