Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Comparison of Optimal Fractional Order Power System Stabilizer for Multi-Machine Power System

In this paper, a novel optimal fractional order Power System Stabilizer (FoPSS) is designed for a multi-machine power system. The new population-based, meta-heuristic Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) are used to design the Power System Stabilizer (PSS). As the complexity of the power system increases drastically, continuous small changes in the load side cause small disturbances and will result in small-signal oscillations. To damp out this oscillation, PSS is equipped with a power system to provide positive damping. Two area four machine power system is considered as a study model. The comparative performance of Fractional order PSS tuned by PSO (PSOFoPSS) and Fractional order PSS tuned by GWO (GWOFoPSS) are evaluated by considering Integral of Time Multiplied Absolute Error (ITAE) as the performance index. A novel biquadratic approximation method is used to realize the designed FoPSS. The non-linear time simulation of deviation in speed are plotted along with convergence characteristics of the optimization algorithm. The comparative analysis depicted that PSOFoPSS outperforms the GWOFoPSS and Conventional PSS.
An Improved Feature-Based Visual Slam Using Semantic Information

The traditional visual slam method for feature extraction is single and has poor robustness. This paper proposes an improved feature-based SLAM (Simultaneous localization and mapping) by adding weights to the features of objects matching the same semantic category and incorporating semantic information into loop closure detection. The basic idea is to use the deep neural network YOLOV5 to classify things, associate feature points with objects appearing in the bounding box, and thus assign the feature points to the semantic labels of these objects. In the feature matching process of the SLAM algorithm, the matching of feature points with the same semantic label will be weight, which increases the matching of similar features on the same category of objects, and at the same time intefrates semantic information into loop detection to improve the accuracy of loop closure detection. The test results show that the absolute trajectory error of the improved algorithm is more minor, the pose estimation accuracy is higher, and the tracking robustness can be effectively improved.
Direct analysis of microbial populations in soil and fresh- water aquifers using nucleic acid based techniques

The first DNA-based methods for direct quantification of soil protozoa, and a DNA-based quantification method to describe the spread of phenanthrene-degrading bacteria in soil and freshwater aquifers, have recently been developed at the BIOPRO Research Centre at the Geological Survey of Denmark and Greenland (GEUS). Well-known genes for phenoxyalcanoic acid degradation have been used to monitor the in situ degradation of phenoxyalcanoic acid pesticides. Studies have been initiated on the short-lived mRNA molecules that are expected to provide a shortcut to the understanding of low, yet important, microbial activity in geological samples. This article reviews recent developments in techniques based on analysis of nucleic acids from soils and aquifers. Analytical work has been carried out mainly on soil samples from a former asphalt production plant at Ringe (Fig. 1). The Ringe plant constitutes one of the most polluted industrial sites in Denmark, and is a priority site of studies by the BIOPRO Research Centre. Although rich in carbon, the Ringe subsoil is an oligotrophic environment due to the high content of polycyclic aromatic hydrocarbons (PAH). This is an environment where the supply of nutrients to microorganisms is low, leading to slow growth, low total numbers of microorganisms and small cells. To study microbial communities of oligotrophic environments, analytical methods with low detection limits are needed. Until recently, microorganisms of natural environments were mainly studied by cultivation-dependent methods. However, microorganisms that can be cultured on agar plates are now known to represent only a small fraction of the total microbial community. Modern methods, therefore, need to be based on the detection of biomolecules in the microorganisms rather than being dependent on growth of the microorganisms. The best available techniques are based on DNA and RNA molecules (Fig. 2), which due to their high level of resolution allow closely related organisms or functional genes to be distinguished. In the following review, examples are given of applications of these nucleic acid based methods.
Diet effects on the short-term temporal dynamics of the equine hindgut microbiota

Horses’ living conditions have changed through thousands of years; altering their diets, that no longer fit the horse’s physiology. Horses were free-ranging grazing animals and their digestive system is therefore adapted to cope with large quantities of fibrous feeds. Mixed roughage and concentrate diets will consequently affect how horses utilize nutrients. In order to optimize feeding rations, it is important to understand how the hindgut microbiota reacts when different diets are presented. The aim of this thesis was therefore to investigate the short-term temporal dynamics of the equine hindgut microbiota by using 16S rRNA gene and shotgun metagenomic sequencing. The microbiota and associated metabolic products were compared to investigate the diet effects on the equine hindgut microbiota, through cecal content collected in a time period of 24 hours from four cecally cannulated horses, given two different diets. Additional fecal samples were also collected in the same time range, to investigate whether fecal samples could represent the microbial population of the cecum. The detected dominant bacterial phyla, in equine cecum, comprised of the predominating phyla Firmicutes and Bacteroidetes, followed by the phyla Verrucomicrobia, Proteobacteria, Tenericutes, Spirochaetes, Cyanobacteria and Fibrobacteres. Based on the observed temporal patterns of the microbiota, we propose a model where the fibrolytic bacteria Fibrobacter succinogenes produce SCFA that lead to a pH decrease in the cecum and the resurgence of lactic acid-producing Streptococcus spp. , where ultimately growth of lactate utilizing Anaerovibrio spp. are believed to prevent the accumulation of lactate in the cecum for a prolonged period of time. Further, the cecal content and feces showed significant difference, suggesting that feces cannot represent the cecal microbiota in a proper way. This study provides a foundation for further understanding of the equine hindgut microbiota and its function, allowing production of feeds that are more adapted to this intestinal ecosystem and may prevent diseases in the future.
PROS SEM NAS MASY BIODIV INDON

Sunaryo W. 2015. DNA barcoding application to analyze the genetic diversity of lai-durian (Durio zibethinus x kutejensis) from East Kalimantan. Pros Sem Nas Masy Biodiv Indon 1: 1273-1277. Indonesian local fruit diversity is the important basic factor to increase the competitiveness of the Indonesian fruit against the imported fruit. Lai-durian (Durio zibethinus x kutejensis), the result of a natural crossing between durian (Durio zibethinus) and lai (Durio kutejensis), is an endemic fruit in East Kalimantan having a superior fruit performance and specific taste, therefore lai-durian often win a price in Durian Contest. Even, some of lai-durian varieties have been released as a National superior variety. The exploration and identification of lai-durian genetic diversity have been studied based on morphological characters. The application of molecular marker such as DNA barcoding has a good prospect to analyze the genetic diversity of laidurian and/ or compared to the parents (Durio zibethinus and Durio kutejensis). A new technology in plant identification of DNA barcoding could be performed quickly and accurately because this technique needs a small sample and could discriminate new variation on the undescribed species. In addition, DNA barcoding could be carried out even by a non-taxonomist expert, with the same accuracy, because it is a high reproducible technique. On the other hand, the identification of species or varieties based on morphological characters (Taxonomy keys) performed by taxonomist is usually applied in mature/adult plant, therefore it needs longer time because of more time to wait until the plant blooming or fruiting. In addition, the morphological character observation requires a taxonomist experts that are recently very limited.Therefore, here we describe the future prospect of DNA barcoding application to analyze the genetic diversity of lai-durian from East Kalimantan.
Nectar volume is positively correlated with flower size in hummingbird-visited flowers in the Brazilian Atlantic Forest

Abstract: We studied the relationship between flower size and nectar properties of hummingbird-visited flowers in the Brazilian Atlantic Forest. We analysed the nectar volume and concentration as a function of corolla length and the average bill size of visitors for 150 plant species, using the phylogenetic generalized least squares (PGLS) to control for phylogenetic signals in the data. We found that nectar volume is positively correlated with corolla length due to phylogenetic allometry. We also demonstrated that larger flowers provide better rewards for long-billed hummingbirds. Regardless of the causal mechanisms, our results support the hypothesis that morphological floral traits that drive partitioning among hummingbirds correspond to the quantity of resources produced by the flowers in the Atlantic Forest. We demonstrate that the relationship between nectar properties and flower size is affected by phylogenetic constraints and thus future studies assessing the interaction between floral traits need to control for phylogenetic signals in the data.
CHARCOAL COLLECTIONS OF THE WORLD

Charcoal reference collections are very important for identifying unknown charcoal specimens in different contexts (palaeoecological, archaeological, environmental and others) and form an integral part of anthracological studies, which can provide crucial information for researchers of different expertise, as wood anatomy, archaeology, palaeobotany, forestry, forensics, etc. A first inventory on charcoal collections maintained by scientific institutions or private individuals around the world revealed 53 charcoal collections in five continents. There is a high concentration of collections and specimens in Europe, reflecting a better established and longer tradition of charcoal identification in temperate and mediterranean regions. However, research seems to be firmly advancing in other parts of the world, especially in the tropics, where important collections are being established. The great increase observed in the number of existing charcoal collections and their geographical spread in the last years attest to their importance, as well as to the vigour of anthracology in its various approaches. The wood anatomical community is called upon to help fill gaps in this first inventory of charcoal collections.
Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources

Habitat selection can be considered as a hierarchical process in which animals satisfy their habitat requirements at different ecological scales. Theory predicts that spatial and temporal scales should co-vary in most ecological processes and that the most limiting factors should drive habitat selection at coarse ecological scales, but be less influential at finer scales. Using detailed location data on roe deer (Capreolus capreolus) inhabiting the Bavarian Forest National Park, Germany, we investigated habitat selection at several spatial and temporal scales. We tested (i) whether time-varying patterns were governed by factors reported as having the largest effects on fitness, (ii) whether the trade-off between forage and predation risks differed among spatial and temporal scales and (iii) if spatial and temporal scales are positively associated. We analysed the variation in habitat selection within the landscape and within home ranges at monthly intervals, with respect to land-cover type and proxys of food and cover over seasonal and diurnal temporal scales. The fine-scale temporal variation follows a nycthemeral cycle linked to diurnal variation in human disturbance. The large-scale variation matches seasonal plant phenology, suggesting food resources being a greater limiting factor than lynx predation risk. The trade-off between selection for food and cover was similar on seasonal and diurnal scale. Habitat selection at the different scales may be the consequence of the temporal variation and predictability of the limiting factors as much as its association with fitness. The landscape of fear might have less importance at the studied scale of habitat selection than generally accepted because of the predator hunting strategy. Finally, seasonal variation in habitat selection was similar at the large and small spatial scales, which may arise because of the marked philopatry of roe deer. The difference is supposed to be greater for wider ranging herbivores. This article is protected by copyright. All rights reserved.
Aromatic Acid and Flavonoids from the leaves of Zanthoxylum piperitum

Five flavonoids and one aromatic acid were isolated from the leaves of Zanthoxylum piperitum. The structures of compounds were elucidated as quercetin, afzelin, quercitrin, hyperoside, hesperidin and protocatechuic acid on the basis of spectral evidence.
Mitigation of High-Frequency Oscillation in a Multiport DC-DC Converter

High-gain current-fed multiport dc-dc converters with hybrid energy storage systems such as low-voltage batteries and super capacitors (SCs) are commonly used in Electric Vehicle (EV) applications. Even when the battery and SC voltages fluctuate, the transformer voltages can always be perfectly matched because of easy power flow between any two ports and low circulating power. Furthermore, interleaved control reduces current ripple, which is beneficial to both batteries and SCs. In a high-frequency transformer, stray capacitance and phase shift inductance form a high-frequency oscillation (HFO), and the high dv/dt of the dual active bridge (DAB) converter degrades performance. A frequency-domain model that considers the parasitic properties of the circuit is useful in understanding the phenomenon of High-Frequency Oscillation (HFO). Based on this model, the present study reveals that the HFO can be reduced by regulating the dv/dt at the H-bridge (Primary) output voltage. If the dv/dt is very high or very low the HFO prevails. Thus, there is a specific range for the dv/dt to effectively limit the HFO. In the present study, the extent of HFO is significantly reduced by the use of parallel capacitance at the switching devices. Further, this enables soft switching and reduces the losses. The capacitance to be connected is determined by identifying the Zero Crossing Points (ZCPs) corresponding to the oscillation frequency in the DAB output voltage. The proposed model facilitates the computation of the capacitance values needed for the desired range of dv/dt that limits the HFO. This in turn helps to improve overall efficiency. Simulation results demonstrate the efficacy of the scheme.
Impact of Drought and Temperature on Growth and Leaf Gas Exchange of Six Bedding Plant Species Under Greenhouse Conditions

The effect of drought on the growth and gas exchange of six bedding plant species-agastache [Agastache urticifolia (Benth.) O. Kuntze 'Honeybee Blue'], dusty miller (Cineraria maritima L. 'Silverdusty'), petunia (Petunia xhybrida 'Wave Purple'), plumbago (Plumbago auriculata Lam. 'Escapade'), ornamental pepper (Capsicum annuum L. 'Black Pearl'), and vinca [Catharanthus roseus (L.) G. Don 'Titan']-was quantified under greenhouse conditions. Seeds were sown in January and seedlings were grown in the greenhouse until 18 Apr., when two irrigation treatments-drought (D, ≈18% volumetric moisture content at reirrigation) and control (C, ≈25% volumetric moisture content at reirrigation)-were initiated. Leaf net photosynthetic rate (P n ), stomatal conductance (g s ), and transpiration (E) were determined in response to a range of substrate moisture content (from ≈5% to 30% by volume) and temperature (from 20 °C to 40 °C). Dry weight of agastache, ornamental pepper, and vinca was unaffected by drought, whereas that of other species was reduced. Leaf area of plumbago and height of plumbago and vinca were reduced by drought. As substrate moisture content decreased from 25% to 10%, P n , E, and g s decreased linearly in all species except petunia and plumbago. Leaf net photosynthetic rate of all species declined as leaf temperature increased from 20 °C to 40 °C. In contrast, E of all species, except petunia, increased as temperature increased. Transpiration rate of petunia increased as temperature increased from 20 °C to 30 °C, and then decreased between 30 °C and 40 °C. Although petunia had the highest P n among the tested species, its P n and g s declined more rapidly compared with the other species as temperature increased from 20 °C to 40 °C or as substrate moisture content decreased, indicating that petunia was most sensitive to high temperature and drought.
The early warning model of HFMD which is implemented by the multivariable deep learning neural network

At present, many neural networks have achieved good results in disease prediction. For hand foot mouth disease(HFMD), mastering its epidemic law can provide scientific basis for effective formulation of prevention and control measures. However, most existing models use SIER infectious disease dynamics model, seasonal difference moving ARIMA or RNN, LSTM and other traditional networks to predict, and do not take climate and other factors into account. In this paper, firstly, a new data set is established, and BiLSTM is used to predict hand, mouth and foot disease. In addition, climate factors are taken into account in the prediction process. Thirdly, we conducted the Controlled experiment with the traditional models to calculate their MAE, MSE, RMSE, MAPE and other evaluation values. And the experiment shows that robustness of BiLSTM model in HFMD is better than these models. Finally, we analyzes the model from the perspective of time step, and sets the time step to 7 days, 14 days, and 21 days. It is found that when the time step is 14 days, the prediction performance is the best. Finally, we also made a comparative analysis through ablation experiments, and found that the HFMD dataset with meteorological factors was better than the HFMD dataset without meteorological factors in prediction accuracy.
Deep Learning Based Lumbar Metastases Detection and Classification from Computer Tomography Images

Metastasis in the vertebral body is a widely observed malignant disease. This study used Computer Tomography (CT) images of the lumbar region to detect and classify the metastases from the normal vertebral bodies. We also classify the two types of metastases; Sclerotic and Lytic. Segmentation of the vertebral body is done using a deep neural network. We compared the performance of our model with existing state-of-art models. Multi-resolution blocks in the proposed model help segment the vertebral body with lytic lesions in the margin of the region of interest. Through Wavelet image transformation, coefficients are derived from the vertebral region. Based on the extracted wavelet scattering features, vertebral bodies are classified into three classes; normal, sclerotic and lytic, using Principal Component Analysis (PCA).
More nodes in fake news participate in multiple networks

Fake news and real news are different in many aspects. Many scholars analyze from the perspective of text, users and so on. This paper compares and analyzes these two types of information from the aspect of network structure: community detection. We found that the number of participating networks is larger in the fake news, the participation in the fake news multi-network is stronger, and the size of the community of fake news is more average. This abnormal spread pattern could be a feature of fake news identification and motivate future studies in this direction.
Application of Gaussian Filtering Three-Frame Difference Method in Moving Target Detection System

Aiming at the problem of low detection accuracy and poor noise robustness of moving target detection algorithm, this paper studies a moving target detection system combining three-frame difference method and Gaussian model, which adopts inter-frame difference and threshold segmentation to extract the moving region in the image, and further enhances the accuracy and practicability of the three-frame difference method. Experimental results show that compared with the single TFDM algorithm, this system has higher detection accuracy and better robustness to noise than the traditional inter-frame difference method and template matching method.
De novo assembled transcriptome of horned gall aphid, Schlechtendalia chinensis Bell, suggest changes in functional gene expression during host alternation

The horned gall aphid, Schlechtendalia chinensis Bell, is the most economically valuable galling aphid. It accounts for approximately 75% of Chinese gallnut production, which is important for medical and chemical purposes. The horned gall aphid feeds on the Chinese sumac tree, Rhus chinensis, during the summer, induces galls, and overwinters on the moss Plagiomnium spp. However, the sequence information of S. chinensis is limited, and the functional gene expression changes during host alternation remain obscure. In this study, the transcriptome of the horned gall aphid was sequenced using high‐throughput sequencing technology. Approximately 49 million reads were obtained and were assembled into 99 366 transcripts and 47 400 unigenes. Annotation was performed using a BLAST search against primary databases such as NCBI nr and Swiss‐Prot, as well as enrichment analysis by GO, KOG and KEGG. Differentially expressed genes between spring and autumn migrant aphids were compared, and the expression levels of many genes related to detoxification, digestion and other functional genes were found to have changed, reflecting the adaptation ability of horned gall aphids in different seasons and hosts. Functional genes in wax biosynthesis were upregulated in spring migrant aphids. This study analyzed the expression profile difference between spring and autumn migrant aphids to approach the real functional genes change during host alternation. The transcriptome provides a basis to understanding the functional genes during gall aphid host alternation and the related physiological and molecular characteristics.
Deep Learning Fuzz Testing Methods for Unstructured Case

Fuzz testing is to modify a large number of test cases by variation to find out the anomalies and vulnerabilities in target program. The Seq2Seq based fuzzing model, can automatically generates test cases that may cover the new path by learning the relationship between the initial seed cases and the corresponding execution path, and thus achieves better fuzz testing performance for structured cases. For unstructured cases, however the Seq2Seq model has two problems. In this paper, we propose a new deep learning testing model based on attention and scheduled sampling for unstructured cases. The model introduces an attention probability distribution on the input information sequences, and adopts decoders twice to generate input sequences by mixing the real information sequences with the predicted sequences. The model improves the coverage of execution paths in target program, and triggers more bugs.