Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar activity modulates the El Niño‐Southern Oscillation‐induced precipitation anomalies over southern China in early spring

The present study identifies an evident solar cycle modulation upon the spatial pattern of the El Niño‐Southern Oscillation (ENSO) impact on the southern China precipitation in early spring (February–March). During high/low solar activity (HS/LS) years, the significant positive correlation between the wintertime Niño 3.4 index and the precipitation in the following early spring mainly locates at the southeastern China/Yangtze River Valley (SEC/YRV). Our analysis also suggests that the precipitation anomalies show asymmetries between ENSO warm and cold events under both solar phases. In HS years, the ENSO warm events‐related rainfall anomalies over the southern China are weak, but during the ENSO cold events significant dry anomalies appear at the SEC region. In LS years, significant wet anomalies over the YRV region are found during the ENSO warm events, whilst the rainfall anomalies are insignificant for the ENSO cold events. These modulations on precipitation are mediated by the changes in the ENSO‐associated anomalous western North Pacific anticyclone/cyclone, which may be attributed to the solar modulations on the ENSO‐associated sea surface temperature anomalies. Our results highlight that the level of solar activity should be taken into account when ENSO is used as a predictor for the precipitation over East Asia. [Correction added on 18 June 2021, after first online publication: The text for the abstract and graphical abstract were interchanged in the original‐published article. This updated version rectifies the error. ]
EVALUATION OF THE ANTIOXIDANT AND ANTIMICROBIAL PROPERTIES OF NOSTOCLINCKIA ISOLATED FROM KUKKARAHALLI LAKE, MYSORE

The present study evaluates the antioxidant and antimicrobial activity of Nostoc linckia which was isolated from Kukkarahalli lake, Mysore and maintained in BG-12 medium. The antioxidant potential of the N. linckia extract was investigated using 2,2- Diphenyl, 1- Picryl Hydrazyl and 2, 2´- Azino- bis-(3- ethylbenzothiazoline- 6- sulfonic acid) radical scavenging assays and ferric reducing power assay. It expressed DPPH radical scavenging activity at 1.58 mMTrolox Equivalent/g extract, ABTS˙ radical scavenging activity at 3.8 mMTE/g extract and total ferric reducing power at 1.05mgButylated Hydroxy Anisole Equivalents/ g extract. The radical scavenging activity was compared with BHA as standard wherein it expressed DPPH and ABTS˙+ radical scavenging activity of 2.8 mMTE/g and 4.3 mMTE/g respectively. In vitro bactericidal screening of ethanol extract of Nostoc linckia was carried out against six species of bacteria namely Bacillus cereus, Bacillus subtilis, Escherichia coli, Klebsiella oxytoca, Proteus vulgaris and Staphylococcus aureus wherein B. cereus, B. subtilis and E.coli expressed minimum bactericidal concentration values more than 1 mg/ml while K. oxytoca, P. vulgaris and S. aureus expressed MBC values of 0.51, 0.77 and 0.79 mg/ml respectiviely. The study also revealed minimum algicidal concentration of the extract at 0.625 mg/ml against Nostoc sp. , Spirullina sp. Synecocystis sp. , and 1.25 mg/ml against Gleocapsia sp by the 6th day after inoculation. The antimicrobial assay was carried out using micro titre plate method.
Manifold Learning-Based Semisupervised Neural Network for Hyperspectral Image Classification

Feature extraction (FE), an important preprocessing step in hyperspectral image (HSI) classification, has received growing attention in the remote sensing community. In recent years, the FE ability of deep learning (DL) methods has been widely recognized. However, most DL models focus on training networks with strong nonlinear mapping ability. They fail to explore the intrinsic manifold structure in HSI, and their performance depends on large size of the labeled training set. To address the above problems, a novel FE approach, termed manifold learning-based semisupervised neural network (MSSNet), was proposed in this article. By introducing the graph embedding (GE) framework, MSSNet develops a semisupervised graph model to explore the manifold structure in HSI with both labeled and unlabeled data. On the basis of this graph model, MSSNet constructs a combined loss function to take into account the metric of difference values and the exploration of manifold margins; thus, it reduces the difference between the predictive value and the actual value to enhance the separability of the features extracted by the network. Experiments conducted on real-world HSI datasets demonstrate that the performance of the proposed MSSNet outperforms some related state-of-the-art FE approaches.
Overview of Gulf of Mottama Wetland (GoMW) & Size Distribution and Economic Status of Sea Bass in Myanmar

The present study was conducted the status of sea bass from Kokko and Kyuntone of The Gulf of Motttama Wetland (GoMW) area in Thanatpin Township in Bago Region Myanmar from September 2019 to August 2020. Fifty specimens were monthly collected, measured and weighed. Invoices of sea bass were collected for the depot and fish sellers by monthly. In Kokko, mean value of standard length and body weight were highest in March (32.70±1.58, 660.7±112.23). The mean value of standard length was peak in January (31.39±7.16) but peak of body weight was in March (963.24±280.86) in Kyuntone villages. The lowest mean value of standard length and body weight were found in June at both study areas. According to the invoice data revealed that monthly catch weight of sea bass is most abundance in October (829.92) kg in Kokko, (339.12) kg in Kyuntone. Based on price of relations to size group, small size C &lt; 300g (41%) was mostly abundance in Kokko and in Kyuntone small size C &lt; 300g (35%) was second abundance. Specimens were not landed in April and May. In June, young specimens were very rarely seen in both study sites. The important roles of wetland fishes, the economic valuation of GOMW in Myanmar and samples of fishing gear and value chain of sea bass in Myanmar was expressed in this study.
Study of Climate Impact on Vegetation Cover in Kherson Oblast (Ukraine) Using Normalized Difference and Enhanced Vegetation Indices

Remote sensing is a convenient tool for the study of vegetation cover conditions and dynamics using normalized difference and enhanced vegetation indices. Determination of the connection between weather and vegetation indices plays an important role in better understanding peculiarities of ecosystems reaction to changing climate conditions. The study devoted to the evaluation of annual and long-term dynamics under vegetation cover conditions, and its reaction to the climate factor, was performed through the establishment of the link between remote sensing information (smoothed time series data on normalized and enhanced vegetation indices) and results of on-land hydrometeorological observations for air temperature and precipitation amounts in Kherson oblast of Ukraine during the period from 2012 to 2019 by the means of linear regression analysis of the data. The values of the studied vegetation indices (Terrain MODIS NDVI and MODIS EVI 250 m smoothed time series) were calculated and generalized by the means of GDAL raster analysis toolkit in QGIS 3.10. Statistical data processing was performed using BioStat v7 software. It was found that there is a strong tendency towards the enhancement of vegetation in the region year by year. Climate has strong effect on the vegetation, and the main input belongs to air temperature, while precipitation amounts cannot be considered as a driving force of changes in the growth of vegetation. Enhanced vegetation index seems to be more reliable for the estimation of vegetation cover conditions in comparison to normalized difference vegetation index.
Chronobiological Patterns of White-Tailed Deer in Suburban Maryland: Implications for Deer Population Management, Human-Deer Conflict, and Zoonotic Disease Mitigation

Understanding the ecology of the often dense white-tailed deer populations in urban and suburban landscapes is important for mitigating a variety of conflicts that arise with dense human populations, especially issues surrounding zoonotic disease mitigation and impacts to existing understory vegetation. We collared white-tailed deer in highly suburban areas of Howard County, Maryland. High-resolution GPS data enabled us to create autocorrelated kernel density home ranges and model deer speed, rates of activity, and proximity to residential buildings over time. Home ranges encompassed approximately 35% residential land and an average of 71 and 129 residential properties were found within female and male core ranges, respectively. Sex, time of day, and day of year all influenced deer speed, activity, and proximity to residences. Deer moved into residential areas nightly, especially in winter, and exhibited bouts of increased speed and activity shortly after sunrise and sunset, though with distinctive seasonal changes. We discuss how variation in home ranges and movements may influence population management success and explore year-round periods of increased risk of deer transporting ticks to residential areas. These findings focus our broad understanding of deer movements in suburban landscapes to improve deer population management, limit human-wildlife conflict, and manage against the spread of ticks and tick-borne disease in suburban areas.
DC magnetron sputtering deposition of titanium oxide nanoparticles : influence

Titanium dioxide nanoparticles were prepared on glass substrates by reactive DC magnetron sputtering. As highlighted by the atomic force microscopy characterization, we were able to control the nanoparticles' surface coverage and diameter by varying the deposition time and the total pressure, respectively. The titanium dioxide energy band gap, determined by using ultraviolet-visible spectroscopy, depends on the total pressure but is quite independent on the deposition temperature. On the contrary, it is blue shifted when the pressure increases. Finally, the contact angles slightly decrease after ultraviolet illumination irrespective of the different deposition parameters, indicating an improvement of the hydrophilic properties of the adsorbed layer. After 21 h in dark, the contact angles are nearly identical to the ones before exposure to UV light: the samples do not keep their hydrophilic behaviour.
Chemical constituents of Paeonia lactiflora

OBJECTIVE To study chemical constituents of Paeonia lactiflora.METHODS The compounds were isolated and purified by various chromatographic techniques and identified by their physicochemical properties and spectral analysis.RESULTS Six monoterpene glycoside compounds were isolated and identified as benzoylpaeoniflorin sulfonate(Ⅰ),paeoniflorin sulfonate(Ⅱ),paeoniflorin(Ⅲ),albiflorin(Ⅳ),4'-hydroxyl-albiflorin(Ⅴ),paeonivayin(Ⅵ). CONCLUSION Compounds(Ⅰ)is a new compound.
Fingermark Analysis by Fourier Transform Infrared Microscopy Using Chemometric Tools

The temporal estimation of the fingermarks deposition at crime scenes is a recurring issue in forensic identification. To study this challenging topic, a preliminary study was proposed to develop a method of fingermark analysis by Fourier Transform Infrared Microscopy (µ-FTIR), using chemometric tools for time separation in a six-day aging study. The samples were collected and analyzed at hour zero, 3 days (72 hours), 4 days (96 hours), 5 days (120 hours) and 6 days (144 hours). The samples were separated into a calibration set and a test set, using Kennard Stone. Following, a comparison between variable selection tools was made of the Ant of Colony (AOC) and the Genetic Algorithm (GA) were used with subsequent application of the Linear Discriminant Analysis (LDA). The results showed that in the analyzed samples there was a predominance of sebaceous material because of the presence of saturated esters signals, with two regions of interest in the infrared spectra, the first being 1800 - 1100 cm-1 and the second region being 3000 - 2800 cm-1. The statistical tools could group the fingermarks by donors and by age, emphasizing the separation within the tested period. More studies need to be carried out, but this work provide that µ-FTIR associated with chemometric analysis was able to separate fingermarks samples aged for up to a week.
Lung cancer and breast cancer mortality trends among European women in the age of 45-74 years old

Introduction We aimed to analyze and compare the most up-to-date breast and lung cancer mortality trends in European women aged 45-74. Material and methods The data on breast and lung cancer mortality in 1960-2017 were obtained from the World Health Organization Mortality DataBase and Eurostat. To determine mortality trends and generate annual percent change, with 95% confidence intervals, joinpoint regression was applied. Results In most European Union (EU) member states (15 out of 28), lung cancer mortality was higher than breast cancer mortality, with either increasing or stable lung cancer mortality trends. In four other EU countries, breast and lung cancer mortality trends in the last reported year were almost equal or equal. Conclusions Lung cancer is becoming the leading cause of cancer deaths among European women. There is a need for ensuring women-targeted smoking cessation services to decrease tobacco-attributable lung cancer mortality.
Levels of polyphenol oxidase activity in leaves of Milicia seedlings is indicative of the resistance to Phytolyma lata‐induced gall disease

Phytolyma lata‐induced galling has remained one of the foremost challenges limiting the regeneration of Milicia species in nurseries and degraded forests in West Africa. Although planting of Milicia progenies resistant to Phytolyma attack has been identified as an opportunity for long‐term control of the pest, the absence of biomarkers for early detection of resistance has limited the selection of resistant seedlings for planting. We compared phenolic metabolites and oxidative enzymes in resistant and susceptible Milicia progenies with the aim of identifying potential biomarkers for resistance to Phytolyma‐induced galling in seedlings. Levels of total phenolics and ortho‐dihydroxyphenolics did not significantly differ between the susceptible and resistant saplings or among seedlings. Similarly, peroxidase activity did not differ among sapling progenies or among seedlings. Thus, no clearly defined role could be ascribed to phenolics and peroxidase in resistance of Milicia species to P. lata‐induced galling. However, polyphenol oxidase (PPO) activity was over two‐fold higher in the resistant than the tolerant or susceptible progenies, suggesting that higher levels of PPO activity corresponded with an increased level of resistance to galling. With further validation, PPO activity in leaves of Milicia seedlings can be used as a biomarker of resistance to Phytolyma‐induced galling.
Controlled preparation of magnetically separable BiOBr/BiFeO3 heterostructures by chemical etching process with enhanced visible light photocatalytic activities and anti-photocorrosion

ABSTRACT Novel magnetically separable BiOBr/BiFeO3 heterostructures were fabricated via a facile in situ hydrothermal chemical etching process using cetyltrimethyl-ammonium bromide (CTAB) and sulphuric acid as etching agents to react with BiFeO3 particles. The effects of solution pH and CTAB amount on the structure, morphology, and optical properties of the as-prepared samples were investigated. It was found that the best acidity of solution is pH = 3.0 for the formation of BiOBr/BiFeO3 heterostructures from BiFeO3 powder. Their photocatalytic activities and anti-photocorrosion behaviour were measured by the photocatalytical reduction of heavy metal ion Cr (VI) under visible-light irradiation. Experimental results show that the molar ratio of BiOBr to BiFeO3 contributed to different morphologies and photocatalytic activities of BiOBr/BiFeO3 composites. The optimised molar ratio in BiOBr/BiFeO3 composites was found to be 1:1. The photocatalytic reduction rate of Cr(VI) over 1:1 BiOBr/BiFeO3 composites was found to be 4.9 and 3.0 times higher than that of pure BiFeO3 and BiOBr, respectively. The hybridisation of BiOBr with BiFeO3 can markedly inhibit the photocorrosion of semiconductor BiFeO3. No obvious catalytic activity decrement can be found after five consecutive photocatalytic Cr (VI) reduction, which demonstrates the high structural stability of 1:1 BiOBr/BiFeO3. Furthermore, a possible photogenerated charge transfer process was proposed. The obviously enhanced photocatalytic activity could be ascribed to the formation of BiOBr-BiFeO3 heterojunction, accelerating the effective separation of photoexcited electron−hole pairs. This study suggests that the magnetically separable BiOBr/BiFeO3 heterostructures can be a promising photocatalyst for environment-related applications.
Design of Automation Environment for Analyzing Various IoT Malware

: With the increasing proliferation of IoT systems, the security of IoT systems has become very important to individuals and businesses. IoT malware has been increasing exponentially since the emergence of Mirai in 2016. Because the IoT system environment is diverse, IoT malware also has various environments. In the case of existing analysis systems, there is no environment for dynamic analysis by running IoT malware of various architectures. It is inefficient in terms of time and cost to build an environment that analyzes malware one by one for analysis. The purpose of this paper is to improve the problems and limitations of the existing analysis system and provide an environment to analyze a large amount of IoT malware. Using existing open source analysis tools suitable for various IoT malicious codes and QEMU, a virtualization software, the environment in which the actual malicious code will run is built, and the library or system call that is actually called is statically and dynamically analyzed. In the text, the analysis system is applied to the actual collected malicious code to check whether it is analyzed and derive statistics. Information on the architecture of malicious code, attack method, command used, and access path can be checked, and this information can be used as a basis for malicious code detection research or classification research. The advantages are described of the system designed compared to the most commonly used automated analysis tools and improvements to existing limitations.
Inhibition of Indigoidine Synthesis as a High-Throughput Colourimetric Screen for Antibiotics Targeting the Essential Mycobacterium tuberculosis Phosphopantetheinyl Transferase PptT

A recently-validated and underexplored drug target in Mycobacterium tuberculosis is PptT, an essential phosphopantetheinyl transferase (PPTase) that plays a critical role in activating enzymes for both primary and secondary metabolism. PptT possesses a deep binding pocket that does not readily accept labelled coenzyme A analogues that have previously been used to screen for PPTase inhibitors. Here we report on the development of a high throughput, colourimetric screen that monitors the PptT-mediated activation of the non-ribosomal peptide synthetase BpsA to a blue pigment (indigoidine) synthesising form in vitro. This screen uses unadulterated coenzyme A, avoiding analogues that may interfere with inhibitor binding, and requires only a single-endpoint measurement. We benchmark the screen using the well-characterised Library of Pharmaceutically Active Compounds (LOPAC1280) collection and show that it is both sensitive and able to distinguish weak from strong inhibitors. We further show that the BpsA assay can be applied to quantify the level of inhibition and generate consistent EC50 data. We anticipate these tools will facilitate both the screening of established chemical collections to identify new anti-mycobacterial drug leads and to guide the exploration of structure-activity landscapes to improve existing PPTase inhibitors.
Developing a Smartphone Application Prototype as Digital Supplementary Reading Materials for the Tenth Graders for Vocational High School

The use of technology in language learning has improved the development of educational products. Related to reading, it makes reading materials is not limited to printed-text only. The Mobile-assisted Language Learning (MALL) makes smartphones have big impact on education since it can be used as a device to access variety of technology-based learning materials. In such a way, the development of learning materials that can be accessed from a smartphone is highly needed. Thus, the need for accessible learning materials from a smartphone is crucial to students, especially during the situation where online learning must be carried out. Since students must do distance learning with teachers, smartphone application can be an additional material that can accommodate students to learn independently. The current study is conducted to develop a smartphone application prototype to support the benefit of technology to the practice of English Language Teaching in Indonesia. The R&D model of Borg & Gall (2003) was used to develop this digital supplementary reading material in the form of a smartphone application prototype. The first final product of this study is a smartphone application named ‘Seeds’ that has implemented the three-phase reading technique. Besides, it consists of three different titles of descriptive text added with different forms of reading activities. The product is also supported with additional features like pop-up glossary, re-reading, show-score, and share-score. The second product is the e-manual book in the form of . pdf where it is written in English and Indonesian.
Modelling long-term alluvial peatland dynamics in temperate river floodplains

Abstract. Peat growth is a frequent phenomenon in European river valleys. The presence of peat in the floodplain stratigraphy makes them hotspots of carbon storage. The long-term dynamics of alluvial peatlands are complex due to interactions between the peat and the local river network, and as a result, alluvial peatland development in relation to both regional and local conditions is not well understood. In this study, a new modelling framework is presented to simulate long-term peatland development in river floodplains by coupling a river basin hydrology model (STREAM) with a local peat growth model (modified version of Digibog). The model is applied to two lowland rivers in northern Belgium, located in the European loess (Dijle river) and sand (Grote Nete river) belts. Parameter sensitivity analysis and scenario analysis are used to study the relative importance of internal processes and environmental conditions on peatland development. The simulation results demonstrate that the peat thickness is largely determined by the spacing and mobility of the local river channel(s) rather than by channel characteristics or peat properties. In contrast, changes in regional conditions such as climate and land cover across the upstream river basin showed to influence the river hydrograph, but have a limited effect on peat growth. These results demonstrate that alluvial peatland development is strongly determined by the geomorphic boundary conditions set by the river network and as such models must account for river channel dynamics to adequately simulate peatland development trajectories in valley environments.