Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin C deficiency reveals developmental differences between neonatal and adult hematopoiesis

Hematopoiesis, a process that results in the differentiation of all blood lineages, is essential throughout life. The production of 1x1012 blood cells per day, including 200x109 erythrocytes, is highly dependent on nutrient consumption. Notably though, the relative requirements for micronutrients during the perinatal period, a critical developmental window for immune cell and erythrocyte differentiation, have not been extensively studied. More specifically, the impact of the vitamin C/ascorbate micronutrient on perinatal as compared to adult hematopoiesis has been difficult to assess in animal models. Even though humans cannot synthesize ascorbate, due to a pseudogenization of the L-gulono-γ-lactone oxidase (GULO) gene, its generation from glucose is an ancestral mammalian trait. Taking advantage of a Gulo-/- mouse model, we show that ascorbic acid deficiency profoundly impacts perinatal hematopoiesis, resulting in a hypocellular bone marrow (BM) with a significant reduction in hematopoietic stem cells, multipotent progenitors, and hematopoietic progenitors. Furthermore, myeloid progenitors exhibited differential sensitivity to vitamin C levels; common myeloid progenitors and megakaryocyte-erythrocyte progenitors were markedly reduced in Gulo-/- pups following vitamin C depletion in the dams, whereas granulocyte-myeloid progenitors were spared, and their frequency was even augmented. Notably, hematopoietic cell subsets were rescued by vitamin C repletion. Consistent with these data, peripheral myeloid cells were maintained in ascorbate-deficient Gulo-/- pups while other lineage-committed hematopoietic cells were decreased. A reduction in B cell numbers was associated with a significantly reduced humoral immune response in ascorbate-depleted Gulo-/- pups but not adult mice. Erythropoiesis was particularly sensitive to vitamin C deprivation during both the perinatal and adult periods, with ascorbate-deficient Gulo-/- pups as well as adult mice exhibiting compensatory splenic differentiation. Furthermore, in the pathological context of hemolytic anemia, vitamin C-deficient adult Gulo-/- mice were not able to sufficiently increase their erythropoietic activity, resulting in a sustained anemia. Thus, vitamin C plays a pivotal role in the maintenance and differentiation of hematopoietic progenitors during the neonatal period and is required throughout life to sustain erythroid differentiation under stress conditions.
Research on Propagation Model of Public Opinion Topics in SNS Based on SIR

The public opinion topics are usually caused by the sudden events,and social network sites( SNS) have become the important communication channels of the public opinion topics because of their large scale of users and the characters of open,real-time and interactive. Therefore,studying the propagation mechanism of public opinion topics in SNS will be conducive to analyzing and monitoring the propagation process of public opinion topics. However,it is difficult for the traditional information propagation models to describe the propagation and evolution of the public opinion topics in SNS. This paper analyzes the information interaction mode and propagation characteristics of the public opinion topics in SNS,and then the propagation model of public opinion topics in SNS is built up based on SIR model in the scale-free network. The model considers internal infection probability,external infection probability,immune probability and direct immune probability as the important parameters in the propagation process. The simulation results show that the model established in this paper can well describe the propagation law of public opinion topics in SNS.
SYNTHESIS OF 1-ARYLOXYACETYL-4- (5-(4-CHLOROPHENYL)-2-FUROYL)- SEMICARBAZIDES

Asim ple and efficient route to 1,4-diacyl semicarbazides is described. 1-Aryloxyacetyl-4-(5-(4-chlorophenyl)-2-furoyl)- thiosemicarbazides (Ia–i) on treatment with potassium iodate in the aqueous solution afford 1-aryloxyacetyl-4-(5- (4-chlorophenyl)-2-furoyl)-semicarbazides (IIa–i) in excellent yields.
Bridge inspection robot system with novel image processing

This paper proposes the design and control methods for a bridge inspection robot system with the novel image processing system. The bridge inspection robot system has been developed with the aim of checking the safety status of a real bridge and gathering accurate data such as crack width and length. The developed robot system is composed of the moving mechanism mounted on the specially designed car for bridge inspection and the novel image processing system. Especially, this paper emphasizes the system integration method to design and control the entire robot system. Also, the users can see the operating conditions of long-distance robot with 3-dimensional graphical user interface. Moreover, the users can feel the operating status of long-distance robot through haptic device. 1207 Bridge Maintenance, Safety, Management, Health Monitoring and Informatics – Koh & Frangopol (eds) © 2008 Taylor & Francis Group, London, ISBN 978-0-415-46844-2
Hybrid algorithms for preprocessing agglutinative languages and less-resourced domains effectively

This thesis deals with text processing applications examining methods suitable for less-resourced and agglutinative languages, thus presenting accurate preprocessing algorithms. The first part of this study describes morphological tagging algorithms which can compute both the morpho-syntactic tags and lemmata of words accurately. A tool (called PurePos) was developed that was shown to produce precise annotations for Hungarian texts and also to serve as a good base for rule-based domain adaptation scenarios. Besides, we present a methodology for combining tagger systems raising the overall accuracy of Hungarian annotation systems. Next, an application of the presented tagger is described that aims to produce morphological annotation for speech transcripts, and thus, the first morphological disambiguation tool for spoken Hungarian is introduced. Following this, a method is described which utilizes the adapted PurePos system for estimating morpho-syntactic complexity of Hungarian speech transcripts automatically. The third part of the study deals with the preprocessing of electronic health records. On the one hand, a hybrid algorithm is presented for segmenting clinical texts into words and sentences accurately. On the other hand, domain-specific enhancements of PurePos are described showing that the resulting tagger has satisfactory performance on noisy medical records. Finally, the main results of this study are summarized by presenting the author’s theses. Further on, applications of the methods presented are listed which aims less-resourced languages. DOI:10.15774/PPKE.ITK. 2015.007
Social contagion influenced by active-passive psychology of college students

Educational behavioral psychology refers to the fact that college students within campus networks have various psychological cognition toward novel information and behavior. This is hardly ever taken into account or theoretically examined in weighted network research. According to psychological traits and a student’s willingness to adopt fresh behaviors, we categorize students’ behaviors into the active and passive. On this basis, a threshold models is established for the behavior of active and passive students in weighted networks, and the influence behavioral psychology on information propagation is discussed. In order to qualitatively investigate the information propagation mechanism, a partition theory based on edge-weight and behavioral psychology is developed. Active students encourage the acceptance of new behaviors and the spread of information, according to theoretical study and simulation results. However, the phase transition intersected was more significant. When the percentage of enrolled pupils is high, a continuous phase transition is present in the growth pattern of the final adoption size. In contrast, as the proportion of active students declines, the increasing pattern alterss to discontinuous phase transition. In addition, weight distribution heterogeneity facilitates the dissemination of information and does not alter phase transition pattern. Finally, the theoretical analysis is in good agreement with the simulation results.
Creating a Research Center: Space for Collaborations and Conversations

ABSTRACT This report describes the creation of a library research center, where a team of librarians provide flexible, convenient, and personalized research assistance to students. A research center creates a positive user experience for students and places collaboration—both among librarians and students—at its core. Next-generation reference models must provide spaces and environments for students and librarians to engage in meaningful and deep information literacy conversations as outlined in the ACRL Framework for Information Literacy for Higher Education.
Molecular epidemiological survey of porcine epidemic diarrhea in some areas of Shandong and genetic evolutionary analysis of S gene

Responsible for the acute infectious disease porcine epidemic diarrhea (PED), PED virus (PEDV) induces severe diarrhea and high mortality in infected piglets and thus severely harms the productivity and economic efficiency of pig farms. In our study, we aimed to investigate and analyze the recent status and incidence pattern of PEDV infection in some areas of Shandong Province, China. We collected 176 clinical samples of PED from pig farms in different regions of Shandong Province during 2019–2021. PEDV, TGEV, and PORV were detected using RT-PCR. The full-length sequences of positive PEDV S genes were amplified, the sequences were analyzed with MEGA X and DNAStar, and a histopathological examination of typical PEDV-positive cases was performed. RT-PCR revealed positivity rates of 37.5% (66/176) for PEDV, 6.82% (12/176) for transmissible gastroenteritis virus, and 3.98% (7/176) for pig rotavirus. The test results for the years 2019, 2020, and 2021 were counted separately, PEDV positivity rates for the years were 34.88% (15/43), 39.33% (35/89), and 36.36% (16/44), respectively. Histopathological examination revealed atrophied, broken, and detached duodenal and jejunal intestinal villi, as typical of PED, and severe congestion of the intestinal submucosa. Moreover, the results of our study clearly indicate that the G2 subtype is prevalent as the dominant strain of PEDV in Shandong Province, where its rates of morbidity and mortality continue to be high. Based on a systematic investigation and analysis of PEDV's molecular epidemiology across Shandong Province, our results enrich current epidemiological data regarding PEDV and provide some scientific basis for preventing and controlling the disease.
GPI-anchored glutathione S-transferase as marker allows affinity sorting of transfection-positive cells

Cell transfection efficiency is still a limiting factor in gene function research. A method that allows isolation and enrichment of the transfection-positive cells is an effective solution. Here, we report a transfection-positive cell sorting system that utilizes GPI-anchored GST (Glutathione S-transferase) as a plasmid marker. The Glutathione S-transferase fusion protein will be expressed and displayed on the cell surface through GPI anchor, and hence permits the positive cells to be isolated using Glutathione (GSH) Magnetic Beads. We prove that the system works efficiently in both the adherent Lenti-X 293T cells and the suspension K-562 cells. The affinity cell sorting procedure efficiently enriched positive cells from 20% to 98% in K-562 cells. The applications in gene knockdown and overexpression experiments in K-562 cells dramatically enhanced the extent of gene alteration, with the gene knockdown efficiency increasing from 7% to 60% and the gene overexpression level rising from 47 to 253 times. This Glutathione S-transferase affinity transfection-positive cell sorting method is simple and fast to operate, large-instrument free, low cost, and hence possesses great potential in gene function study in vitro.
Enhancement of Chest X-Ray images Using Filtering Techniques

X-ray image is never the correct representation of the object under observation; it is always ruined by degradations during acquisition and within the imaging system itself. These include noise, blurring and distortion. Noise removal is an important and challenging issue in medical image processing. Various filtering techniques have been developed to solve the noise removal problems, but most of them require deep expert knowledge to design appropriate image filters. These filtering techniques have their own assumptions, advantages and disadvantages. This paper proposes mean and median filtering techniques for the removal of noise from the X-ray medical image. Proposed method applied for noise removal problems. In terms of statistical quantity measures such as MSE, RMSE, PSNR, AD, the results show the superiority of the proposed method.
Applications of an asymmetric [2 + 2]-photocycloaddition. Total synthesis of (-)-echinosporin. Construction of an advanced 11-deoxyprostaglandin intermediate

The first total synthesis of the novel antitumor metabolite (-)-echinosporin (1) has been achieved. Asymmetric [2+2]-photocycloaddition of dihydrofuran acetonide (+)-8 to 2-cyclopentenone (7) constituted the cornerstone of the synthetic strategy. Mitsunobu lactonization of hemiacetal acid 43 generated the tricyclic framework of 1, which embodies a strain energy of ca. 17 kcal/mol as estimated by MNDO calculations. The successful synthetic venture permitted assignment of the absolute configuration of echinosporin
A Combinational Model to Optimize DNA Encoding Based on Discrete Particle Swarm Optimization

We analyze the objective and several constraints of DNA encoding,build a combinational optimization model.Based on this model,a discrete particle swarm optimization(DPSO) algorithm is proposed to produce DNA encoding sequences.According to the special constraints and the characteristics of discrete parameters,we redefine the computation rules of particle's position and velocity.The result shows that the DNA sequences produced by DPSO have better quality than that produced by the genetic algorithm.
Implementation of retrieving High Dimensional Data Using Clustering-Based Selection Algorithm

Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Feature selection is the process of selecting a subset of relevant features for use in model construction. The central assumption when using a feature selection technique is that the data contains many redundant or irrelevant features. Of the many feature subset selection algorithms, some can effectively eliminate irrelevant features but fail to handle redundant features yet some of others can eliminate the irrelevant while taking care of the redundant features. Our proposed FAST algorithm falls into the second group. Traditionally, feature subset selection research has focused on searching for relevant features. This paper provides the implementation of this algorithm on high dimensional data.
A PAPER RECOMMENDER SYSTEM BASED ON USER'S PROFILE IN BIG DATA SCHOLARLY

Users encounter a huge volume of papers in digital libraries and paper search engines such as IEEE Explore, ACM Digital library, Google scholar and etc. these high number of papers make some difficulties for researchers for finding proper information and items. Recommender systems contain successful tools for knowledge of users and identification of their priorities. These systems present a personalized proposal to users who seek to find a special kind of relevant data or their priorities through the big number of data. Recommendersystem based on personalization uses the user profile and in view of the fact that the user profile encompass information pertaining to the user priorities; so it is a very active district in data recovery. Recommendersystem is an attitude that presented in order to encounter difficulties caused by abundant data and it helps users to attain their goals quickly through huge number of data. In this paper, we have presented an approach that received entire of available information in a paper, and formed a profile for each user by short and long inquiries; this profile is personalized for user and then recommends the closest paperto the user by the user profile. Findings indicate that suggested approach outperformsthe similar approaches. Keywords: recommender system; bigdata; user profile; content-based recommender system; hadoop
Optimized Design Implementation of Direct Memory-Based Hardware for Efficient Resource- Constraint Digital Signal Processing Systems

An advance approach for Direct-Memory-Based hardware for area-delay-power efficient systems for commonly encountered computation-intensive cores of digital signal processing (DSP) systems is presented by combining three techniques, where the memory-size is reduced to one-eighth at the cost of some increase in combinational circuit complexity for signed magnitude numbers. Each of these techniques results in the reduction of the memory size by a factor of two. It is shown that by efficiently combining sign-bit exclusion technique, a different form of anti-symmetric product coding (APC) and a modified odd-multiple-storage (OMS) scheme, we get an optimized direct-memory-based multiplication hardware for resource-constraint DSP systems which provides a reduction in memory size to one-eighth over conventional direct-memorybased hardware, at the cost of a marginal area overhead. The proposed design for small input sizes can be used for efficient implementation of high-precision multiplication by input operand decomposition. The proposed optimized design also offers almost 87.5% and 85% reductions in directmemory size for L=5 bits and L=6 bits signed-magnitude numbers respectively, over conventional direct-memory size. Keywords— Digital signal processing (DSP), direct-memorybased computing, very large scale integration (VLSI).
Expressing Data, Space, and Time with Tableau Public™: Harnessing Open Data to Enhance Visual Learning through Interactive Maps and Dashboards

Virtually every subject area depicted in a learning object could conceivably involve a space-time element. Theoretically, every event may be mapped geospatially, and in time, these spatialized event maps may be overlaid with combined data (locations of particular natural and human-made objects, demographics, and other phenomena) to enable the identification and analysis of time-space patterns and interrelation-ships. They enable hypothesis formations, hunches, and the asking and answering of important research questions. The ability to integrate time-space insights into research work is enhanced by the wide availability of multiple new sources of free geospatial data: open data from governments and organizations (as part of Gov 2.0), locative information from social media platforms (as part of Web 2.0), and self-created geospatial datasets from multiple sources. The resulting maps and data visualizations, imbued with a time context and the potential sequencing of maps over time, enable fresh insights and increased understandings. In addition to the wide availability of validated geospatial data, Tableau Public is a free and open cloud-based tool that enables the mapping of various data sets for visualizations that are pushed out onto a public gallery for public consumption. The interactive dashboard enables users to explore the data and discover insights and patterns. Tableau Public is a tool that enables enhanced visual-and interaction-based knowing, through interactive Web-friendly maps, panel charts, and data dashboards. With virtually zero computational or hosting costs (for the user), Tableau Public enables the integration of geospatial mapping and analysis stands to benefit research work, data exploration and discovery and analysis, and learning.
Handbook of Large-Scale Random Networks: Bolyai Society Mathematical Studies

This handbook describes advances in large scale network studies that have taken place in the past 5 years since the publication of the Handbook of Graphs and Networks in 2003. It covers all aspects of large-scale networks, including mathematical foundations and rigorous results of random graph theory, modeling and computational aspects of large-scale networks, as well as areas in physics, biology, neuroscience, sociology and technical areas. Applications range from microscopic to mesoscopic and macroscopic models.The book is based on the material of the NSF workshop on Large-scale Random Graphs held in Budapest in 2006, at the Alfrd Rnyi Institute of Mathematics, organized jointly with the University of Memphis.
ID3 Applying to Loss of Bank Clients

Decision tree has been successfully applied to many of the classification issue,ID3 is the representative algorithm.Gives an instance study for ID3 completing the classification of banks forecast,presents the principle and implementation of the ID3 algorithm and analyses the reason and classification of the loss of bank clients.Also explains concretely the approach of how to use ID3 to forecast the loss of bank clients in detail,for instance,data sampling,data analyzing,model getting and model explaining.At the end,gets a model from which by picking up rules helps the bank forecast the loss of clients.
Effect of armrest positioning and workspace constraints on muscle activity for touchless gestural controls

The recent development of affordable technologies now allow touchless gestural controls to be integrated in common computing environments, however, ergonomic issues (user fatigue, in particular) have not been solved. This experiment investigates shoulder muscle activity for different traditional supported or user-preferred touchless gesture interaction scenarios and quantifies the location that touchless gestural control users would like to position armrests in different gestural workspaces. A custom hand/finger-based gestural control system was developed using a motion tracking system. Users browed an online shopping website while a prototype office chair allowed them to positon armrests easily in a wide space in front of themselves. Results show that median muscle activity of the upper trapezius, medial deltoid, and anterior deltoid are significantly affected by armrest configuration. User-preferred armrest positions generally reduced muscle activity compared to traditional positions, but this reduction was greatest when the gesture space is constrained over the desktop. In those conditions, average user preferred positioning of the armrest was higher and closer to the sternum of the user.