Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological characteristics and molecular phylogeny of Disciseda hyalothrix (Gasteromycetes) from Altai Mountains, a new record to Northern Asia

Morphological characteristics and molecular phylogeny of the gasteroid fungus, Disciseda hyalothrix, and data on its localities, habitat and distribution are provided. This rare species of D. hyalothrix was found in the protection zone of the Tigirek Reserve, Altai Territory, Russia (Altai Mountains, Western Siberia, Northern Asia). A fruiting body of D. hyalothrix was found in “Dragunskaya” cave. Detailed descriptions, illustrations of basidiocarp and basidiospores are given. The main diagnostic features of Disciseda species are the size of the spore and the nature of the ornamentation. Spores of D. hyalothrix are globose, brown, grossly verrucose, (6) 6.5–7.5 μm in diameter, without ornamentations, without pedicels or rarely with colorless pedicels 4–6 (up to 10) μm. In the SEM, ornamentation in the form of powerful pyramidal tufts consisting of thin spines pressed together to 1–1.3 μm in height. We present a scanning electron micrograph study and morphological characteristic comparison of D. hyalothrix and other Disciseda species found in Eurasia, which currently includes 5 taxa. We first generated new sequences for rDNA (ITS1-5.8SITS2 region and partly for LSU) of D. hyalothrix (NSK 1014099). The new record of D. hyalothrix broadens information on the ecology of the rare gasteromycete species, which was growing in the conditions of stony steppe communities. New sequence data for studied loci of rDNA will help clarify the phylogenetic relationships of species from the genera Disciseda and Bovista.
SEISMIC PERFORMANCE OF BEAM-COLUMN JOINT CONNECTIONS WITH REDUCTION IN TRANSVERSE REINFORCEMENTS IN RIGID- FRAMED RAILWAY BRIDGES BY USING PP-ECC

Bridges are vital components of transportation that requires a high degree of protection to ensure their safety during a strong earthquake. The extensive damages of RC bridges observed in the past earthquakes such as Northridge, Kobe and 2011 Great East Japan earthquakes triggered extensive researches on the behavior of beam–column joint connections for designing and constructing a safer infrastructure, which further resulted in the improvements of design codes focusing on providing sufficient ductility in the vulnerable structural member to prevent its brittle failure during a major seismic event. Accordingly, for reinforced concrete (RC) structures, a considerable amount of steel reinforcements are required to be provided in these vulnerable regions, such as the plastic hinge in the beam end adjacent to the column face in a beam–column joint connection in the rigid-framed railway bridges, to confine the concrete to realize the formation of ductile inelastic behavior in the plastic hinge. However, the increased and elaborated reinforcement details bring the difficulties in fabricating this complicated steel reinforcement cage as well as placing and consolidating concrete in it during the construction phase. The contradiction between increased high cost for design and construction due to these complicated reinforcements with accordingly raised requirements on seismic performance becomes more and more apparent. In this research, a cementitious composite combined with fabricated polypropylene fibers named Polypropylene Fiber Reinforced Engineered Cementitious Composites (PP-ECC) with improved bond properties exhibiting the pseudo strain hardening and multiple fine cracking of ECC was utilized to reduce the transverse reinforcements in beam–column joint connections of rigid-framed bridges. Compared with widely used polymer fibers such as polyvinyl alcohol (PVA) fibers or polyethylene (PE) fibers, polypropylene (PP) fiber is softer, costs lower and disperses faster, which all results in better workability. In addition, because of the hydrophobic and non-polar nature of PP fiber, PP-ECC has better durability in an alkaline environment. The loading tests including two phases were conducted: the basic mechanical properties of PP-ECC in compression and tension were confirmed by cylinder compression and uniaxial tensile tests in the first phase and a total of three one-sixth scaled T-shaped beam–column joint connections which were prepared based on the design standards for existing railway bridges in Japan were tested under the applied reversed cyclic load to verify the possibility of reducing transverse reinforcements. The experimental results reveal that the PP-ECC is effective in replacing transverse reinforcements in the beam-column joint connections of railway rigid-framed bridges without deterioration of seismic performance.
Nasal Provocation Test with Cat and Dog Extracts: Results according to Molecular Components

Background IgE sensitization (atopy) to pets is commonly evaluated using pet dander extracts. However, the diagnosis by components seems to be more adequate to evaluate the clinical relevance (allergy) of sIgE sensitization. Objective To study the association between IgE sensitization to pet allergen components and clinical symptoms. Methodology. Dander extracts and sIgE levels to pet components (Can f 1, Can f 2, Can f 3, Can f 5, Fel d 1, Fel 2, and Fel 4) were measured in a rhinitis group (n = 101) and a control group (n = 101) and a control group ( Results Dog (34.6% vs. 23.5%) and cat dander (26.7% vs. 8.8%, p = 0.05) IgE sensitization was frequent among rhinitis and no-rhinitis subjects, and it was similar to dog (29.7% vs. 20.5%) and cat (18.8% vs. 8.8%) components. Polysensitization for dog (3.1, 95% CI: 1.5 to 6.1, p = 0.05) IgE sensitization was frequent among rhinitis and no-rhinitis subjects, and it was similar to dog (29.7% vs. 20.5%) and cat (18.8% vs. 8.8%) components. Polysensitization for dog (3.1, 95% CI: 1.5 to 6.1, p = 0.05) IgE sensitization was frequent among rhinitis and no-rhinitis subjects, and it was similar to dog (29.7% vs. 20.5%) and cat (18.8% vs. 8.8%) components. Polysensitization for dog (3.1, 95% CI: 1.5 to 6.1, Conclusions Sensitization to pet dander extract identifies atopic patients, but its utility to predict clinical relevance is poor. Allergenic components could help to define the clinical relevance of sensitization to furry animals and could reduce the need for provocation test.
Gender Prediction from Social Media Comments with Machine Learning

In the 21st century, which can be termed as age of artificial intelligence, machine learning (ML) techniques that can become widespread and improve themselves can be given more quality services to humanity in many fields. As a result of these ML developments, nowadays many companies use predictive models to estimate customer behavior. Also, with increasing use of social media, the companies have started to deliver their products and services to their customers via social media accounts. But every customer is not interested in all product or service. Each customer's area of interest is different. Gender is one of the main reasons for this difference. If the gender of a social media user is determined correctly, the amount of sales may be increased by offering the appropriate products or services. The main aim of our study is an estimation of genders of the commenters thanks to machine learning techniques by analyzing the comments of companies posting on Facebook. In context of the study, the genders of the commenters labelled based on commenters' name. The data set is divided into training and test data as 70-30%. As a result of the study, it was seen that machine learning methods predicted with similar accuracy rates, while the highest accuracy rate (74.13%) was obtained by logistic regression method.
THE UCSB METHOD FOR SIMULATING BROADBAND GROUND MOTION USING CORRELATED RUPTURE PARAMETERS ON A FINITE FAULT

The UCSB method produces broadband ground motion (0-25 Hz) for earthquakes with magnitudes between 5 and 8. For each earthquake scenario we generate kinematic rupture scenarios (50 stochastic realizations or more) that are characterized by Kostrov-like [1] slip-rate functions densely spaced on a finite fault area. The slip-rate functions are parameterized by the total slip, time to reach the maximum slip-rate (peak-time), the total time of slipping (rise-time), and time when slip starts (this determines the local rupture velocity). For each stochastic simulation each kinematic rupture parameter we filter white noise with a Von Karman power spectrum in the wavenumber domain to produce the spatial correlation. We use the correlations between each kinematic source parameter pair based on the dynamic rupture scenarios [2]. For each synthetic earthquake rupture scenario, we compute ground motion using the representation theorem. For this, we separate the wave propagation problem into a lowand high-frequency components separated at 1.0 Hz. The high-frequency Green's functions capture the geometrical decay with a simplified velocity structure. The high-frequency Green’s functions will be later convolved with scattering functions. The high-frequency amplitude is modified using the detailed 1D velocity model for the velocity and density and the quarter-wavelength impedance [3]. The low-frequency ground motion is propagated from the source to the site using either a 1D or 3D velocity structure. We merge the lowand high-frequency ground motion by stitching these two in the wavelet domain [4]. Important to note is that the source is the same for both the lowand high-frequency components of ground motion. So far we have successfully validated our method against well-recorded data produced by earthquakes in different tectonic regions such as California, Eastern United States, and Japan [5]. The metric for comparing the quality of the computed ground motion is acceleration response spectrum at distance up to 150 km from the fault. The comparisons look at the total bias between observed and computed response spectral ordinates at different periods as well as the dependence of the spectral ordinate on distance from the fault at various periods. The UCSB method is an attractive solution to generate physics-based synthetic ground motion with minimal computational cost.
Ultra-High-Speed 3D Astigmatic PTV in Supersonic Underexpanded Impinging Jets

Ultra-high-speed three-component, three-dimensional (3C3D) velocity measurements of micronsized particles suspended in a supersonic impinging jet flow are presented. Understanding the dynamics of individual particles in such flows is important for the design of particles impactors for drug delivery or cold gas dynamic spray processing. The underexpanded jet flow is produced via a converging nozzle and micron-sized particles (dp = 110 μm) are introduced into the gas flow. The supersonic jet impinges onto a flat surface and the particle impact velocity and particle impact angle are studied for a range of flow conditions and impingement distances. The imaging system consist of an ultra-high-speed digital camera (Shimadzu HPV-1) capable of recording rates of up to 1 Mfps. Astigmatism particle tracking velocimetry (APTV) is used to measure the 3D particle position [6] by coding the particle depth location in the 2D images by adding a cylindrical lens to the high-speed imaging system. Based on the reconstructed 3D particle positions the particle trajectories are obtained via a higher-order tracking scheme that takes advantage of the high temporal resolution to increase robustness and accuracy of the measurement. It is shown how the particle velocity and impingement angle depend on the nozzle pressure ratio and stand-off distance and that higher pressure ratios and stand-off distances lead to higher impact velocities and larger impact angles.
Deploying Decision Tree Ensembles to DBMS

e decision tree ensemble is one of the most well-known statistical models used in the eld of machine learning. With a long history in reseach literature, the tree ensemble has been used with great eect, showing impressive predictive performance on many tabular datasets1. e goal of this project is to deploy tree ensemble models to a modern database system for the prediction task. Existing packages require that the data be moved into the prediction code, which may be costly. We will instead move the prediction code into the database as a user-dened function (UDF). It is oen said that it is beer to move code to where data is than to move data to where code is2; let’s see if it’s true for decision trees as well.
OTT_A_227122 9085..9092

Jinjing Zhang Xuyong Lin 2 Yan Li Rui Zhang 1Department of Hematology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, People’s Republic of China; 2Department of Pathology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, People’s Republic of China Abstract: Primary cardiac diffuse large B cell lymphoma (PC-DLBCL) is a rare kind of hematological malignancy, and its clinical and pathologic characteristics, especially in Eastern countries, remain unclear. Moreover, genomic alterations in PC-DLBCL have not been studied previously.We describe a case of a 57-year-oldman who presented with exertional dyspnoea due to a heart mass in April 2018 and was diagnosed with PC-DLBCL characterized by immunohistochemical markers of the activated B cell (ABC) subtype and double expression of c-MYC and Bcl-2. Mutations in a total of 11 genes—TBL1XR1, CD79B, IGLL5, ZMYM3, MYD88, TMSB4X, PIM1, BTK, NRXN3, CUX1, andCSMD1—were detected via next-generation sequencing (NGS), while 19 copy number variations (CNVs) such as 1q+, 3p+, 3q+(*2), 5p+, 6p−, 6q−, 7q+, +11, 12q−, 15q−, 17q+, 17p−, +18, 19q+, 19p−, 19q−, X q+, and −Yand 4 copy-neutral loss of heterozygosity (CN-LOH) lesions located at 1q21.1q44, 3p26.3q11. 2, 3q13.11q29 and 6p22.2p21. 32 were identified by single nucleotide polymorphism (SNP) array karyotyping. Some key gene alterations in lymphoma, such as PRDM1 deletion and Bcl-2 amplification, were identified using SNP array analysis. The patient received 6 courses of chemotherapy (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone, R-CHOP regimen) after surgery and is currently in remission. In summary, the present case was diagnosed as PCDLBCL, ABC subtype by the Hans algorithm and double expression lymphoma, with cooccurrence of the MYD88 and CD79B mutations (MCD) subtype by genetic alteration analysis. This study presents a unique PC-DLBCL case in which complex genomic alterations were revealed by NGS and SNP array analysis, which has never been reported in the literature, and these findings could provide new insight into the genomic characterization of PC-DLBCL.
Probing and Enhancing Ligand-Mediated Active Targeting of Tumors Using Sub-5 nm Ultrafine Iron Oxide Nanoparticles

Rationale: “Active targeting” based on the ligand-target affinity is a common strategy to precisely deliver nanoparticle (NP) imaging probes or drug carriers to the diseased tissue. However, such ligand-mediated active targeting inevitably takes place with prerequisite “passive targeting”, driven by the enhanced permeability and retention (EPR) effect. Thus, the efficiency of active targeting in relation to off-targeted unbound NPs is of great importance in quantitative imaging of tumor biomarkers and delivery. With the notion that easy clearance of off-targeted uIONPs may lead to enhanced active targeting and tumor accumulation, we examined the NP size effect on “active targeting” of the transferrin receptor (TfR) using transferrin (Tf)-conjugated sub-5 nm (3 nm core) ultrafine iron oxide NPs (uIONPs) and larger IONPs (30 nm core). Methods: Green fluorescent dye (FITC)-labeled active targeting uIONPs (FITC-Tf-uIONPs) and red fluorescent dye (TRITC)-labeled passive targeting uIONPs (TRITC-uIONPs) were prepared. FITC-Tf-IONPs and TRITC-IONPs were used as comparison for the NP size effect. Multiphoton imaging, confocal fluorescence imaging, histological staining and computational analysis were applied to track different types of NPs in tumors at 1, 3 and 24 hours after co-injection of equal amounts of paired NPs, e.g., active targeting FITC-Tf-uIONPs and non-targeting TRITC-uIONPs, or FITC-Tf-IONPs and TRITC-IONPs into the same mice bearing 4T1 mouse mammary tumors. Results: Active targeting uIONPs exhibited an almost 6-fold higher level of tumor retention with deeper penetration comparing to non-targeting uIONPs at 24 hours after co-injection. However, accumulation of active targeting IONPs with a 30-nm core is only about 1.15-fold higher than non-targeting IONPs. The enhanced active targeting by uIONPs can be attributed to the size dependent clearance of unbound off-targeted NPs, as majority off-targeted uIONPs were readily cleared from the tumor by intravasation back into tumor blood vessels likely due to high interstitial pressure, even though they are not favorable for macrophage uptake. Conclusion: Ligand-mediated active targeting improves the delivery and accumulation of the sub-5 nm NPs. The improvement on active targeting is size-dependent and facilitated by NPs with sub-5 nm core sizes. Thus, sub-5 nm NPs may serve as favorable platforms for development of NP-based molecular imaging probes and targeted drug carriers.
Do regional social capital and trust matter for immigrant diversity and wages

Recent studies suggest that greater immigrant diversity in regions and workplaces increases productivity, and inclusive regional conditions are found to be important for this mechanism. Seeking to better understand this relationship, this paper broadens the dimensions and refines the measures of regional context pertaining to immigrant diversity outcomes. Regional measures of trust in foreigners and trust in government are tested under the hypothesis that regions with higher trust will have larger associations between rising immigrant diversity and increasing local wages. Additionally, we hypothesize that the benefits from immigrant diversity will be higher in regions with a strong social bridging culture, while the opposite will be the case in regions with a high level of social bonding. Looking across these novel and more nuanced dimensions of regional context, we find that they each matter in shaping the effects of diversity. Specifically, we find that spillovers from regional diversity are higher in regions with low levels of social bonding and in regions with high levels of trust, confirming the hypotheses. Evidence on regional variation in bridging social capital does not confirm the hypothesis. Using high quality longitudinal matched employer-employee data from Norway from 2001-2011, this paper provides a new case in the empirical diversity-productivity literature and novel evidence on the regional dimensions that shape this relationship.
Thünen-Series of Applied Economic Theory

This paper investigates how demographic change affects the financial sustainability of a defined benefit pay-as-you-go social security system in an environment with collective bargaining on the labor market. Temporary equilibrium analysis shows that the contribution rate decreases, if the old-age dependency ratio rises. The government balances the social security budget by aiming indirectly at a higher level of employment. In the intertemporal equilibrium the opposite applies. The government increases the contribution rate due to additional effects of demographic change on capital accumulation and labor demand. In contrast to a perfect labor market scenario, the imposed financing burden from an aging society is overcompensated by favorable labor market effects on the social security budget. JEL-Codes: E24, H55, J11, J51
Clustering radar satellite data: a data mining approach

In this paper we discuss the importance of applying clustering data mining algorithms, instead of traditional analysis, in estimating different types of ground deformation trend by processing ERS1 and ERS2 satellites SAR images of the European Space Agency. The data set is a peculiar temporal large data sets (formed about by 18,000 time series) related to 72 measurement of ground displacement dated between 1992 and 2000 over a sector of Campania Region comprised between Avellino and Benevento towns. 1 The framework: Clustering Temporal Data Mining Clustering of sequences or time series is concerned with grouping a collection of time series (or sequences) based on their similarity. It is well known that data clustering is inherently a more difficult task if compared to supervised classification, in which classes are already identified, so that a system can be adequately trained. This intrinsic difficulty worsens if sequential data are considered: the structure of the underlying process is often difficult to infer, and typically different length sequences. In spite of the great wealth of clustering algorithms, the rapid accumulation of large databases of increasing complexity poses a number of new problems that traditional algorithms are not equipped to address. One important feature of modern data collection is the ever increasing size of a typical database: it is not so unusual to work with databases containing from a few thousands to a few millions of individuals and hundreds or thousands of variables. Now, most clustering algorithms of the traditional type are severely limited as to the number of individuals they can comGermana Scepi, Gabriella Milone University of Naples, Via Cinthia, Monte Sant’Angelo (NA) Italy; e-mail: scepi@unina.it Fabio Matano Unita’ n 6 Campania PODiS PON ATAS QCS 2000-2006 Ministero per l’Ambiente e la Tutela del Territorio e del Mare c/o Ufficio Autorita’ Ambientale, Regione Campania, Napoli-Italy
EXPERIENTIAL DESTINATION MARKETING AND TOURIST BEHAVIOR: A RESEARCH ON SENIOR TOURISTS

Destination tourism activities and objects, by their very nature, are experience based and have a high potential in terms of experiential marketing’s applicability. In this regard, it has been aimed to adapt strategic experiential marketing modules (sense, feel, act, think and relate) to the destination of Istanbul and to analyze the effect of those components on the satisfaction level and behavioral intentions (loyalty, intention to pay more and negative word of mouth) of senior tourists visiting Istanbul, Turkey. Data were collected by a self-administrative questionnaire on senior visitors. The results of structural equation model showed direct and indirect relations between strategic experiential marketing modules, experiential satisfaction and behavioral intentions.