Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid Detection of Rice Disease Based on FCM-KM and Faster R-CNN Fusion

In this paper, a method for detecting rapid rice disease based on FCM-KM and Faster R-CNN fusion is proposed to address various problems with the rice disease images, such as noise, blurred image edge, large background interference and low detection accuracy. Firstly, the method uses a two-dimensional filtering mask combined with a weighted multilevel median filter (2DFM-AMMF) for noise reduction, and uses a faster two-dimensional Otsu threshold segmentation algorithm (Faster 2D-Otsu) to reduce the interference of complex background with the detection of target blade in the image. Then the dynamic population firefly algorithm based on the chaos theory as well as the maximum and minimum distance algorithm is applied for optimization of the K-Means clustering algorithm (FCM-KM) to determine the optimal clustering class k value while addressing the tendency of the algorithm to fall into the local optimum problem. Combined with the R-CNN algorithm for the identification of rice diseases, FCM-KM analysis is conducted to determine the different sizes of the Faster R-CNN target frame. As revealed by the application results of 3010 images, the accuracy and time required for detection of rice blast, bacterial blight and blight were 96.71%/0.65s, 97.53%/0.82s and 98.26%/0.53s, respectively, indicating clearly that the method is more capable of detecting rice diseases and improving the identification accuracy of Faster R-CNN algorithm, while reducing the time required for identification.
On the Feature Selection Methods and Reject Option Classifiers for Robust Cancer Prediction

Cancer is the second leading cause of mortality across the globe. Approximately 9.6 million people are estimated to have died due to cancer disease in 2019. Accurate and early prediction of cancer can assist healthcare professionals to devise timely therapeutic innervations to control sufferings and the risk of mortality. Generally, a machine learning (ML) based predictive system in healthcare uses data (genetic profile or clinical parameters) and learning algorithms to predict target values for cancer detection. However, optimization of predictive accuracy is an important endeavor for accurate decision making. Reject Option (RO) classifiers have been used to improve the predictive accuracy of classifiers for cancer like complex problems. In a gene profile all of the features are not important and should be shaved off. ML offers different techniques with their own methodology for feature selection (FS) and the classification results are dependent on the datasets each having its own distribution and features. Therefore, both FS methods and ML algorithms with RO need to be considered for robust classification. The main objective of this study is to optimize three parameters (learning algorithm, FS method and rejection rate) for robust cancer prediction rather than considering two traditional parameters (learning algorithm and rejection rate). The analysis of different FS methods (including t-test, Las Vegas Filter (LVF), Relief, and Information Gain (IG)) and RO classifiers on different rejection thresholds is performed to investigate the robust predictability of cancer. The three cancer datasets (Colon cancer, Leukemia and Breast cancer) were reduced using different FS methods and each of them were used to analyze the predictability of cancer using different RO classifiers. The results reveal that for each dataset predictive accuracies of RO classifiers were different for different FS methods. The findings based on proposed scheme indicate that, the ML algorithms along with their dependence on suitable FS methods need to be taken into consideration for accurate prediction.
No evidence of MET and HER2 over-expression in non-small cell lung carcinoma and breast cancer, respectively, raises serious doubts on using RNA-seq profiles of tumor-educated platelets as a ‘liquid biopsy’ source

The prevailing excitement in the scientific and medical community about ‘liquid biopsy’, a minimally invasive diagnostic involving body fluid, is understandable, since it has the possibility of detecting pre-malignant and early-stage cancers, and enables the assessment of response to treatments [1]. Supplementing previous techniques that sample circulating cell-free tumor DNA, tumor cells, and microvesicles [2], a recent work has shown using RNA-seq data that tumor-educated platelets (TEP) can distinguish 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy [3]. However, as demonstrated in the current work, over-expression of MET genes in nonsmall cell lung carcinoma (NSCLC), and HER2/ERBB2 genes in breast cancer are grossly misreported. Based on an analysis of a smaller subset of samples, it is shown that there is little, leave alone overexpression, of these genes in the samples with the specified disease. Confirmation that this is bonafide platelet mRNA is provided by high levels of the platelet marker TMSB4X. A kmer-based method (k=32) has been used here (KEATS) to detect homologous transcripts, although the results are easily verified by a BLAST search BLAST’ing the MET gene (Accid: NM 001127500.2) to a NSCLC sample (https://trace.ncbi.nlm.nih.gov/Traces/sra/? run=SRR1982781) shows almost no expression. This is in contrast to expected expression of the MET gene in another a NSCLC sample (SRR3475320) from another sample. Similar contradictions apply for HER2/ERBB2 genes with respect to breast cancer samples. This work emphasizes the neccessity of a more stringent verification framework for bioinformatic analyses, and raises serious doubts on using TEP as a possible ‘liquid biopsy’ candidate.
Reporting the utilization and perspectives of different surface active agents for bread making

The present study was planned to use surfactants in different concentrations along with varying amounts of shortening in the form of gels to prepare breads. For that purpose, SSL, CSL, PS-60 and GMS were used at level of 0.25, 0.50, 0.75 and 1.00 parts in combination with shortening @ 4.00, 3.75, 3.50 and 3.25 parts. The dough having surfactants gels resulted in longer resistance time and overall dough stability. The moisture and protein content of breads increased which is due to interactions of surfactant gels with starch and gluten fractions that result in increasing dough strength and baking quality. Significant increase in specific volume is observed in breads of GMS and PS-60 gels. The sensory evaluation was carried out by a panel of trained judges and the breads having GMS gels ranked highest for quality attributes. The average quality scores were higher for the SSL, CSL and PS-60 as compared to the control bread. Dn the whole, breads having surfactants gels were acceptable for all sensory characteristics.
Removal Of 2,4,6-Trichlorophenol From Aqueous Solutions Using Agricultural Waste As Low-Cost Adsorbents

Agricultural waste products including sunflower seed hulls, pumpkin seed shells, walnut shells and peanut shells were used as low-cost adsorbents for the removal of 2,4,6-trichlorophenol (TCP) from aqueous solutions. The effects of adsorbent dosage, pH and ionic strength on the adsorption of TCP were investigated. The results showed that the adsorption of TCP was pH dependent and increased upon increasing the ionic strength of the solution. The adsorption kinetics was found to follow a pseudo-second order kinetics. The equilibrium adsorption data were fitted to the Langmuir, Freundlich and Sips isotherms and the best results were achieved with the Freundlich model. The desorption of TCP using deionized water, water/methanol mixture or 5% sodium hydroxide was also studied. The results suggest that the tested materials may be used as an effective adsorbents without any treatment or any other modification for removal of TCP from the aqueous medium.
NanoSr – A New Carbonate Microanalytical Reference Material for In Situ Strontium Isotope Analysis

The in situ measurement of Sr isotopes in carbonates by MC‐ICP‐MS is limited by the availability of suitable microanalytical reference materials (RMs), which match the samples of interest. Whereas several well‐characterised carbonate reference materials for Sr mass fractions > 1000 µg g−1 are available, there is a lack of well‐characterised carbonate microanalytical RMs with lower Sr mass fractions. Here, we present a new synthetic carbonate nanopowder RM with a Sr mass fraction of ca. 500 µg g−1 suitable for microanalytical Sr isotope research (‘NanoSr’). NanoSr was analysed by both solution‐based and in situ techniques. Element mass fractions were determined using EPMA (Ca mass fraction), as well as laser ablation and solution ICP‐MS in different laboratories. The 87Sr/86Sr ratio was determined by well‐established bulk methods for Sr isotope measurements and is 0.70756 ± 0.00003 (2s). The Sr isotope microhomogeneity of the material was determined by LA‐MC‐ICP‐MS, which resulted in 87Sr/86Sr ratios of 0.70753 ± 0.00007 (2s) and 0.70757 ± 0.00006 (2s), respectively, in agreement with the solution data within uncertainties. Thus, this new reference material is well suited to monitor and correct microanalytical Sr isotope measurements of low‐Sr, low‐REE carbonate samples. NanoSr is available from the corresponding author.
Antibiotic susceptibility of the bacteria causing odontogenic infections.

Aims: An evaluation is made of bacterial species and susceptibility to various antibiotics used in application to odontogenic infections of periapical location and in pericoronitis of the lower third molar, with the aim of optimizing the antibiotherapy of such infections and thus preventing unnecessary side effects and over-treatment. Material and methods: Sixty-four patients with odontogenic infection were selected on the basis of a series of inclusion and exclusion criteria. Samples were collected from lesions under maximally aseptic conditions, avoiding oral saprophytic contamination. The samples were cultured and incubated under aerobic and anaerobic conditions, followed by bacteriological identification and antibiotic susceptibility testing. Results: A total of 184 bacterial strains were isolated and identified, comprising grampositive facultative anaerobes (68%), gramnegative strict anaerobes (30%) and grampositive facultative anaerobes (2%). Regardless of the origin of the odontogenic infection, the causal bacteria yielded the best results in terms of increased sensitivity and lesser resistance with amoxicillin / clavulanate and amoxicillin, respectively (p<0.05). Discussion: There are increasingly numerous reports in the literature of growing bacterial resistance to antibiotics in infectious processes affecting non-buccodental territories. This same tendency has not been observed in relation to oral infections, though important resistance has been documented for certain concrete antibiotics. According to our results, the common-use antibiotics with the greatest sensitivity and lowest resistance were shown to be amoxicillin / clavulanate followed by amoxicillin alone.
Tactical Investment Algorithms

There are three fundamental ways of testing the validity of an investment algorithm against historical evidence: a) the walk-forward method; b) the resampling method; and c) the Monte Carlo method. By far the most common approach followed among academics and practitioners is the walk-forward method. Implicit in that choice is the assumption that a given investment algorithm should be deployed throughout all market regimes. We denote such assumption the “all-weather” hypothesis, and the algorithms based on that hypothesis “strategic investment algorithms” (or “investment strategies”). The all-weather hypothesis is not necessarily true, as demonstrated by the fact that many investment strategies have floundered in a zero-rate environment. This motivates the problem of identifying investment algorithms that are optimal for specific market regimes, denoted “tactical investment algorithms. ” This paper argues that backtesting against synthetic datasets should be the preferred approach for developing tactical investment algorithms. A new organizational structure for asset managers is proposed, as a tactical algorithmic factory, consistent with the Monte Carlo backtesting paradigm.
Countering Hate Speech on Facebook: The Case of the Roma Minority in Slovakia

This article explores hate speech against the Roma in Slovakia on Facebook between April 2016 and January 2017 and the impact of fact-checking and personal experience strategies in countering hate speech through a quasi-experimental research design. It examines how the Roma were constructed and how discussion participants reacted to our pro-Roma interventions. The research sample consisted of 60 Facebook discussions (with more than 7,500 comments) on Roma-related topics posted by the profiles of various members of the Slovak Parliament and the most popular online news media outlets. Qualitative content analysis revealed that the Roma in Facebook discussions were constructed primarily in a negative sense, as asocial criminals misusing welfare benefits. This study demonstrated that Facebook discussion participants presenting anti-Roma attitudes did not use any research evidence to support their constructions. It also demonstrated that pro-Roma comments encouraged other participants with a pro-Roma attitude to become involved.
Effects of Potassium on Boll Development of Different Positions and Influence of Endogenous Hormone Mechanism in High Quality Cotton

High quality cotton has shown different boll development and fiber quality,the objective of this study was to investigate the effects of potassium on boll development of different positions and the influence of endogenous hormone mechanism in high quality cotton.The study was undertaken on a hybrid(Kemian 3) at Yangzhou University Farm,Yangzhou of Jiangsu Province,China,during 2003 and 2004.The results showed that potassium fertilizer application increased the boll size and boll weight effectively,especially for the bolls in the upper parts of the plant.While applying potassium fertilizer at 225、375kg·hm~(-2),the volume of the bolls in the upper part of the plant were 6.75% and 3.95% lower than that of the middle part,respectively.Compared with the middle part,the upper boll weight of the cotton plant was 4.50% lower with potassium fertilization at 225 kg·hm~(-2). whereas 1.89% higher with potassium fertilization at 3755 kg·hm~(-2). That made the overall boll weight increase and got a higher lint yield.Potassium fertilizer application also increased the fiber length and maturity significantly,narrowed the fiber quality difference between the middle and upper plant.Potassium also increased micronaire value.The results also showed that the absorption of potassium at the reproductive organs increased the IAA content in boll husk and the ZR content in the fiber for the whole plant.There are significant positive correlation between the IAA content in boll husk and boll volume,boll weight,respectively(r=0.9647~(**),r=0.9145~(**)),significant positive correlation between the ZR content in fiber and the fiber length,fiber maturity,respectively(r=0.8712~*,r=0.9474~(**)). These results suggested that potassium nourishment had changed the endogenous hormonal system,which induced boll development and bolstering boll weight and fiber quality for the whole plant.
A straightforward synthesis of phenyl boronic acid (PBA) containing BODIPY dyes: new functional and modular fluorescent tools for the tethering of the glycan domain of antibodies

We report here on the efficient and straightforward synthesis of a series of modular and functional PBA-BODIPY dyes 1–4. They are an outstanding example of the efficient merge of the versatility of the 3,5-dichloro-BODIPY derivatives and the receptor-like ability of the PBA moiety. The potential bioanalytical applicability of these tools was assessed by measuring the binding to glycan chains of antibodies by a Quartz Crystal Microbalance (QCM).
Supplementary material to "The sulfur- and halogen-rich super eruption Los Chocoyos and its impacts on climate and environment"

Abstract. The super-eruption of Los Chocoyos, newly dated to 80.6 kyrs ago, in Guatemala was one of the largest volcanic events of the past 100 000 years. Recent petrologic data show that the eruption released very large amounts of climate-relevant sulfur and ozone destroying chlorine and bromine gases. Using the recently released Earth System Model CESM2(WACCM6) we simulate the impacts of the sulfur- and halogen-rich Los Chocoyos (~ 15° N) eruption on the pre-industrial Earth System for the eruption month January. Our model results show that enhanced modeled sulfate burden and aerosol optical depth (AOD) persists for five years, while the volcanic halogens stay elevated for nearly 15 years. As a consequence the eruption leads to a collapse of the ozone layer with global mean column ozone values dropping to 50 DU (80 % decrease) leading to a 550 % increase in surface UV over the first five years with potential impacts on the biosphere. The volcanic eruption shows an asymmetric hemispheric response with enhanced aerosol, ozone, UV, and climate signals over the Northern Hemisphere (NH). Surface climate is impacted globally due to peak AOD of > 6 leading to a maximum surface cooling of > 6 K, precipitation and terrestrial net primary production (NPP) decreases of > 25 %, and sea ice area increases of 40 % in the first three years. Locally, a wetting (> 100 %) and strong increase of NPP (> 700 %) over Northern Africa is simulated in the first five years related to a southwards shift of the Inter-Tropical Convergence Zone to the southern tropics. The ocean responds with El-Niño conditions in the first two years which are masked by the strong volcanic induced surface cooling. Recovery to pre-eruption ozone levels and climate takes 15 and 30 years respectively. The long lasting surface cooling is sustained by sea ice/ocean changes in the Arctic showing an immediate sea ice area increase followed by a decrease of poleward ocean heat transport at 60° N lasting up to 20 years. In contrast, when simulating Los Chocoyos conventionally, including sulfur and neglecting halogens, we simulate larger sulfate burden and AOD, more pronounced surface climate changes and an increase of column ozone. Comparing our aerosol chemistry ESM results to other super-eruption simulations with aerosol climate models we find a higher surface climate impact per injected sulfur amount than previous studies for our different sets of model experiments, since CESM2(WACCM6) creates smaller aerosols with a longer lifetime partly due to the interactive aerosol chemistry. As the model uncertainties for the climate response to super eruptions are very large observational evidence from paleo archives and a coordinated model intercomparison would help to improve our understanding of the climate and environment response.
Aerosol direct radiative effect over clouds from a synergy of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) reflectances

Abstract. The retrieval of geophysical parameters is increasingly dependent on synergistic use of satellite instruments. More sophisticated parameters can be retrieved and the accuracy of retrievals can be increased when more information is combined. In this paper, a synergistic application of Ozone Monitoring Instrument (OMI), on the Aura platform, and Moderate Resolution Imaging Spectroradiometer (MODIS), on the Aqua platform, Level 1B reflectances is described, enabling the retrieval of the aerosol direct radiative effect (DRE) over clouds using the differential aerosol absorption (DAA) technique. This technique was first developed for reflectances from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on the Environmental Satellite (Envisat), which had the unique capability of measuring contiguous radiances from the ultraviolet (UV) at 240 to 1750 nm in the shortwave-infrared (SWIR), at a moderate spectral resolution of 0.2 to 1.5 nm. However, the spatial resolution and global coverage of SCIAMACHY was limited, and Envisat stopped delivering data in 2012. In order to continue the DRE data retrieval, reflectances from OMI and MODIS, flying in formation, were combined from the UV to the SWIR. This resulted in reflectances at a limited but sufficient spectral resolution, available at the OMI pixel grid, which have a much higher spatial resolution and coverage than SCIAMACHY. The combined reflectance spectra allow the retrieval of cloud microphysical parameters in the SWIR, and the subsequent retrieval of aerosol DRE over cloud scenes using the DAA technique. For liquid cloud scenes in the south-east Atlantic region with cloud fraction (CF) >0.3, the area-averaged instantaneous aerosol DRE over clouds in June to August 2006 was 25 Wm−2 with a standard deviation of 30 Wm−2. The maximum area-averaged instantaneous DRE from OMI–MODIS in August 2006 was 75.6±13 Wm−2. The new aerosol DRE over-cloud dataset from OMI–MODIS is compared to the SCIAMACHY dataset for the period 2006 to 2009, showing a very high correlation. The OMI–MODIS DRE dataset over the Atlantic Ocean is highly correlated to above-cloud AOT measurements from OMI and MODIS. It is related to AOT measurements over Ascension Island in 2016, showing the transport of smoke all the way from its source region in Africa over the Atlantic to Ascension and beyond.
Evaluation of radicular dentin thickness of danger zone in mandibular first molars.

Objective: To determine the prevalence and correlated factors of self-reported oral malodor in Thai dental patients from Chulalongkorn Dental Hospital. Materials and Methods: A self-administered questionnaire was developed to assess the self-reported perception of oral malodor in 839 patients. Significant associations between self-perceived oral malodor and sociodemographics, oral problems and oral hygiene practice variables were determined by Chi-square test. Results: The prevalence of currently self-perceived oral malodor was 61.1%. A higher prevalence of self-perceived oral malodor was significantly correlated with a number of factors including being 30 years of age or older, having a high school or lower educational level, tongue coating, xerostomia, bleeding when brushing teeth, never receiving professional tooth cleaning and a lower toothbrushing frequency. However, multivariable analysis showed that tongue coating was the factor most strongly associated with self-perceived oral malodor (OR=3.53; CI=2.05-6.08), followed by bleeding when brushing teeth (OR= 2.96) and being 30 years of age or older (OR=2.46). Subjects with oral malodor perceived by themselves and others had a higher level of self-perceived oral malodor, a higher prevalence of bad odor when talking, in the morning and throughout the whole day, and a higher prevalence of consulting with other people in comparison with those with perception by themselves alone. Conclusion: Tongue coating, bleeding when brushing teeth and being 30 years of age or older were significantly associated with self-perceived oral malodor. The level of selfperceived oral malodor and consulting with other people was more prevalent in subjects with oral malodor perceived by themselves and others.