Miracle-dz/UniFAR-FTUs huggingface dataset:
Bolus Inflow Detection Method by Ultrasound Video Processing for Evaluation of Swallowing

To prevent aspiration pneumonia, a system for non-invasive and quantitative evaluation of the swallowing function is required. Therefore, we have previously proposed a method of using ultrasound videos to establish evaluation indicators of the swallowing function. The proposed method aims to automatically estimate the velocities of the esophageal wall region and the bolus region in the ultrasound video. In this method, estimation of the bolus region comprises two steps: estimating the esophageal region through which the bolus flows and extracting only the frame in which the bolus passes through the esophageal region. However, the step of extracting the frame in which the bolus passes is still performed manually. Therefore, to automate this step, the purpose of this study was to automatically determine the frame in which the bolus flowed into the screen. This method was tested five times on five healthy adult male subjects by recording a cervical ultrasound video while swallowing a bolus of water. We identified the different elements of the esophageal region in the video by first identifying the esophageal wall region with the maximally stable extremal regions (MSER). Then, we used the luminance histogram of each frame to establish the graph of the histogram similarity. This, in turn, was used to detect a change in the observed region, thus indicating the inflow of the bolus. Moreover, we could distinguish the change caused by the inflow from the change caused by the elevation of the esophageal wall using the velocity results obtained by optical flow estimation in the anterior esophageal wall region. Our results showed that in most cases, the proposed method was successful in recognizing the inflow of the bolus and distinguishing it from the elevation of the esophageal wall. Furthermore, an accuracy sufficient for estimation of the velocity of the bolus was achieved. optical flow, esophagus, bolus, maximally stable extremal regions.
Cadmium(II) and lead(II) extraction and transport through polymer inclusion membranes with 1-alkylimidazole

The formation of cadmium(II) complexes with hydrophobic 1-alkylimidazoles (1-hexylimidazole (1), 1-heptylimidazole (2), 1-octylimidazole (3), 1-decylimidazole (4)) was tested by liquid–liquid partition method. On the basis of the extraction data, stability constants of cadmium(II) and Pb(II) complexes were determined. It had been assumed that differences in the formation of cadmium(II) and lead(II) complexes with alkylimidazoles could be used to separate those ions. The possibility of cadmium(II) and lead(II) ion separation in the transport through polymer inclusion membranes (PIMs) was examined. PIMs comprising of cellulose triacetate, o-nitrophenylpentyl ether, and alkylimidazole (1-4) were used. The membranes were characterized using atomic force microscopy (AFM). The results have shown that cadmium(II) ions are effectively transported through PIMs. The best result achieved for cadmium(II) removal from Cd(II)–Pb(II) solution for PIMs with (4) was 95.5% after 24 h. For this membrane, the separation coefficients for Cd(II)/Pb(II) were 1.62. Best Cd(II)/Pb(II) selectivity coefficients equal to 2.94 were found for (1). The influence of the basicity of carrier molecules on transport kinetics was discussed as well.
Smooth branch of travelling waves for the Gross-Pitaevskii equation in dimension two for small speed

We construct a smooth branch of travelling wave solutions for the 2 dimensional Gross-Pitaevskii equations for small speed. These travelling waves exhibit two vortices far away from each other. We also compute the leading order term of the derivatives with respect to the speed. We construct these solutions by an implicit function type argument.
Bone remodeling during alveolar repair is impaired by RANKL antagonist

Post-menopausal osteoporosis is detrimental to bone metabolism as well as alveolar repair. This osteometabolic disorder is an obstacle to the success of maxillofacial rehabilitations, since a large number of patients are carriers of the disease. Denosumab is widely used as a treatment for post menopausal osteoporosis. This drug exerts an antiabsorptive action by inhibiting RANKL, helping to reduce the bone loss caused by osteoporosis. This study aimed to evaluate the repair bone formed after the extraction of the upper incisor of estrogen-deficient rats treated with anti-RANKL monoclonal antibody. The rats (Rattus novergicus albinus, Wistar) were ovariectomized or SHAM operated (n=36). Half of the ovariectomized rats were treated with osteoprotegerin with an Fc fragment (OPG-Fc; 10mg/kg, twice a week), the other half received saline solution as control. After 30 days the rats had their right upper incisor extracted. After 60 days of extraction, the alveoli were evaluated by immunohistochemical, computerized microtomography and confocal microscopy. The OPG-Fc decreased the percentage of bone volume (BV/TV), thickness (Tb.Th) and number of alveolar trabecules (Tb.N) when compared to groups that received saline solution (p<0.005). The OPG-Fc increased the separation between the trabecules (Tb.Sp) and the porosity (Po.tot) of the reparative alveolar bone (p<0.005). The OPG-Fc decreased immunolabelling for RANKL and TRAP when compared to groups that received saline solution. Treatment with OPG-Fc decreased bone neoformation but preserved preexisting bone tissue. This data is supported by the mineral apposition rate, which showed higher values for OVX/OPG-Fc when compared to the OVX group.
Understanding orientations to participation: overcoming status differences to foster engagement in global teams

ABSTRACT A key challenge facing global teams lies in overcoming status differences in order to elicit participation and input from all members. This study extends prior research – which has focused largely on individual-level factors such as language, culture, and location that create status differences that fracture teams and reduce participation – by examining members’ underlying orientations to participation, team practices that encourage these, and their impacts on global team effectiveness. We draw on a rich multilevel, mixed-method data set consisting of 45 in-depth interviews and a comprehensive analysis of conference calls from 9 global teams in a multinational integrated mining, minerals processing, and manufacturing organization. We identified three orientations to participation (Help, Learn, and Engage). Team-level analysis revealed team practices that encouraged certain orientations to participation to emerge, in particular relationships across sites and input solicitation. Only the Engage orientation was positively associated with overall global team effectiveness. Implications of these findings are discussed.
Facilitating protein denaturation in organic solvent and the contribution to the promoting dispersion of graphite nanoplatelets in a polymer

Denatured proteins, natural macromolecules are very attractive for advanced nanocomposites owing to their multiple functional chemical groups. However, denaturation processes were only successfully conducted in an aqueous environment, limiting their broad applications in hydrophobic polymers. In this study, we report an effective approach of denaturing soy protein at nanoscale in an organic solvent. Further, the denatured soy protein was found to be able to infiltrate between the graphite nanoplatelet (GNP) layers to reduce the thickness of GNPs and improve the dispersion of the nanoparticles in either the suspension or the final polymeric nanocomposites. As a result, remarkable improvements in transparency and electrical conductivity have been achieved for the nanocomposites with the GNPs treated by the denatured soy protein.
Effect of shading in physiological responses, milk yield and quality of Girolando cows

The aim of this study was to evaluate the effect of providing shade to Girolando cows on milk yield and composition, physiological parameters, hemogram and blood pH. Two treatments were used: paddocks with and without shade. Animals were alternately kept in each treatment for a period of 15 days for three times. Milk production was recorded and measurements were taken for rectal temperature, skin surface and udder surface temperatures. A total of 24 blood samples were collected form each cow during the experimental procedure. This was done to compare the mean milk yield and chemical composition as well as physiological and blood parameters. The t-test was applied at 5% significance level. Milk urea was higher when the animals were kept in a shaded area. The morning recording for blood erythrocyte counts hematocrit, milk urea, rectal temperature, skin surface and udder surface temperatures showed interaction with respect to temperature ranges whereas the udder temperature in the afternoon showed a similar response. Girolando cows with 3/4 Holland + 1/4 Gyr and 7/8 Holland + 1/8 Gyr blood levels present an ability to adapt to the environment, and there was no effect of shading on milk yield and composition, physiological and blood parameters evaluated.
LIStEN: L′ band Imaging Survey for Exoplanets in the North

Context. Planetary systems and debris discs are natural by-products of the star formation process, and they affect each other. The direct imaging technique allows simultaneous imaging of both a companion and the circumstellar disc it resides in, and is thus a valuable tool to study companion-disc interactions. However, the number of systems in which a companion and a disc have been detected at the same time remains low. Aims. Our aim is to increase this sample, and to continue detecting and studying the population of giant planets in wide orbits. Methods. We carry out the L′ band Imaging Survey for Exoplanets in the North (LIStEN), which targeted 28 nearby stars: 24 are known to harbour a debris disc (DD) and the remaining 4 are protoplanetary disc-hosting stars. We aim to detect possible new companions, and study the interactions between the companion and their discs. Angular differential imaging observations were carried out in the L′ band at 3.8 μm using the LMIRCam instrument at the LBT, between October 2017 and April 2019. Results. No new companions were detected. We combined the derived mass detection limits with information on the disc, and on the proper motion of the host star, to constrain the presence of unseen planetary and low-mass stellar companion around the 24 disc-hosting stars in our survey. We find that 2 have an uncertain DD status and the remaining 22 have disc sizes compatible with self-stirring. Three targets show a proper motion anomaly (PMa) compatible with the presence of an unseen companion. Conclusions. Our achieved mass limits combined with the PMa analysis for HD 113337 support the presence of a second companion around the star, as suggested in previous RV studies. Our mass limits also help to tighten the constraints on the mass and semi-major axis of the unseen companions around HD 161868 and HD 8907.
Do Satisfied Cellar Door Visitors Want to Revisit? Linking Past Knowledge and Consumption Behaviors To Satisfaction and Intention to Return

This study evaluates the main determinants of wine tourists' intention to revisit the winery cellar door. The proposed tourist behavior model suggests that past wine-related knowledge and behaviors as well as motivation affect satisfaction with the cellar door visit. The model suggests that actual behavior at the cellar door (number of bottles bought and amount of money spent) is dependent on the previously mentioned factors. A survey of wine tourists in the Barossa Valley, Australia, led to 676 useable questionnaires. The results of a binary logistic model show that only monthly household expenditure on wine consumption and the motive of tasting wine predict satisfaction with the cellar door visit. A negative binomial model shows that the probability to buy more bottles at the winery increases if the visitor is from Australia, satisfied with the visit, has tasted wine at the cellar door, is younger, spends more on monthly household consumption of wine, and was primarily visiting to buy wine. However, intention to revisit is predicted only by satisfaction, awareness of the winery before the visit, motives of buying and tasting wine, and some sociodemographic characteristics. Implications for the management of visitor behavior and the cellar door experience are also discussed.
Knowledge Graph Completion Based on Graph Representation and Probability Model

Knowledge Graph provides an effective scheme for unstructured knowledge on the Internet. but, to a large extent, the lack of information in the knowledge graph restricts the application of the knowledge graph. Therefore, knowledge graph completion has been an attractive research area. In recent years, many researchers apply graph convolutional neural networks to knowledge graph embedding so as to solve this problem, including R-GCN, SACN et al. The current state-of-the-art SACN uses graph convolutional neural as an encoder to make more accurate embeddings of graph nodes, and uses a convolutional network as a decoder, leading a good performance of link prediction task. In this work, we produce a novel graph representation model based on SACN---property graph convolutional network called PGCN. PGCN treats the knowledge graph as a property graph, regarding the initial embedding vector of entities and relations as the property of nodes and edges. What makes the model different is that it introduces the node clustering before convolving the nodes, so that the graph takes into account the importance of neighbors when aggregating the neighbors of nodes. We adopt the probability model Conv-TransE proposed by SACN for the modeling of relation of graph, Conv-TransE takes advantages of ConvE and use probability method which greatly improves the efficiency of the experiment and avoids the construction of the corrupted triplet. We conduct experiments on the standard datasets WN18RR and FB15k-237, and demonstrate that our new model achieves better performance.
Evolutionary synthesis of nonlinear models based on metaheuristic programming and templates

The application of a metaheuristic programming (MP) algorithm based on various bio-inspired algorithms for the evolutionary (metaheuristic) synthesis of nonlinear models is considered. The described approach of evolutionary synthesis uses a sequential operator structure of the chromosome, templates (with some undefined functions and parameters) of the models and the given sets of pairs of input and output data. The influence of the degree of specialization of the template on the characteristics of the search algorithm in the metaheuristic synthesis of nonlinear models defined by ordinary differential equations with undetermined functions and parameters is studied. Estimates of the complexity of this algorithm are obtained, and a significant reduction in the search time when using templates in the process of the evolutionary synthesis is shown.
Bio-efficacy of newer insecticides against Spodoptera litura in soybean

The experiments was conducted during kharif 2017 and 2018 at the farm of AICRP on soybean, VNMKV, Parbhani (Maharashtra) to evaluate the different newer chemical molecules against Spodoptera litura in soybean. The data revealed that chlorantraniliprole 18.5 SC@ 30 g a.i./ha was the most effective followed by spinetoram 11.7 SC @ 15 g a.i./ha. The next most effective emamectin benzoate 5 SG @ 11 g a.i./ha, flubendiamide 39.35 SC @ 48 g a.i./ha, indoxacarb 15.8 EC @ 30 g a.i./ha and lamda-cyhalothrin 4.9 CS @ 15 g a.i./ha which were at par with each other. chlorantraniliprole 18.5 SC and spinetoram 11.7 SC proved most safer treatments against natural enemies as compared to Emamectin benzoate 5 SG lamda cyhalothrin 4.9CS. The maximum yield was recorded in treatment chlorantraniliprole 18.5 SC followed by spinetoram 11.7 SC, emamectin benzoate 5 SG and flubendiamide 39.35 SC which were at par with each other.
Single nucleotide polymorphism mutation related genes in bladder cancer for the treatment of patients: a study based on the TCGA database

Abstract Bladder cancer (BLCA) is a common malignancy and has a poor prognosis. Single nucleotide polymorphisms (SNPs) in genes are closely associated with the tumorigenesis and tumor development and yet are not well illustrated in BLCA. In this study, we downloaded SNP‐related data and transcriptome profiling of BLCA from the Cancer Genome Atlas (TCGA) database and identified high frequency mutation genes using Maftools package and differentially expressed genes (DEGs) between BLCA and normal bladder tissues by the Limma package. Then, the overlapping genes between high frequency mutation genes and DEGs were obtained by the Venn diagram tool. These overlapping genes were analyzed by Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) network construction, survival analysis and drug–gene interaction analysis. As a result, 33 overlapping mutant genes were obtained, which were enriched in multiple KEGG pathways (e.g. cellular senescence) and GO items (e.g. muscle organ development, costamere and actin binding). A significant gene module was constructed by PPI network analysis and included 12 hub genes (SYNE1, DMD, ATM, EP300, ANK2, LAMA2, FAT1, SRRM2, MACF1, TSC1, VCAN and RXRA). Moreover, ATM, RXRA, TSC1, DMD, EP300, LAMA2 and VCAN were drug targets. These findings provide important bioinformatics and theoretical basis for understanding the pathogenesis of BLCA and exploring the detailed mechanisms of mutant genes in the disease.
Energy-Net: A Deep Learning Approach for Smart Energy Management in IoT-Based Smart Cities

Although intelligent load forecasting is essential for optimal energy management (EM) in smart cities, there is a lack of current research exploring EM in well-regulated Internet-of-Things (IoT) networks. This article develops a new deep learning (DL) model for efficient forecasting of short-term energy consumption while maintaining effective communication between energy providers and users. The proposed Energy-Net stack comprises multiple stacked spatiotemporal modules, where each module consists of a temporal transformer (TT) submodule and a spatial transformer (ST) submodule. The TT models the temporal relationships in load data; and the ST submodule extracts hidden spatial information by integrating convolutional layers and includes an improved self-attention mechanism. The experimental evaluation on IHPEC and independent system operator New England (ISO-NE) data set demonstrates the superiority of Energy-Net over recent cutting-edge DL models with root mean-square error (RMSE) of 0.354 and 0.535, respectively. The computational complexity of Energy-Net is appropriate for dependable resource-constrained IoT devices (i.e., fog nodes or edge nodes) linked to a joint IoT-cloud server that interacts with connected smart grids to handle EM tasks.
A stable feature selection method based on relevancy and redundancy

In this paper, the characteristics of software defect prediction are analyzed from the perspective of machine learning. To solve the problem of some redundant or uncorrelated features in defect data sets, a stable feature selection method based on relevancy and redundancy (RRSFS) is proposed. RRSFS combines the redundancy between features and the correlation between features and classes to select the optimal subset. RRSFS not only reduces the cost of data operation in the prediction model, but also enhances the stability of feature selection algorithm.
A Virtual Emotion Detection System With Maximum Cumulative Accuracy in Two-Way Enabled Multi Domain IoT Environment

In this letter, we introduce a multiplex cumulative virtual emotion detection system for two-way enabled multi domain IoT environment, which avoids detection holes in all IoT domains. Formally, we define a problem whose objective is to maximize cumulative accuracy of detection holes on condition that perpendicular barriers or horizontal barriers are constructed in every domain area. After presenting the defined problem with ILP formulation, we devise a novel scheme to solve the problem. Moreover, we evaluate the obtained results through extensive experiments.
Hedgerows and Enclosures in Rural Areas: Traditional vs. Modern Land Use in Mediterranean Mountains

The present paper highlights the importance of hedgerows and enclosures in the mountains of Central Spain. Now, these landscapes have suffered profound variations in terms of agroforestry practices, especially in the Mediterranean mountains where the characteristic multifunctional has largely been lost. The article analyzes land uses changes, dynamics, and their morphological features between the first half of the 20th Century (1956) and the second decade of the present time (2019). The paper was divided into three sections. First, the identification of land uses using orthophotograph and aerial photograph; after that the info was checked with fieldwork. Eleven categories were identified according to the dominant use and land use changes and size of land parcels were taken into consideration. Second, the configuration and the information collected through the type and intensity of change in land uses made it possible to recognise and quantify their distribution and trend between these two dates. Also, the kernel density algorithm available in the Arcgis 10.5 software was used to obtain density and changes in land parcels. Finally, an overview is given of the main role that this agroforestry plays due to the social, ecological, and economic benefits that they provide for allowing sustainable development.
Next-Generation Sequencing Myeloid Panel Test for Patients with AML and MDS: Experience in a Tertiary Care Hospital

This article is available from https://www.labmedonline. org 2021, Laboratory Medicine Online This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Next-generation sequencing (NGS) technology can be used for detecting gene mutations in various patients. The NGS myeloid panel test can be specifically used for patients with a myeloid neoplasm. In this study, the NGS myeloid panel test was used for patients with AML and MDS, and the results are summarized and reported retrospectively. Methods: Thirty-two NGS myeloid panel test results were reviewed retrospectively. Oncomine Myeloid Research Assay (Thermo Fisher Scientific, USA) and Ion Torrent S5 XL (Thermo Fisher Scientific) were used for sequencing, and variant annotation was performed using Ion Reporter Software (Thermo Fisher Scientific). Filtered variants were classified into tiers 1, 2, and 3, according to the Association for Molecular Pathology guidelines. Results: Eighty-seven variants were detected from 32 cases, and 30 cases (94%) had at least 1 variant classified into tier 1 or 2. The most frequently detected mutated gene in patients with AML was DNMT3A (N=8) and that in patients with MDS was U2AF1 (N=4). Gene mutations were not detected in patients with MDS with single lineage dysplasia. Conclusions: Clinically useful genetic mutations were found in patients with AML and MDS through an NGS myeloid panel test. Although there are limitations to this study due to the small number of cases, some differences were found between the results of this study and the genetic profiles of AML patients in other studies. Further evaluation of the genetic profile of myeloid neoplasm is needed, and the NGS myeloid panel test can be useful for this.