Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Optimal Allocation of Resources and Improvement of Total Factor Productivity—Taking Shaanxi as an Example

Taking Shaanxi province as an example, the panel data of 10 cities in Shaanxi province from 2005 to 2016 were used to explore the influence of factor resource allocation on total factor productivity. The results show that the allocation of factor resources has a positive effect on total factor productivity, that is, the better the allocation of resources, the higher the total factor productivity. The results of regional regression showed that the rationalization of resource allocation in Guanzhong and Northern Shaanxi significantly promoted the local total factor productivity, and the promotion effect of resource allocation in northern Shaanxi was greater than that in Guanzhong.
Detection of low-magnetic fields by rubidium (87Rb) vapor cell

This paper describes the work carried out to assess the use of a quartz reference rubidium (87Rb) vapor cell for non-invasively magnetoencephalography, avoiding cryogenically cooled sensors as the Superconducting Quantum Interference Devices (SQUIDs). An experimental setup based on a cylindrical glass vapor cell of 87Rb (l = 75 mm, d =19 mm) was developed. The 87Rb cell was heated to around 75°C and it was optically pumped with polarized light (range 750-850 nm), tuned to the D1 transition of rubidium, for spin-polarization of the atoms, and the intensity of the light transmitted through the cell was detected using a photodiode. Without magnetic field, the photodiode current is maximized but when a small transverse magnetic field is present a measurable drop in light transmission occurs. A Magnetic Shielded Box (MSB) made by a nickel-iron ferromagnetic alloy, was used for nulling background magnetic fields and the transmittance light versus transverse magnetic field intensity (100-1000 nT) was measured.
Transcriptome Analysis of Acer truncatum Seeds Reveals Candidate Genes Related to Oil Biosynthesis and Fatty Acid Metabolism

Acer truncatum seeds are an excellent source of beneficial natural compounds, including high levels of unsaturated fatty acids (UFAs), that promote health. Recently, A. truncatum has emerged as an oil crop. Therefore, the transcriptomes of A. truncatum seeds at 70, 85, 100, 115, 145, 180 days after flowering (DAF) were analyzed to gain a better understanding of the transcriptional and translational regulation of seed development and oil biosynthesis. A total of 28,438 genes were identified, and 3069/2636, 3288/3438, 1319/2750, and 5724/5815 upregulated/downregulated genes were identified when comparing different samples with 85 DAF seeds. Sixteen lipid metabolism pathways with 754 differentially expressed genes (DEGs) were identified, including 34 DEGs associated with UFA biosynthesis. A phylogenetic analysis revealed that six putative fatty acid desaturase (FAD) genes clustered into five FAD groups. A quantitative real-time polymerase chain reaction analysis indicated that the temporal expression patterns of oil biosynthesis genes and transcription factors were largely similar to the RNA sequencing results. The results of this study will enhance the current understanding of oil metabolism in A. truncatum seeds and allow new methods of improving oil quality and seed yield in the future.
Modifying the Mini-Cog to Screen for Cognitive Impairment in Nonliterate Individuals

Objectives The Mini-Cog, a rapid, valid, and reliable screening tool for cognitive impairment, consists of 3-word recall and an executive clock drawing test (CDT). However, CDT requires at least basic literacy and cultural exposure to analog clocks, conditions not met in many population groups around the world. We developed a modification of the Mini-Cog (MMC) for use with nonliterate and literate individuals. Methods Participants were adults (≥60 years) with no neurological diagnosis, with known cognitive impairment due to stroke, Parkinsonism, traumatic brain injury, or Alzheimer's disease, and whose family members were able to read and write. We replaced the CDT with two tasks of everyday life: a serial subtraction task or a multistep performance task. Family members rated the acceptability and feasibility of the Mini-Cog versions using a 6-point scale and completed a proxy-rated cognitive staging tool, the Dementia Severity Rating Scale (DSRS). Spearman's rho, Mann-Whitney U, and chi-square tests were used to evaluate group differences and associations between measures. Results Data were collected from 63 participants (75% ≥ 60 years, 67% nonliterate). Literacy was associated with CDT (chi-square strength 0.9, p < 0.001). Both MMC versions correlated with DSRS in healthy adults and patients (rho 0.6-0.7, p < 0.05). In literate individuals, the acceptability and feasibility of CDT and both alternate distractors were similarly high (5/6). Conclusions Two alternate distractor tasks may successfully replace CDT in the Mini-Cog. The MMC versions are promising and deserve further study as screening tools for cognitive impairment in larger and more fully characterized samples.
MobLen Model for Enhancing Scientific Creativity of Physics Students: An Alternative in the Covid-19 Pandemic

The development of scientific creativity (SC) is critical in physics education because students must have the improved-scientific-creativity to become superior graduates, including prospective physics teachers. Many prospective physics teachers lack scientific creativity. The focus of this research was to analyse the effectiveness of the MobLen model in increasing the scientific creativity of future physics teachers as an alternative to online learning models in the COVID-19 pandemic. This research used a pre-experiment design with one group pre-test and post-test of 62 prospective physics teachers. The data was collected using a scientific creativity test, then analysed using inferential statically with the Paired Sample Test and N-gain. The results showed that the MobLen model proved effective in increasing the scientific creativity of prospective physics teachers. This research implies that the MobLen learning model can increase the scientific creativity of prospective physics teachers as an alternative to online learning in the COVID-19 pandemic.
Isolation and Identification of Effective Microorganisms from Water Hyacinth Biofertilizer

The use of microorganisms to promote growth and increase crop production has begun to be studied. Microorganisms that isolated from biofertilizers vary according to the source of organic matter. One of the biofertilizer quality determinants is the type and number of populations of microorganisms. This study aims to know is the type and abundance of microorganisms, as well as nutrient content in water hyacinth biofertilizers. The experiment was conducted at the Greenhouse and Laboratory of Food Crops Cultivation, Payakumbuh State Agricultural Polytechnic, Limapuluh Kota Regency, West Sumatra from March to July 2019. The experimental stages included (1) Manufacture water hyacinth biofertilizers, the experiments using Completely Randomized Design (CRD) with four measurements of water hyacinth treatment in biofertilizer, A = 25%, B = 50%, C = 75%, and D = 100% and five replications, (2) Isolation of microorganisms from biofertilizers using pure plate and streak plate methods. Eleven bacterial species and two fungal species were identified using molecular analysis based on 16S rRNA gene fragments. Effective microorganisms that play a role in the degradation of biofertilizers are Pseudomonas aeruginosa, Bacillus subtilis, Trichoderma asperellum, and Trichoderma harzianum. Biofertilizers contain C-organic 3.61-3.92%, N 0.166-0.278%, C/N 14,10-21,75, P2O5 0.347-0.729%, K2O 1.422-2.090%, and Ca 0.140-0.259%.
Research on Advanced Power System Analysis and Control Based on Big Data Technology

The continuous development of big data technology has brought many new ideas and challenges to power system analysis and control. With the development of distributed power sources, energy storage, monitoring, and protection devices, the traditional distribution network has gradually evolved into much Active distribution networks with control ability. At present, the power quality of the power system is a hot issue in power system research. There are many types of power quality disturbances, mainly including single type and compound type disturbances. The thesis first uses Matlab to model and simulate the power quality disturbance signal and then obtains a complex number matrix through S transform, then calculates its modulus, and extracts the corresponding characteristic parameters to form the characteristic vector. Secondly, the thesis uses a simple and efficient decision tree to correctly classify and identify power quality disturbance signals. Finally, the thesis’s simulation analysis results show that this research method combining S transform and decision tree has high recognition accuracy and strong anti-noise ability, which is a very suitable method.
A review on how a Perpetual Motion Machine generates electrical power

Electrical energy demand is increasing in accordance with rapid growth of the human population. Since fossil fuels is the most widely used energy source, thus it is depleting very fast. Alternative energy source is urgently needed to replace the use of conventional energy sources. Perpetual Motion Machine (PMM) which can be applied to produce electricity, may be an alternative solution for the problem the world is facing today. The machine is designed to generate power from repulsive forces of permanent magnet without utilizing external sources. Some researches had conducted experiments and Neodymium magnet is most used in the project due to its strong magnetic field. The device is mainly built using a permanent magnet, a rotating wheel and a generator. This paper reviews some aspects on how A Perpetual Motion Machine (PMM) generates electrical power. The aim of the paper is to provide a summary of the topic and its opportunities in further enhancements for better results. The study found that the concept is very effective, ecofriendly and less space needed. However, a larger scale development of the machine along with proper magnet and gear arrangement is currently needed for a better performance and application.
Empirical Analysis on the Impact of Energy Output and Industrial Structure Adjustment on Economic Growth in Shanxi Province, China : from the Perspective of SVAR

Based on the time series data of Shanxi Province from 1989 to 2018, this paper constructs the SVAR model (structural Vector autoregression). Using impulse response function, variance decomposition and other tools, this paper makes an empirical study on the relationship between economic growth, industrial structure adjustment and energy output in Shanxi Province. The correlation and contribution rate among energy output, industrial structure adjustment and economic growth are evaluated dynamically. The main conclusions of this paper are as follows: there is a long-term stable relationship among the economic growth, the proportion of the gross output of the secondary industry and the output of the primary energy; when the proportion of the Gross Domestic Product of the secondary industry and the output of the primary energy have a dynamic impact on economic growth, their responses are not the same; by comparison, the impact of industrial restructuring on the economic growth of primary energy is greater than the pulling effect of output.
Numerical and experimental investigation on the performance of hybrid porous gas journal bearings

As the progress of the high‐speed performance requirement for porous gas journal bearings continuing, the aerodynamic effect, which plays a key role in the state of lubrication, causes the porous gas journal bearings being gradually to be used as hybrid bearings. This paper firstly presents a theoretical analysis on the lubrication mechanism of the hybrid bearings. The gas flow in the porous and clearance is modelled by using the mass continuity equation. Two experimental test rigs are designed to systematically test the static and dynamic characteristics of the hybrid bearings. The numerical results are corroborated by the experimental data. Results show that there is optimal clearance for hybrid bearings to obtain maximum load capacity. The load capacity of the hybrid bearings is increased by the aerodynamic effect to be higher than that of pure aerostatic bearings especially at higher rotational speed and larger eccentric ratio. However, due to the occurrence of the aerodynamic effect, the hybrid bearings show clear cross‐coupling dynamic coefficients, which may lead to bearing instability. It is interesting to note that the direct dynamic stiffness and damping coefficients are both influenced by the aerodynamic and aerostatic effects. Higher rotational speed and external supply pressure will result in higher direct dynamic coefficients.
The Fundamentals of Gamut Mapping: A Survey

This article aims to give a survey of the fundamentals of gamut mapping by describing the cross-media color reproduction context in which it occurs, by giving definitions of terms used in conjunction with it, by describing its aims and by giving an overview of parameters that influence it. These parameters are primarily the choice of color space used, the category into which a gamut mapping algorithm belongs and whether the approach is image or medium dependent. A succinct summary is then given of the principal trends in gamut mapping studies conducted to date.
Overview of the development of speaker recognition

Speaker recognition is a technology that recognizes a person’s identity through a person’s voice. Speaker recognition is one of the important research topics in the field of biometrics. This article first introduces the background and research significance of speaker recognition; secondly, it briefly introduces speaker recognition technology; again introduces the method research used in speaker recognition; and finally analyzes the research difficulties and challenges of speaker recognition.
Prevalence of Staphylococcus aureus Nasal Carriage and Methicillin-resistant S. aureus Among Medical Students: A Systematic Review and Meta-analysis

Context: Evaluating the prevalence of Staphylococcus aureus nasal carriage and methicillin-resistant S. aureus (MRSA) that are sources of nosocomial infection among medical students. Evidence Acquisition: Electronic databases were searched by preferred subject headings and free-text keywords. After omitting duplicates, retrieved articles were screened by two independent reviewers in a three-step process based on inclusion criteria. Then, reviewers critically appraised the selected studies by JBI checklists and extracted the required data. Finally, the pooled prevalence rates of S. aureus nasal carriage and MRSA were meta-analyzed by Stata V.16 software. The heterogeneity of included studies was calculated by I2 and chi-square. Subgroup analysis was carried out according to study designs, as well as the continent origin of clinical and preclinical students. Results: Of 858 retrieved studies, 15 were included in the meta-analysis. The results showed that the pooled prevalence of nasal S. aureus carriage was 28% [prevalence rate: 0.028, 95% CI: 0.21 - 0.34, P < 0.001, I2: 96.40%, chi2: 360.98 (df = 14)]. The prevalence of S. aureus among clinical students was 33% (pooled prevalence rate: 0.33, 95% CI: 0.18 - 0.47) whereas, in preclinical students, it was 25% (pooled prevalence rate: 0.25, 95% CI: 0.23 - 0.28). Also, in a subgroup analysis of continents, Australia (Oceania) had the highest prevalence rate. According to an evaluation of publication bias, the distribution of studies was very high. Moreover, pooled MRSA prevalence among medical students was 2% (prevalence rate: 0.02 95% CI: 0.01 - 0.03, P < 0.001). Conclusions: In this meta-analysis, S. aureus and MRSA prevalence rates among medical students were estimated at 28% and 2%, respectively. More attention should be given to the prevention of MRSA colonization and screening strategies among medical students across the world.
Sedimentation of psbA Gene‐Containing Cyanophages, Cyanobacteria, and Eukaryotes in Marine and Estuarine Sediments

The transport of planktonic microbes from the upper ocean to sediments plays an important role in marine ecology and biogeochemistry (e.g., the downward transport of organic matter). In order to have a better understanding of this important process, we investigated the diversity of allochthonous cyanophages, cyanobacteria, and eukaryotic algae in the sediments from the Pearl River Estuary and South China Sea based on psbA, the gene encoding the D1 protein involved in photosynthesis. The psbA is prevalent and diverse in sediments regardless of water depth, revealing that the vertical export of psbA gene‐containing planktonic microbes provide an important source of sedimental microbes. Phylogenetic analysis showed the presence of Synechococcus, Synechococcus myovirus, Synechococcus podovirus, Prochlorococcus, Prochlorococcus myovirus, Prochlorococcus podovirus, and eukaryotic algae groups in the sediments. More than 80% of psbA amplicons belong to cyanophages, suggesting the potential prevalent downward transport of cyanophages from the photic zone to the seafloor. Diatoms Pseudosolenia calcar‐avis and Opephora were dominant in some sediment samples, different from planktonic community in the photic zones, indicating a potentially different vertical export efficiency among phytoplankton. The principal coordinate analysis indicated that psbA gene‐containing microbial community varied in estuarine, continental shelf and deep sea sediments. This study investigated the diversity of psbA gene‐containing microorganisms in marine sediments and could facilitate the evaluation of the output of photosynthetic organic carbon.
2SPD-031 Subgroup analysis about efficacy of early use of remdesivir in COVID-19

Background and importanceA greater benefit was suggested with early treatment with remdesivir against COVID-19 Aim and objectivesTo develop a systematic review and methodological interpretation of subgroup analyses according to timing of use of remdesivir in COVID-19 Material and methodsA bibliographic review in MEDLINE was conducted up to 10 October 2020 The ‘Clinical Queries/Narrow’ tool was used with the search strategy: ((Therapy/Narrow[filter]) AND (remdesivir AND COVID)) Randomised clinical trials (RCTs) with subset analysis about early and late use of remdesivir (≤10 vs >10 days from symptom onset, or ≤9 vs >9 days) were selected The rest of the studies were excluded All endpoints with subgroup analysis regarding timing of remdesivir use were assessed Two methodologies were applied The first considered statistical interaction among subsets, prespecification, biological plausibility and consistency of the subgroup analyses of similar RCTs 1 The second methodology was a validated tool with preliminary questions to discard subset analysis without minimal relevance, and a checklist 2 This checklist assigned a score related to a recommendation for applicability of subgroup analysis in clinical practice Results20 results were found after review;16 studies were excluded because they were not RCTs and 1 study had no efficacy evaluation of remdesivir Therefore, three RCTs were selected Endpoints considered were: time to clinical improvement, mortality, viral load, and clinical status at days 11 and 15 According to the first methodology, no statistical interaction was observed in the outcomes of the RCTs Prespecification was established in time to clinical improvement, and clinical status at day 15 of an RCT Biological plausibility was described in the subset analysis of each endpoint of the RCTs No consistency of subgroup analyses were found The second methodology discarded the applicability of the subset analysis through preliminary questions in two RCTs because of the absence of minimal relevance For the third RCT, ‘null’ recommendation (score −3 points) of clinical applicability was reached for clinical status at day 11 Conclusion and relevanceNo differences were found between early and late use of remdesivir in COVID-19 We developed the first study with a systematic review and methodology about subgroup analysis of timing of use of remdesivir References and/or acknowledgementsSun X, et al How to use a subgroup analysis: users’ guide to the medical literature JAMA 2014;311:405–11 Gil-Sierra MD, et al Checklist for clinical applicability of subgroup analysis J Clin Pharm Ther 2020;45:530–8 Conflict of interestNo conflict of interest
A Method for Multi-objective Optimization and Application in Automobile Impact

A method is proposed for constrained multi-objective optimization problems, which is based on Newton method and the linear weighted sum method. The automobile impact problem is studied in this paper. The multi-objective optimization model of the impact problem would be established. Then, an improved design of front rail is obtained by the algorithm proposed.
Cooperative control of large flexible space structure by two planar robots

This study discusses a cooperative control problem of a ﬂexible beam by two planar space robots. The goal is to control the position and orientation of the ﬂexible structure and robots, and to suppress the vibration of the ﬂexible structure. To solve this problem, a boundary controller based on a dynamic model represented by a hybrid PDE-ODE model is presented. In particular, a boundary controller using the Lyapunov method is derived, and it is showed that the system becomes Lyapunov stable and that the system in the neighbourhood of the desired conﬁguration becomes asymptotically stable. As the system has an actuation redundancy, distribute control inputs among actuators considering each actuator’s performance can be distributed. Finally, several numerical simulations are carried out to investigate the validity of the proposed boundary controller.
Filling Missing Value Method for Power Quality Data Based on Correlation Analysis

A large number of monitoring indicators own strong correlation among them which help to better fill missing values in these sensor data. In this study, we propose an electric power quality data filling method based on correlation analysis. Firstly, normalized mutual information method is applied to deal with nonlinear correlation which makes up for the deficiency that the traditional Pearson correlation coefficient. Additionally, the measurement of correlation is calculated to obtain the closely correlated indicators. This study utilizes the regression model to build the strong regression model. Experimental results show that the approach can effectively improve the accuracy of filling, reduce the filling error, and improve the quality of data.