Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine learning discovery of distinguishing laboratory features for severity classification of COVID‐19 patients

Abstract The exponential spread of COVID‐19 worldwide is evident, with devastating outbreaks primarily in the United States, Spain, Italy, the United Kingdom, France, Germany, Turkey and Russia. As of 1 May 2020, a total of 3,308,386 confirmed cases have been reported worldwide, with an accumulative mortality of 233,093. Due to the complexity and uncertainty of the pathology of COVID‐19, it is not easy for front‐line doctors to categorise severity levels of clinical COVID‐19 that are general and severe/critical cases, with consistency. The more than 300 laboratory features, coupled with underlying disease, all combine to complicate proper and rapid patient diagnosis. However, such screening is necessary for early triage, diagnosis, assignment of appropriate level of care facility, and institution of timely intervention. A machine learning analysis was carried out with confirmed COVID‐19 patient data from 10 January to 18 February 2020, who were admitted to Tongji Hospital, in Wuhan, China. A softmax neural network‐based machine learning model was established to categorise patient severity levels. According to the analysis of 2662 cases using clinical and laboratory data, the present model can be used to reveal the top 30 of more than 300 laboratory features, yielding 86.30% blind test accuracy, 0.8195 F1‐score, and 100% consistency using a two‐way patient classification of severe/critical to general. For severe/critical cases, F1‐score is 0.9081 (i.e. recall is 0.9050, and precision is 0.9113). This model for classification can be accomplished at a mini‐second‐level computational cost (in contrast to minute‐level manual). Based on available COVID‐19 patient diagnosis and therapy, an artificial intelligence model paradigm can help doctors quickly classify patients with a high degree of accuracy and 100% consistency to significantly improve diagnostic and classification efficiency. The discovered top 30 laboratory features can be used for greater differentiation to serve as an essential supplement to current guidelines, thus creating a more comprehensive assessment of COVID‐19 cases during the early stages of infection. Such early differentiation will help the assignment of the appropriate level of care for individual patients.
Responses of nitrite-oxidizing bacteria community to excessive nitrogen application and straw incorporation under intensive cultivation

ABSTRACT N fertilization and straw incorporation often disturb the soil and may affect nitrite oxidation (NO); however, the underlying mechanism remains unclear. Here, we collected soil samples through a 4-year field experiment including no N fertilization, normal N application, excess N application (EN), and EN plus straw incorporation (ES) treatments. We measured the community composition, abundance, and activity of Nitrobacter-like and Nitrospira-like nitrite-oxidizing bacteria (NOB). N application and straw incorporation significantly enhanced potential NO activity (PNO). PNO was affected by the abundance of Nitrobacter but not Nitrospira and the community compositions of both NOB. With increasing N application rate, Nitrobacter abundance increased from 1.0 to 11.8 × 104 copies g−1 dry weight soil, whereas Nitrospira abundance increased initially then subsequently decreased, ranged from 2.1 to 5.2 × 106 copies g−1 dry weight soil. Moreover, N application and straw incorporation markedly affected the NOB community composition. Soil pH and organic C were the key factors shaping the NOB community composition. Overall, N fertilization combined with straw incorporation can affect NO by altering the Nitrobacter abundance and NOB community composition. These findings expand our understanding of mechanisms underlying the effects of straw incorporation on nitrification, particularly under N enrichment.
Finance and Firm Volatility: Evidence from Small Business Lending in China

The online trading platform Alibaba provides financial technology (FinTech) credit for millions of micro, small, and medium-sized enterprises (MSMEs). Using a novel data set of daily sales and an internal credit score threshold that governs the allocation of credit, we apply a fuzzy regression discontinuity design (RDD) to explore the causal effect of credit access on firm volatility. We find that credit access significantly reduces firm sales volatility and that the effect is stronger for firms with fewer alternative sources of financing. We further look at firm exit probability and find that firms with access to FinTech credit are less likely to go bankrupt or exit the business in the future. Additional channel tests reveal that firms with FinTech credit invest more in advertising and product/sector diversification, particularly during business downturns, which serves as effective mechanisms through which credit access reduces firm volatility. Overall, our findings contribute to a better understanding of the role of FinTech credit in MSMEs. This paper was accepted by Haoxiang Zhu, finance.
Transcriptomic analyses reveal molecular mechanisms underlying regulation of floral attributes in Lonicera japonica Thunb.

Background Lonicera Japonica Thunb. is a perennial, semi-evergreen and twining vine in the family of Caprifoliaceae, which is widely cultivated in Asia. Thus far, L. japonica is often used to treat some human diseases including COVID-19, H1N1 influenza and hand-foot-and-mouth diseases, however, the regulatory mechanism of intrinsic physiological processes during different floral developmental stages of L. japonica remain largely unknown. Results The complete transcriptome of L. japonica was de novo-assembled and annotated, generating a total of 195850 unigenes, of which 84657 could be functionally annotated. 70 candidate genes involved in flowering transition were identified and the flowering regulatory network of five pathways was constructed in L. japonica. The mRNA transcripts of AGL24 and SOC1 exhibited a downward trend during flowering transition and followed by a gradual increase during the flower development. The transcripts of AP1 was only detected during the floral development, whereas the transcript level of FLC was high during the vegetative stages. The expression profiles of AGL24, SOC1, AP1 and FLC genes indicate that these key integrators might play the essential and evolutionarily conserved roles in control of flowering switch across the plant kingdom. We also identified 54 L. japonica genes encoding enzymes involved in terpenoid biosynthesis pathway. Most highly expressed genes centered on the MEP pathway, suggesting that this plastid pathway might represent the major pathway for terpenoid biosynthesis in L. japonica. In addition, 33 and 31 key genes encoding enzymes involved in the carotenogenesis and anthocyanin biosynthesis pathway were identified, respectively. PSY transcripts gradually increased during the flower development, supporting its role as the first rate-limiting enzyme in carotenoid skeleton production. The expression level of most anthocyanin biosynthetic genes was dramatically decreased during the flower developmental stages, consistent with the decline in the contents of anthocyanin. Conclusion These results identified a large number of potential key regulators controlling flowering time, flower color and floral scent formation in L. japonica, which improves our understanding of the molecular mechanisms underlying the flower traits and flower metabolism, as well as sets the groundwork for quality improvement and molecular breeding of L. japonica.
Protocol for a Systematic Review of the Effectiveness of Provider-targeted Interventions to Improve Opioid Prescribing in Primary Care

Background: Improving primary care opioid prescribing is a public health priority in many western nations. Governments, policymakers and key stakeholders are intervening on multiple levels to address patient, prescriber and systems factors contributing to opioid over-prescription in primary care. Many opioid prescribing interventions specifically target primary care providers (PCPs); however, the overall effectiveness of these interventions is not known. Identifying effective components of PCP-targeted behaviour change interventions may help inform scalability and translation of prescribing interventions across countries and varying primary healthcare settings. The aim of this systematic review is to assess the effectiveness of provider-targeted interventions to improve opioid prescribing in primary care. This protocol reports the methods of the proposed narrative synthesis review that will be guided by the Theoretical Domains Framework (TDF). Methods: The study will follow Cochrane methods for conducting a narrative synthesis. Reporting is compliant with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocols. The review will conduct searches in PubMed, EMBASE, PsychInfo, CINAHL, and the Cochrane Library databases for studies published in the English language from 2010 onwards. Reference lists of accepted articles will be also screened for additional studies meeting inclusion. Any opioid prescribing behaviour will be measured as an outcome. Intervention components will be mapped to domains of the TDF. No geographic limits will be applied. All stages of screening and data extraction will involve a dual review with gold standard adjudication. The Cochrane Risk of Bias tool will be used to evaluate quality and risk. Discussion: This review is being conducted in strict adherence to Cochrane principles. The protocol was submitted for registration to Prospero prior to publication for transparency and to avoid duplication of research. Formal ethics approval is not required for this research. The findings of this review will inform the delivery and implementation of PCP targeted opioid prescribing interventions. Findings will be disseminated to a wide range of stakeholders involved in quality improvement, prescribing interventions, education and training; professional groups, policymakers, researchers and PCPs.Systematic review registration: Submitted to Prospero 22 December 2020; pending registration
Data-to-text Generation via Planning

Planning based text generation from structural data is an emerging approach that manages to plan for “what to say. ” Existing methods can not dynamically adjust the planning, because they generate complete plans statically without considering the result of surface realization. To address this issue, we propose a model that conducts dynamic text planning and surface realization alternately. In each sentence’s generation, our model first plans the records according to the generated text and the plan history, then realizes the sentence conditioned on the corresponding plan. Experimental results demonstrate that our model performs better on both text planning and text generation. Our model with the dynamic planner achieves impressive results on the E2E dataset.
Optical and photoelectrochemical properties of nitrogen-doped a-SiC thin films deposited by reactive sputtering method at room temperature

ABSTRACT This paper studies optical properties of Nitrogen-doped a-SiC amorphous, commonly called, silicon carbonitride (SiCN) thin films deposited on polished and textured silicon wafers by reactive RF magnetron sputtering technique. Different samples were made at room temperature by sputtering a silicon carbide (SiC) target in argon and nitrogen mixture environment. The FTIR measurement confirms the presence of Si-C and Si-N bonds. The peaks corresponding to Si-C are 611, 653, 669, 740, 834 cm−1 and the peaks corresponding to Si-N are in the range ~870–950 cm−1. The optical properties were achieved from reflectivity spectra by UV-visible spectroscopy. The refractive index (n < 2.5) and the optical gap (Eg>2.2 eV) of the deposited films depended on the used argon and nitrogen flows. The electrochemical properties of amorphous p-type a-SiC/N thin films on p-Si substrate were investigated as electrodes in H2SO4 aqueous solutions in the dark and under the white light illumination. The SiCN films show a good suitability for the antireflective coating application and can be applied to fabricate high efficient and stable SiCN catalysed n + p-Si photocathode with pyramid surface for PEC CO2 conversion.
A Wind Speed Prediction Method Based on Improved Empirical Mode Decomposition and Support Vector Machine

Based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and bat algorithm (BA) to optimize the support vector machine, this paper proposed a combined model for short-term wind speed forecasting to predict the wind speed more accurately. Firstly, CEEMDAN was used to decompose the original wind speed time series into a series of subsequences with different frequencies. Secondly, the decomposed subsequences were forecasted by combined model of BA-SVM. Finally, the wind speed forecasting results was achieved by superposing each predicted subsequence. The simulation results suggest that the model improves the prediction accuracy and reduces the error.
Synthèse et structure électronique de phases MAX et MXènes

Les objectifs de ce travail sont d'une part d'etudier la structure electronique de carbures de titane bidimensionnels appartenant a la famille des MXenes, et d'autre part de synthetiser des films minces pour caracteriser certaines de leurs proprietes. L'etude de la structure electronique a ete realisee sur le systeme Ti3C2T2 avec une attention particuliere portee aux groupements de surface T (T=OH, F ou O) en comparant les resultats obtenus par spectroscopie de perte d'energie des electrons a ceux des calculs ab initio. Cette etude, portee a la fois sur les excitations du gaz d'electrons de valence et des electrons de coeur, a permis de mettre en evidence la localisation des groupements de surface, ainsi que leur influence sur la structure electronique du MXene. La comparaison des simulations et des spectres experimentaux a egalement permis de caracteriser la nature chimique des groupements de surface. Enfin, la limite d'une telle etude est discutee en considerant les phenomenes d'irradiation responsables de la perte d'atomes d'hydrogene. La synthese d'echantillons modeles necessite la synthese prealable d'un film mince de phase MAX precurseur pour le MXene : nous avons choisi la phase Ti2AlC, precurseur de Ti2C. La synthese de Ti2AlC a ete realisee par recuit ex-situ de systemes multicouches deposes a temperature ambiante. Les films ont ete caracterises par diffraction des rayons X et microscopie electronique en transmission. Au-dela de l'obtention d'un film mince de Ti2AlC texture, cette etude a permis de montrer que la phase recherchee etait obtenue via des mecanismes d'interdiffusions induisant la formation d'une solution solide metastable vers 400°C qui se transforme en phase MAX vers 600°C. Enfin, l'application de ce procede a la phase V2AlC a permis de montrer l'importance de l'orientation de la phase initiale pour l'obtention d'un film mince texture.
Successful lmplementation of lnformation Strategies to Strengthen lmmunity in Air Pollution Environment

This study is to successfully implement information strategies to strengthen immunity in air pollution environment. The data were collected from February 5 to April 16, 2019 for 128 people who visited the general hospital’s health examination center in the metropolitan area. The data were collected from February 5 to April 16, 2019 for 128 people who visited the health examination center in the general hospital in the metropolitan area. The application of information system to improve immunity in air pollution environment was analyzed as t-test. The results of the study are as follows. Firstly, the information group drinking enough water every day was significantly higher than the non-information group drinking insufficiently (t=-1.64, p=.000). Secondly, the quality of sleep has continued to improve significantly since seven days before the application of the information system(p<.05). Therefore, it is expected to contribute to the prevention of diseases and the improvement of quality of life by strengthening immunity in the air pollution environment.
Bioactive compound content and antioxidant activities of analog rice enriched with the germinated of white corn (zea mays) and the germinated of mung bean (vigna radiata)

The research aimed to know bio-active compounds’ content and antioxidant activity of rice analog based on germinated white corn (Zea mays), germinated mung bean (Vigna radiata) and white sweet potatoes. There were several stages: first, the formulation of analog rice—the second analyzes of total phenol and flavonoids content. The third is the analysis of antioxidant activity done by DPPH, FTC, and TBA methods. Results showed that formulation I TPC levels are 385.00 ± 0.04 (mgGAE/100g), TFC 267.60 ± 0.42 (mgQCE/100g). Formulation II TPC levels are 379.20 ± 0.85 (mgGAE/100g), TFC 235.40 ± 0.92 (mgQCE/100g). Formulation III TPC levels are 346.50 ± 0.85 (mgGAE/100g), TFC 227.00 ± 0.42 (mgQCE/100g). Antioxidant activity formulation I with DPPH method: 67.71 ± 0.20%; The percentage inhibitory with the FTC 69.10 ± 1.01%, TBA 65.28 ± 0.28%. Antioxidant activity formulation II with DPPH method: 66.57 ± 0.20%; The percentage inhibitory with the FTC 60.63 ± 0.81%, TBA method 64.42 ± 0.58%. Antioxidant activity formulation III with DPPH method: 63.57 ± 0.20%; The percentage inhibitory with the FTC 45.41 ± 0.30%, TBA 63.21 ± 0.58%. There is a significant and positive correlation between bioactive compounds with three methods of antioxidant activity used.
Ego‐lane index‐aware vehicular localisation using the DeepRoad Network for urban environments

Accurate real-time localisation is crucial for various autonomous driving applications. Numerous methods for localization, combining various kinds of input such as data from environmental sensors, inertial measurement units, and the Global Positioning System, have been proposed. Given the present state of affairs with regards to map compactness and sensor affordability, lane map-matching-based methods with cameras used as environmental sensors have been widely proposed. In previous methods, however, lanes detected by cameras could falsely correspond to other lanes in a map. This would result in inaccuracies such as a two-lane or three-lane deviation from the actual pose. This paper proposes a localisation method integrating the ego-lane index to avoid lane deviations during lane map matching. A novel ego-lane index identiﬁcation algorithm and methodology to integrate the ego-lane index information into the lane-based map-matching function is presented. It is demonstrated that incorporating ego-lane index information improves the accuracy of map-matching localisation. The efﬁcacy of our approach in diverse environments, including complex urban scenarios, was successfully demonstrated.
The Relationship between Religiosity and Subjective Well-Being in Takmir Who Works as a Fisherman

This study aims to determine the relationship between religiosity and subjective well-being in Takmir mosque who works as a fisherman. The number of samples in this study was 40 fishermen in Kupang City who were Muslim. The data collection method was carried out using a questionnaire divided into three scales, namely the religiosity scale adapted from Satriani, (2011), and the two subjective well-being scales of the PANAS (Positive Affect and Negative Affect Scale) expressed by Watson, Clark, and Tellegen (1988) and SWLS (Satisfaction with Life Scale) based on the theory stated by Diener (1999). The results showed a significant relationship between religiosity and subjective well-being at the mosque takmir who works as fishermen where the Pearson Correlation value = 0.610 with a significance value of 0,000 (ƿ<0.05). This study aims to provide a new understanding of increasing welfare by increasing the religiosity value of the individual.
An online survey of equestrian headcollar use and safety

Summary Background: Headcollars (halters, US) are one of the most commonly used pieces of equestrian ‘ tack ’ . Despite this, there appears to be minimal information on their use, or more importantly, risk factors for injury of horses/handlers. Objective: To explore headcollar use and safety in equestrians. Study design: Quantitative cross-sectional survey. Methods: An online survey (19 questions) exploring headcollar use and safety was disseminated through equestrian social media. Frequency analysis and multivariable modelling identi ﬁ ed how headcollar type was linked to use and injury risk. Results: Most respondents (88%; n = 4786) used headcollars multiple times daily but for short time periods (66%, n = 3388, < 30 min). A horse being injured as a result of wearing a headcollar was reported by 1615 (31%) respondents with 15% of incidents also injuring a person. Fractures (horses) occurred in 134 incidents, and 167 equine fatalities were reported. Across all headcollar types, the odds of injury risk increased by 1.7 times (con ﬁ dence intervals (CI): 1.07 – < using a headcollar when mucking out. During travelling, headcollar reduced the odds of risk of injury by times (CI: – odds of injury when using leather ratio (OR): CI: – < or synthetic (OR: 0.8, CI: 0.58 – 0.85, P < 0.0001) safety headcollars compared with standard headcollars of the same material. Thematic analysis identi ﬁ ed three key themes: (1) need for increased education: ﬁ t, safety features and basic horse handling, (2) ‘ safer ’ leather headcollars, and (3) increased safety focus required. Main limitations: Data were self-reported and may be subject to memory recall errors; online surveys are subject to self-selection bias. Conclusions: Increased user knowledge of risk factors for headcollar injury, combined with standardised guidance on how to correctly ﬁ t and use headcollars, would be bene ﬁ cial to reduce injury risk.
Investigation of continuous and discontinuous contact cases in the contact mechanics of graded materials using analytical method and FEM

The aim of this paper was to examine the continuous and discontinuous contact problems between the functionally graded (FG) layer pressed with a uniformly distributed load and homogeneous half plane using an analytical method and FEM. The FG layer is made of non-homogeneous material with an isotropic stress–strain law with exponentially varying properties. It is assumed that the contact at the FG layer-half plane interface is frictionless, and only the normal tractions can be transmitted along the contacted regions. The body force of the FG layer is considered in the study. The FG layer was positioned on the homogeneous half plane without any bonds. Thus, if the external load was smaller than a certain critical value, the contact between the FG layer and half plane would be continuous. However, when the external load exceeded the critical value, there was a separation between the FG layer and half plane on the finite region, as discontinuous contact. Therefore, there have been some steps taken in this study. Firstly, an analytical solution for continuous and discontinuous contact cases of the problem has been realized using the theory of elasticity and Fourier integral transform techniques. Then, the problem modeled and twodimensional analysis was carried out by using ANSYS package program based on FEM. Numerical results for initial separation distance and contact stress distributions between the FG layer and homogeneous half plane for continuous contact case; the start and end points of separation and contact stress distributions between the FG layer and homogeneous half plane for discontinuous contact case were provided for various dimensionless quantities including material inhomogeneity, distributed load width, the shear module ratio and load factor for both methods. The results obtained using FEM were compared with the results found using analytical formulation. It was found that the results obtained from analytical formulation were in perfect agreement with the FEM study.