Miracle-dz/UniFAR-FTUs huggingface dataset:
Pavlović, D., Zlatković, B., Živanović, S., Kitić, D., Golubović, T.: Serbian Rutaceae species: comparison of flavonoid contents, coumarin compounds and radical scavenging activity. Biologica Nyssana, 9 (1). September, 2018: 37-43

Pavlović, D. , Zlatković, B. , Živanović, S. , Kitić, D. , Golubović, T. : Serbian Rutaceae species: comparison of flavonoid contents, coumarin compounds and radical scavenging activity. Biologica Nyssana, 9 (1). September, 2018: 37-43. Family Rutaceae is presented in Serbian flora with 3 genera and 4 species: Ruta graveolens L. , Dictamnus albus L. , Haplophyllum suaveolens (DC.) G. Don and H. boissieranum Vis. & Pančić. Comparative study of the phytochemical variability and antioxidant activity of ethanolic and methanolic extracts, obtained from these species’ areal parts, was performed. Total flavonoid content was determined spectrophotometrically and HPLC method was employed for quantification of coumarins. Fast antioxidant screening of samples was done in DPPH test. Flavonoid content of the tested samples varied from 2.82±0.27 to 27.72±0.15 mg of rutin equivalent (Ru)/g of extract. Psoralen, bergapten and xanthotoxin were detected and quantified only in R. graveolens extracts. All the tested samples exhibited notable potential in DPPH radicals scavenging assay. Yet, considerably lower activity was measured for Haplophyllum extracts. The present study brings forward the new data regarding the chemical profiles and antiradical activities of named Rutaceae species.
Multiple Lines of Evidence for Estimating NSZD Rates Overlying a Shallow LNAPL Source Zone

Quantitative methods of monitoring natural source zone depletion (NSZD) via biodegradation of petroleum hydrocarbons (PHC) are required to investigate source zone longevity and guide long‐term management of PHC impacted sites. Vadose zone NSZD processes can be monitored using analysis of surficial CO2 effluxes, soil‐gas gradients, and thermal gradients. This study describes an applied research and development program conducted at a former refinery site over a 4‐year period (2015 to 2019) on quantitative technologies for evaluation of NSZD of PHC light nonaqueous phase liquid (LNAPL) present within a shallow soil zone. A multiyear study using discrete CO2 efflux measurements from dynamic closed chambers was compared with estimates obtained using static traps and continuous monitoring using forced diffusion (FD) technology. Thermistor strings along a transect were used to monitor hourly thermal gradients and assess NSZD rates using the temperature gradient method. Discrete soil‐gas data were used to quantify the vertical oxygen gradient to estimate NSZD rates using the concentration gradient method (CGM). Results of discrete and continuous monitoring methods provide estimates of monthly NSZD rates that range seasonally from 80 to 1300 US gal/acre/year using radiocarbon corrected CO2 efflux method for decane (C10H22) equivalent, 120 to 1600 US gal/acre/year using CGM (for wet to dry conditions) and 400 to 2000 US gal/acre/year using the temperature gradient method. Both seasonal temperature and precipitation fluctuations contribute to variability in rates. Continuous methods are shown to provide for improved resolution of temporal variability and seasonal estimates, although discrete methods provide for improved spatial quantification.
USING SEMANTIC LAYER PROJECTION FOR ENHANCING MUSIC MOOD PREDICTION WITH AUDIO FEATURES

We propose a novel technique called Semantic Layer Pro-jection (SLP) for predicting moods expressed by music based on audio features. In SLP, the predictive models are formed by a two-stage mapping from audio features to listener ratings of mood via a semantic mood layer. SLP differs from conventional techniques that produce a direct mapping from audio features to mood ratings. In this work, large social tag data from the Last.fm music service was analysed to produce a semantic layer that represents mood-related information in a low number of dimensions. The method is compared to baseline techniques at predicting the expressed Valence and Arousal in 600 popular music tracks. SLP clearly outperformed the baseline techniques at predicting Valence ( R 2 = 0 . 334 vs. 0 . 245 ), and produced roughly equivalent performance in predicting Arousal ( R 2 = 0 . 782 vs. 0 . 770 ). The difﬁculty of modelling Valence was highlighted by generally lower performance compared to Arousal. The improved prediction of Valence, and the increasingly abundant sources of social tags related to digital music make SLP a highly promising technique for future developments in modelling mood in music.
Object Detection of Millimeter Wave Radar Based on Computer Vision

Millimeter-wave (MMW) radar is an indispensable sensor for smart cars to realize environmental perception because it is not affected by light and weather. The current MMW radar can provide information about the position and velocity of an object but it is not easy to directly obtain classification information. In this paper, a radar object detection method based on computer vision is proposed. To enable the object detection network to learn the information returned by the radar, a method to convert the radar cluster information into 3 channel RGB image is proposed, and two feature expression forms are constructed. This transformation allows image-based detection to be applied to radar data. The Darknet53-based object detection network is compressed by one-third based on the filter similarity. The test results on campus data collected from real vehicles show that the compressed network achieves almost the same detection performance with fewer parameters.
Membrane Internalization Mechanisms and Design Strategies of Arginine-Rich Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) have been discovered to deliver chemical drugs, nucleic acids, and macromolecules to permeate cell membranes, creating a novel route for exogenous substances to enter cells. Up until now, various sequence structures and fundamental action mechanisms of CPPs have been established. Among them, arginine-rich peptides with unique cell penetration properties have attracted substantial scientific attention. Due to the positively charged essential amino acids of the arginine-rich peptides, they can interact with negatively charged drug molecules and cell membranes through non-covalent interaction, including electrostatic interactions. Significantly, the sequence design and the penetrating mechanisms are critical. In this brief synopsis, we summarize the transmembrane processes and mechanisms of arginine-rich peptides; and outline the relationship between the function of arginine-rich peptides and the number of arginine residues, arginine optical isomers, primary sequence, secondary and ternary structures, etc. Taking advantage of the penetration ability, biomedical applications of arginine-rich peptides have been refreshed, including drug/RNA delivery systems, biosensors, and blood-brain barrier (BBB) penetration. Understanding the membrane internalization mechanisms and design strategies of CPPs will expand their potential applications in clinical trials.
Molecular characterization of Clinical carbapenem-resistant Acinetobacter baumannii isolates from two tertiary care hospitals in Indonesia

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) is an important pathogenic bacterium that can cause nosocomial infection in hospitalized patients with various manifestations. The purposes of this recent study were to determine the prevalence, antimicrobial susceptibility profiles, carbapenemase-producing phenotypic and genotypic of CRAB in two tertiary care hospitals in Indonesia. Methods: A. baumannii isolates collected from patient’s clinical cultures in two tertiary care hospitals in Malang and Manado were included. Identifications of meropenem-resistant A. baumannii isolates with the vitek2® system results, followed by a sensitivity test using 10 µg imipenem antibiotic disc according to CLSI guidelines to fulfill the criteria as CRAB isolates. We assessed carbapenemase-production using mCIM and eCIM, and determined the presence of blaKPC, blaNDM, blaOXA-23 carbapenemase resistance genes using simplex PCR. Results: 73 CRAB were collected from hospitalized patients, of which 30 CRAB from Manado and 43 CRAB from Malang. The largest number of samples came from sputum and indicates that XDR has also occurred in all CRAB isolates. Carbapenemase-production test using mCIM obtained positive results on 29 samples (96.7%) and 42 samples (97.7%) in Manado and Malang, respectively. The eCIM showed metallo-β-lactamase was dominant in two tertiary care hospitals. The prevalence of carbapenemase resistance genes was obtained blaOXA-23 and blaNDM ranged between 60% - 90.7% and 3.3% - 4.6%, respectively. blaKPC gene was not detected. Conclusions: We showed that CRAB isolates positive result of carbapenemase-production and carbapenemase resistance genes of blaOXA-23 seem to be dominant in two tertiary care hospitals in Malang and Manado, Indonesia. A national prevention and surveillance system should be prepared to reduce and limiting transmission of CRAB isolates.
Level one industrial automation : choosing network control systems

Data mining techniques and public information available on industrial automation (IA) company websites were used to classify the product or service offers of 214 IA companies and Network Control Systems. Based on the market offer description, the results suggest that the clustering of IA companies can be grouped this way: (i) concentrates on specific features (key words) in choosing the NCS; (ii) two NCSs (protocols) as the choice for level one in IA depending on usage (Ethernet or ModBus); (iii) one suggested NCS (LAN) as the choice for level one in IA for all their offers; and (iv) a choice between three NCSs (ModBus, Ethernet, or LAN) as the choice for level one in IA. The results indicate that the applications in industrial automation can be divided into three types: general applications, secured applications and non secured applications. A selection guide is presented based on specific keywords.
Reducing tillage intensity benefits the soil micro‐ and mesofauna in a global meta‐analysis

Soil fauna drives crucial processes of energy and nutrient cycling in agricultural systems, and influences the quality of crops and pest incidence. Soil tillage is the most influential agricultural manipulation of soil structure, and has a profound influence on soil biology and its provision of ecosystem services. The objective of this study was to quantify through meta‐analyses the effects of reducing tillage intensity on density and diversity of soil micro‐ and mesofaunal communities, and how these effects vary among different pedoclimatic conditions and interact with concurrent management practices. We present the results of a global meta‐analysis of available literature data on the effects of different tillage intensities on taxonomic and functional groups of soil micro‐ and mesofauna. We collected paired observations (conventional vs. reduced forms of tillage/no‐tillage) from 133 studies across 33 countries. Our results show that reduced tillage intensity or no‐tillage increases the total density of springtails (+35%), mites (+23%), and enchytraeids (+37%) compared to more intense tillage methods. The meta‐analyses for different nematode feeding groups, life‐forms of springtails, and taxonomic mite groups showed higher densities under reduced forms of tillage compared to conventional tillage on omnivorous nematodes (+53%), epedaphic (+81%) and hemiedaphic (+84%) springtails, oribatid (+43%) and mesostigmatid (+57%) mites. Furthermore, the effects of reduced forms of tillage on soil micro‐ and mesofauna varied with depth, climate and soil texture, as well as with tillage method, tillage frequency, concurrent fertilisation, and herbicide application. Our findings suggest that reducing tillage intensity can have positive effects on the density of micro‐ and mesofaunal communities in areas subjected to long‐term intensive cultivation practices. Our results will be useful to support decision making on the management of soil faunal communities and will facilitate modelling efforts of soil biology in global agroecosystems.
A Spatiotemporal Directed Graph Convolution Network for Ultra-Short-Term Wind Power Prediction

The expansion of wind generation and the advance in deep learning have provided feasibility for multisite wind power prediction motivated by spatiotemporal dependencies. This paper introduces a novel spatiotemporal directed graph convolution neural network to sufficiently represent spatiotemporal prior knowledge and simultaneously generate ultra-short-term multisite wind power prediction. At first, a spatial dependency-based directed graph is established to learn the intrinsic topology structure of wind farms taking sites as graph nodes and Granger causality-defined spatial relation as directed edges. Subsequently, a unified spatiotemporal directed graph learning model is presented by embedding the multi-scale temporal convolution network as a sub-layer into the improved graph convolution operator, where the temporal features of each node are extracted by the above sub-layer to capture time patterns with different lengths, and the improved graph convolution layer is introduced by redefining K-order adjacent nodes to further share and integrate the deep spatiotemporal knowledge on the graph containing temporal features. Finally, under a comprehensive training loss function, this method is capable of improving the accuracy of each site for 4h-ahead prediction along with decent robustness and generalization. Experiment results verify the superiority of the proposed model in spatiotemporal correlation representation compared with classic and advanced benchmarks.
Design and Fabrication of High-Frequency Piezoelectric Micromachined Ultrasonic Transducer Based on an AlN Thin Film

A piezoelectric micromachined ultrasonic transducer (PMUT) is a microelectromechanical system (MEMS) device that can transmit and receive ultrasonic waves. Given its advantages of high-frequency ultrasound with good directionality and high resolution, PMUT can be used in application scenarios with low power supply, such as fingerprint recognition, nondestructive testing, and medical diagnosis. Here, a PMUT based on an aluminum nitride thin-film material is designed and fabricated. First, the eigenfrequencies of the PMUT are studied with multiphysics coupling simulation software, and the relationship between eigenfrequencies and vibration layer parameters is determined. The transmission performance of the PMUT is obtained via simulation. The PMUT device is fabricated in accordance with the designed simple MEMS processing process. The topography of the PMUT vibration layer is determined via scanning electron microscopy, and the resonant frequency of the PMUT device is 7.43 MHz. The electromechanical coupling coefficient is 2.21% via an LCR tester.
ASYMPTOTIC BEHAVIOR OF THIN ELASTIC INTERPHASES

The asymptotic behavior of a linearly elastic composite material that contains a thin interphase is described and analyzed by means of two complementary methods: the asymptotic expansions method and the study of the weak form using variational methods on Sobolev spaces. We recover the solution of the system of linearized elasticity in the two dimensional vectorial case and we find limit transmission conditions. The same steps are followed for harmonic oscillations of the elasticity system, and different solutions are found for concentrated mass densities. The cases in which the elastic coefficients depend on the thickness of the small parameter, for soft as well as stiff materials are considered. An approximated solution is found for harmonic oscillations of the elasticity system and limit transmission conditions are derived. Considering a bounded rectangular composite domain, with a thin interphase, we describe the weak formulation of the linearized system of elasticity. In the case of constant elastic coefficients, we estimate the bounds of the strain tensor and so, the energetic functional in the rescaled domain. We perform a variational formulation of the system of linearized elasticity and find estimates for the energetic functional of the system.
Adrenal Near-Infrared Autofluorescence

Abstract Context Parathyroid tissue is one of the few tissues to have strong near-infrared (NIR) autofluorescence, which has been exploited to improve intraoperative parathyroid identification. The US Food and Drug Administration has approved 2 devices for this purpose. Adrenal glands can be difficult to distinguish from surrounding fat, an issue during total adrenalectomy. Objective We hypothesized adrenal tissue may also possess considerable NIR autofluorescence. Methods Resected patient adrenal specimens were examined after robotic adrenalectomy with an NIR camera intraoperatively. Patients did not receive fluorescent dye. Images were taken of both gross and sectioned specimens. Post hoc image analysis was performed with ImageJ software. Confocal microscopy was performed on selected tissues using immunofluorescence and hematoxylin-eosin staining. Results Resected tissue was examined from 22 patients undergoing surgery for pheochromocytomas (6), primary aldosteronism (3), adrenocorticotropin-independent hypercortisolism (10), and a growing or suspicious mass (3). Normal adrenal tissue demonstrated strong NIR autofluorescence. The intensity ratio compared to background (set as 1) for gross images was 2.03 ± 0.51 (P < .0001) compared to adjacent adipose of 1.24 ± 0.18. Autofluorescence from adrenal tumors was also detected at variable levels of intensity. Cortisol-producing tumors had the highest fluorescence ratio of 3.01 ± 0.41. Confocal imaging localized autofluorescence to the cytosol, with the highest intensity in the zona reticularis followed by the zona fasciculata. Conclusion Normal and abnormal adrenal tissues possess natural NIR autofluorescence. Highest autofluorescence levels were associated with cortisol-producing tumors. Confocal imaging demonstrated the highest intensity in the zona reticularis. NIR cameras may have the potential to improve identification of adrenal tissue during surgery.
A Fuzzy AHP-Fuzzy TOPSIS Urged Baseline Aid for Execution Amendment of an Online Food Delivery Affability

The increased demand for this form of food delivery has been expected to drastically alter restaurant patrons’ dining habits. As people have been forced to stay indoors to prevent the virus from spreading, food delivery services over the internet are in high demand. As established in this study, the planned ideal is a good executive implementation for online meal delivery services. Food delivery services are rapidly growing in India, opening up several opportunities for a wide range of online food delivery (OFD) platforms while also generating a competitive commercial sector. Following that, the fuzzy technique for order performance by similarity to ideal solution method (FTOPSIS) is used to rank online food delivery (OFD) enterprises based on the characteristics chosen. In this paper, we study the present multi-criteria decision-analysis (MCDA) paradigm based on the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method to achieve the goal. After that, a hierarchy multiple criteria decision-analysis (MCDA) model based on fuzzy sets theory is introduced to deal with the online food delivery Service in the chain system. The fuzzy analytic hierarchy process (FAHP) is a fuzzy set theory technique for generating criteria weights, which are then used to interpret expert phonological evaluation statements.
Combined displacement estimation and segmentation of stereo image pairs based on Gibbs random fields

A technique for displacement estimation in stereo image pairs, which is closely coupled with a segmentation of the images into homogeneously displaced regions, is described. An arbitrary initial displacement field is modified by a displacement vector relaxation, evaluating a statistical optimization criterion. Since the displacements are considered vector by vector during the relaxation, the method provides accurate locations of the boundaries between differently displaced regions. The proposed technique derives its power from the fact that the spatial array of displacements-and hence the resulting segmentation-is modeled by a Gibbs-Markov random field. <<ETX>>
Needle Penetration Simulation: Influence of Penetration Angle and Sample Stress on the Mechanical Behaviors of Polymers Applying a Cast Silicone and a 3D-Printed Resin

For surgical catheterization training applications, realistic and effective materials are desired. In this study, the relevance of a needle puncture angle and a simulated wall stress on different elastic materials were determined in a previously developed experimental setup. Both settings were considered individually in two new setups. In addition, a control setup with neither angle nor prestress was designed. During the process of puncturing the samples of two materials (Replisil 9N and Formlabs Elastic 50A), force–displacement values were collected, and three predefined parameters evaluated. The differences between the angled/stressed groups and the control group were analyzed. The additively processed material required a significantly higher force to puncture than the conventional one (p < 0.001). Moreover, a needle angulation of 45° required more force than puncturing orthogonally. Prestressing the samples did not clearly influence the resulting force. An evaluation of relative parameters showed that the investigated materials behaved differently but not linearly differently under the influence of needle angle and prestress. Therefore, it is essential to evaluate the properties and suitability of materials for surgical training models in appropriate experimental setups considering multiple parameters.
Interactome of PTH-Regulated miRNAs and Their Predicted Target Genes for Investigating the Epigenetic Effects of PTH (1–34) in Bone Metabolism

Osteoporosis is a metabolic bone disease that mostly affects the elderly. A lot of drugs are available, mostly with an antiresorptive effect but just a few with an osteoanabolic effect, meaning they promote bone building. PTH (1-34) or teriparatide is an osteoanabolic drug, but its efficacy varies between individuals. We performed a literature review and extracted a dataset of 62 microRNAs (miRNAs) from 10 different studies; predicted miRNA target interactions (MTIs) were obtained with the help of four software tools: DIANA, miRWalk, miRDB and TargetScan. With the construction of an interactome of PTH-regulated miRNAs and their predicted target genes, we elucidated miR-146a-5p, miR-551b-5p, miR-205-3p, miR-33a-3p, miR-338-5p as miRNAs with the most interactions and miR-410-3p as the miRNA targeting bone-related pathways with the highest significance. These miRNAs could help in further understanding the mechanism of action of PTH on bone metabolism and osteoporosis. They also have the potential for novel network-based biomarkers for osteoporosis treatment efficacy and safety and as new therapeutic targets.