Miracle-dz/UniFAR-FTUs huggingface dataset:
Reply on RC3

The authors showed the size-fractioned phytoplankton community growth and grazing based on the result from dilution experiments. The authors also explained the biophysical factors which controlled the growth and grazing rates of micro-, nanoand pico-phytoplankton. In general, this manuscript is novelty and a board international interest. The experiment was well designed and conducted, the data interpretation was sufficient and accurate. However, the statistical analysis and some data interpretation should be revised and improved.
A Combination of Lexicon-Based and Classified-Based methods for Sentiment Classification based on Bert

Sentiment classification is a crucial problem in natural language processing and is essential to understand user opinions. There are two main approaches to solve this problem, one is the classified-based method, the other is the lexicon-based method; however, both methods perform not well on the long-sequence methods, and each method has its advantages and disadvantages. This paper introduced a new method called Lexiconed BERT, which cream off the best and filter out the impurities from the above two methods. The evaluation shows that our model achieves excellent results in the long sequence sentence and reduce resource consumption significantly.
Pl/sql design to determine the training data pattern on the Adaline neural network

Inventories of goods in business activities greatly affect the smooth running of business activities. The durian fruit sales business is also affected by inventory. Durian fruit sellers must be able to predict the needs of durian fruit customers so that sales business activities run stable. For sellers with low durian fruit sales, they will have no difficulty predicting demand for durian fruit. But for sellers of durian fruit in large quantities, it will take a long time and is prone to errors. An error in the prediction causes the sales business to lose. It takes high accuracy and fast time to make predictions. Adaline neural network has been proven to be able to solve prediction problems precisely. Adaline network performance is affected by training data. Durian fruit sales data is used as network training data to improve network performance. The focus of this research is the design of the pl/sql database to determine the training data input pattern in the android application to predict the number of durian fruit customer needs. Types of pl/sql used in this study are procedures and functions. Meanwhile, the method used to design pl/sql is an extreme method.
Various Types of Nitrogen and Light Levels on Brassica chinensis Yield and Quality Parameters under Water Stress

ABSTRACT To evaluate the effect of nitrogen, light, and water interaction on the biomass of cabbage the experiment was performed at three light intensities, three water stresses, and four nitrogen levels for four replicates using hydroponic technique in green house. The results showed that the biomass of the edible parts of cabbage at H1L3 was significantly higher than in weak light intensity and water stress treatments under the same nitrogen supply. An optimal yield was reached at 60% of the traditional nitrogen application in the presence of adequate high light intensity and normal water content. Decreased nitrate reductase and low capacity of nitrogen assimilation were observed when the nitrate–nitrogen (NO3-N) levels were increased from N2 to N4 with normal water content. Under severe water stress (H3), the plants have a high content of soluble sugars and a low content of amino acids in low NO3− levels (N1 to N3). Modulating the relationship between water stresses, light intensity, and nitrogen supply levels could increase the biomass and may promote the quality of a certain plant.
Biorthogonal Wavelet on a Logarithm Curve 
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According to the length-preserving projection and Euler discretization method, biorthogonal wavelet function on a smooth curve C is constructed in this paper, such as a logarithm curve. The properties of biorthogonal wavelet filters on a smooth curve C are discussed, such as induced refinable equation and symmetry. Moreover, an example is given for discussing the biorthogonal scaling function and its dual on a logarithm curve C . Finally, a numerical application is given for dealing with financial data.
Psychosocial Aspects of Deliberate Physical Suicide Attempts by Children and Adolescents

Suicide is the second most common cause of death among young people in Lithuania. This study aimed to evaluate circumstance, and conditions possibly related to suicide attempt in adolescents. Study was performed at the tertiary Children’s Hospital. Medical documentation of the suicide attempts from January 2011 to April 2018 was analyzed. There were 102 cases included in the study: 83.8% female and 16.2% male patients (average age of 15.02 ± 1.9); 40.6% of patients lived in divorced families, 17.7% in orphanages, 4.2% in foster care; 36.4% suffered from parental alcoholism, and 17.2% experienced suicide in close surroundings; 54.1% experienced bullying or violence (26.0%), and 85.4% showed signs of other types of self-harm, girls more often (P < .001). In 52.8% of cases, the attempt was spontaneous, and 34% relapsed. In summary female gender, living in orphanages, and signs of other self-harm were significantly related to suicide attempt.
Study of Lora Module Ra-02 For Long Range, Low Power, Low Rate Picture Transfer Applications

LoRa is a long-range, low-power, low-bitrate communication technology that is a major component of the Internet of Things (IoT). In realizing smart cities, many environmental parameters are observed in decision making that supports sustainable development. LoRa is an alternative to wireless communication from wifi and GSM networks which are more power-consuming. The use of many sensor nodes that are distributed in areas with difficult access to electricity requires low power usage. The use of low-power LoRa has the disadvantage of slow transmission speeds. Although environmental monitoring based on specific parameters such as temperature, humidity, gas, pH, etc. has been widely applied, visual environmental monitoring is necessary. In monitoring volcanoes, visual field inspections are needed to support decision making. Monitoring can be done periodically based on time. The LoRa Ra-02 module is a Lora module that is cheap and widely available in the market. In this research, a study on the potential use of the Lora Ra-02 Module for low-speed image transfer applications was conducted.
Economic Geography of U.S. Apparel Trade: Home Market and Vertical Linkage Effects

ABSTRACT A partial equilibrium trade model is used to test the role of vertical linkages and home market effects on the pattern of U.S. apparel trade, while controlling for trade costs and comparative advantage. Input output data is used to investigate the significance of linkages between the apparel and textile industries. Industrial production data is used to provide industry specific estimates of the home market effect. We find strong evidence of home market effects that increase with the phasing out of apparel quotas. Strong linkages between the apparel and textile industries in the exporting country are positively correlated with apparel exports.
Chemically tailored molecular surface modifiers for efficient and stable perovskite photovoltaics

Perovskite solar cells (PSCs) have attracted intense attention based on their high power conversion efficiency and low production cost. However, due to the polycrystalline nature and the intrinsic hydrophilicity of the metal halide perovskite moieties, the photovoltaic performance of PSCs is largely limited by defects within the polycrystalline perovskites and the sensitivity to moisture. In this perspective, we focus on the chemically tailored interface materials to passivate the defects and improve the moisture stability of PSCs. First, we provide a brief overview of various molecular interface modifiers. Thereafter we provide examples from our recent work on organic ammonium halide‐based passivation materials as representatives to illustrate the design strategies and the modification effects. In the end, we shed light on the future development of organic ammonium halides for applications in PSCs.
Determination of Optimal MR&R Strategy and Inspection Intervals to Support Infrastructure Maintenance Decision Making

In the commonly used approach to maintenance scheduling for infrastructure facilities, maintenance decisions are made under the assumptions that inspection frequency is periodical and fixed, and that the true state of a facility is revealed through inspections. This research addresses these limitations by proposing a decision-making approach for determining optimal maintenance, repair, and rehabilitation (MR&R) strategy and inspection intervals for infrastructure facilities that can explicitly take into account non-periodical inspections as well as previously considered periodical inspections. Four transition probabilities are proposed to represent four different MR&R strategies. Then, an optimization program is suggested to minimize MR&R and inspection costs of a bridge element network over a given time period, while keeping the condition states of the element network above a predetermined level. A case study was applied to illustrate the proposed approach. The results show that the proposal approach can support decision making in situations where non-periodical inspections and MR&R actions are incorporated into the model development. If employed properly, this may allow agencies to maintain their infrastructure more effectively, resulting in cost savings and reducing unnecessary waste of resources.
ISOLATION, CHARACTERIZATION AND PREDICTION OF BIOLOGICAL ACTIVITY OF TWO NEW FATTY ESTERS AND A PHENOL FROM THE HEARTWOOD OF PTEROCARPUS MARSUPIUM ROXB.

Objective: The current investigation involves the isolation, characterization and prediction of biological activity spectra of the phytoconstituents from the ethanolic extract of the heartwood of Pterocarpus marsupium roxb. (Fabaceae). Methods: The heartwood (3 kg) was extracted in alcohol by cold maceration for 21 d and the compounds were isolated by column chromatography. The compounds thus isolated were characterised and their structures were elucidated by using assorted spectral data analysis, i.e., infrared radiation spectroscopy (IR), proton nuclear magnetic resonance ( 1 HNMR), carbon thirteen nuclear magnetic resonance ( 13 C NMR) and direct analysis in real time mass spectrometry (DART-MS). PASS (prediction of activity spectra for substances) computer program was used to predict the biological activity spectra of the isolated compounds. Results: Phytochemical investigation of ethanolic extract of the heartwood of Pterocarpus marsupium led to isolate two fatty esters and a phenolic compound characterised as n -octanyl n -octadeca-9,12-dienoate ( n -octanyl linoleiate, 1), n -dodecanyl n -octadeca-9,12-dienoate ( n -dodecanyl linoleiate, 2) and 2, 3-dioxymethylene phenol (3). These phytoconstituents are reported for first time in the heartwood of Pterocarpus marsupium Roxb. The in silico profiling of these phytoconstituents exhibited their broad spectra of biological activity. Compounds (1) and (2) showed their maximum activity as All-trans-retinyl-palmitate hydrolase inhibitor, anti eczematic, lipid metabolism regulator, etc. and compound (3) was found to be active as membrane integrity agonist, aspulvinone dimethylallyl transferases inhibitor, carminative, neurotransmitter uptake inhibitor, etc. Conclusion: These isolated phytoconstituents can be used as the marker compounds to establish the identity, quality and purity of the drug. The results of PASS prediction shall be very useful for establishing these phytoconstituents as active pharmacological moieties.
Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China

Abstract. Recent increases in atmospheric carbon dioxide (CO2) and temperature relieve the limitation of these two on terrestrial ecosystem productivity, while nutrient availability constrains the increasing plant photosynthesis more intensively. Nitrogen (N) and phosphorus (P) are critical for plant physiological activities and consequently regulates ecosystem productivity. Here, for the first time, we mapped N and P densities of leaves, woody stems, roots, litter and soil in forest, shrubland and grassland ecosystems across China, based on an intensive investigation in 4175 sites, covering species composition, biomass, and nutrient concentrations of different tissues of living plants, litter and soil. Forest, shrubland and grassland ecosystems in China stored 7665.62 × 106 Mg N, with 7434.53 × 106 Mg (96.99 %) fixed in soil (to a depth of one metre), and 32.39 × 106 Mg (0.42 %), 59.57 × 106 Mg (0.78 %), 124.21 × 106 Mg (1.62 %) and 14.92 × 106 Mg (0.19 %) in leaves, stems, roots and litter, respectively. The forest, shrubland and grassland ecosystems in China stored 3852.66 × 106 Mg P, with 3821.64 × 106 Mg (99.19 %) fixed in soil (to a depth of one metre), and 3.36 × 106 Mg (0.09 %), 14.06 × 106 Mg (0.36 %), 11.47 × 106 Mg (0.30 %) and 2.14 × 106 Mg (0.06 %) in leaves, stems, roots and litter, respectively. Our estimation showed that N pools were low in northern China except Changbai Mountains, Mount Tianshan and Mount Alta, while relatively higher values existed in eastern Qinghai-Tibetan Plateau and Yunnan. P densities in plant organs were higher towards the south and east part of China, while soil P density was higher towards the north and west part of China. The estimated N and P density datasets, Patterns of nitrogen and phosphorus pools in terrestrial ecosystems in China (the pre-publication sharing link: https://datadryad.org/stash/share/78EBjhBqNoam2jOSoO1AXvbZtgIpCTi9eT-eGE7wyOk, are available from the Dryad Digital Repository (Zhang et al., 2020). These patterns of N and P densities could potentially improve existing earth system models and large-scale researches on ecosystem nutrients.
Development of fragility functions for rigid-frame bridges subjected to tsunami-induced hydrodynamic forces

Abstract The rigid-frame bridges with a fully continuous moment connection between the superstructure and substructure piers are suitable for high-seismic regions; however, research on the response of these bridge types under tsunami loads is limited. This paper presents a framework for developing fragility functions of coastal rigid-frame bridges, and bridges with strong pier-to-deck connectivity, undergoing tsunami-induced hydrodynamic loads. The fragility analysis is demonstrated on a three-span reinforced concrete (RC) bridge structure with double-column bents. The Monte Carlo simulation is implemented to consider the uncertainties in capacity and demand parameters. The efficiency of single-parameter and two-parameter intensity measures for predicting the response of bridges is examined. The viability of strengthening bridge piers using fiber-reinforced polymer (FRP) is also investigated. The results indicate that the use of two-parameter intensity measures is a better option to estimate the structural response since the hydrodynamic forces are a function of both the flow depth and velocity. This also leads to a significant reduction in the scatter of fragility data. The comparative assessment of the initial and FRP-strengthened bridges highlights that the FRP-jacketing is an effective method in reducing the risk of failure of the rigid-frame bridges.
Recovery from acute kidney injury is an independent predictor of survival at 30 days only after out-of-hospital cardiac arrest who were treated by targeted temperature management

Background: Development of acute kidney injury (AKI) after out-of-hospital cardiac arrest (OHCA) is associated with mortality and poor neurological outcome. However, the effect of recovery from AKI after OHCA is uncertain. This study investigates whether recovery from AKI was associated with the rate of survival and neurological outcome at 30 days after OHCA. Methods: This is a prospective multicentre observational cohort study of adult OHCA patients treated with targeted temperature management (TTM) across five hospitals in South Korea between February 2019 and July 2020. AKI was diagnosed using the Kidney Disease: Improving Global Outcomes criteria. The primary outcome was the rate of survival at 30 days, and the secondary outcome was the rate of survival with a favourable neurological outcome at 30 days, defined by a score of 3 or less on the modified Rankin scale. Results: Among the 2,018 patients with OHCA, 79 were treated with TTM. After excluding two patients with incomplete data on outcomes, 77 were analysed. AKI developed in 43 (56%) patients. Among them, 22 (51%) recovered from AKI. Although the rate of survival at 30 days for the recovery group was superior to the non-recovery group (82% vs. 24%, P < 0.001), the rate of survival with a favourable neurological outcome at 30 days for the recovery group was not different than that for the non-recovery group (32% vs. 10%, P = 0.132). Recovery from AKI was an independent predictor of survival at 30 days after OHCA in the multivariate analysis (adjusted odds ratio, 22.737; 95% confidence interval, 3.814-135.533; P = 0.001); however, it was not associated with a favourable neurological outcome at 30 days after OHCA in the multivariate analysis. Conclusion: Recovery from AKI was an independent predictor of survival at 30 days only after OHCA who were treated by TTM.
Preparation of Fe3O4 @ CaP magnetic fiber scaffold with electrospining

Fe3O4@CaP magnetic fiber scaffold is prepared with electrospining by compounding ferroferric oxide nanoparticles into the calcium phosphate ceramic. The composite scaffold combines the superparamagnetism of ferroferric oxide nanoparticles and the good biocompatibility and bone tissue guidance of calcium phosphate, and has a high specific surface area and provides a suitable regeneration space for bone tissue, which is expected to be used for biomedical field.
Phenomena Affecting Catalytic Reactions at Solid–Liquid Interfaces

Interest in liquid-phase reactions over heterogeneous catalysts is growing rapidly, partially because of the desire to find efficient methods for biomass conversion to renewable fuels and chemicals. The presence of a solvent can affect reactions at surfaces by competing with reactants and products for adsorption sites and solvating adsorbed species. Mass transport limitations can also have a pronounced effect on liquid-phase reaction rates. Because many heterogeneous catalysts were designed to be stable under gas-phase reaction conditions, their operation in liquid reaction media at moderately elevated temperatures can result in unexpected structural changes. In some cases, components derived from the evolving catalyst contribute significantly to the catalytic activity. Solvents, as well as byproducts from biomass feedstocks, can also act as homogeneous catalysts to alter the intrinsic reactivity of the heterogeneous catalyst. In this contribution, we discuss each of these phenomena and provide illustrati.
Definition of Virtual Reality through Creative Act

Currently there are many attempts to determine virtual reality which is created by digital technologies. The present article discusses this phenomenon in the creative act. This approach gives an opportunity for the full consideration of virtual reality because the category of reality includes not only digital technologies but subjective perceptions which creates problems in its definition. According to our understanding virtual reality is determined by the relation with the person’s virtual world and digital code. The person’s creative potential is defined, in its turn, as the person’s virtual. In the creative act between virtual reality and creative potential besides homogeneous connection there is an ontological connection and then virtual reality is a medium and a tool for the person’s creative potential realization. In this case the creative act is an actualization of images or symbols, by changing the intensities of the virtual image which results in the transition of the creative potential into otherness- the virtual reality of the code. As the tool of creative reality virtual reality plays the role of the digital technology which alienates the person’s time and space. Received: 19 November 2020 / Accepted: 4 February 2021 / Published: 5 March 2021
Interactive multimedia – based mobile learning prototipe development

Mobile learning (m-learning) is a learning paradigm utilizing mobile technology and devices which is expected to experience rapid and potential development along with the development of mobile technology itself. The flow of information that is so swift requires each individual to be able to access learning activities more flexibly meaning without being limited by time and space. Therefore, we need an application that is able to accommodate the needs of every individual with a variety of activities but is still able to participate in various learning activities without limited space and time.
Synthesis of Fluoromethyl‐Substituted Isoxazolines via Transition Metal‐Free Oxyfluorination of Alkenyl Oximes

A mild and efficient transition metal-free intramolecular oxyfluorination of alkenyl oximes is demonstrated. The reaction tolerates a range of substrates to give a series of monofluoromethylated isoxazoline derivatives with good yields. The possible pathways are proposed based on the reaction results and control experiments.
Warped Document Image Correction Based on Checkboard Pattern and Geometric Transformation

— Document image warping problem refers to the process of geometrically transforming 2D images. In this work we aim to solve the warped document image problems. The idea of the proposed method is inspired from the concept of image registration to align two images (distorted document and undistorted ground truth checkboard). In this paper, we propose document image dewarping method based on checkboard calibration pattern and geometric transformation. Some pairs of control points are selected between the two images to define the mapping function between them. The dewarping process transforms the warped document image according to the geometric transformation defined by the calculated mapping function. Results on document dewarping dataset CBDAR 2007 demonstrate the success of our strategy. OCR (Optical Character Recognition) error metrics are also used to gauge the success of the suggested approach. Based on the quantitative and qualitative metrics the proposed method outperforms the compared state of the art method.
Feature optimization using Backward Elimination and Support Vector Machines (SVM) algorithm for diabetes classification

Diabetes is a disease that occurs when the blood glucose level is higher than normal and also leads to health problems. Early and accurate diagnosis needs to be carried out on individuals affected by this disease. Furthermore, excellent treatment needs to be provided to prevent worse situations. Some studies have used several machine learning methods to diagnose diabetes. Furthermore, in this study, the Backward Elimination and Support Vector Machine (SVM) algorithm was used to classify the PIMA Indians diabetes dataset. It consisted of 268 diabetic and 500 non-diabetic patients with eight attributes. Backward Elimination is a feature selection method used to remove irrelevant features based on the linear regression model. Using this method, the right features for the model was expected. This method has some advantages which include increasing training time, decreasing complexity and improving performance and accuracy. Therefore, the performance of SVM improved. Based on the experiments, it was discovered that by combining feature selection algorithm (backward elimination) and SVM, the highest accuracy obtained was 85.71% using 90% data training. Therefore, it was concluded that Backward Elimination combined with SVM algorithm is an excellent method to classify diabetes by using the PIMA Indians diabetes dataset.