Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of dry cow therapy on incidence of clinical mastitis,milk yield and composition in crossbred cows

Mastitis is considered as one of the important production disease in dairy cows which incurs huge economic losses to dairy industry, despite considerable efforts has been dedicated to solve it for the last two decades. In the present study, the impact of dry cow therapy (DCT) on incidence of clinical mastitis, milk yield and composition in crossbred cows was studied. About 20 healthy crossbred cows were selected at dry-off and randomly allotted either to control or treatment group. Daily milk yield of cows was recorded up to 45 days post-partum and fortnightly separate quarter wise milk samples were collected for estimation of milk composition. While no quarter in the treatment group showed clinical mastitis, 33.33% of quarters in control group showed clinical mastitis within 45 days post-partum. Milk production increased by 9.71, 8.40 and 18.18% during first, second and third fortnight with overall value 11.84% during the entire 45 days post-calving period in DCT treated cows compared to control group. Also, the overall fat-corrected milk, solid-corrected milk and energy-corrected milk production following 45 days post-partum increased significantly (P<0.05) by 22.71, 23.70 and 22.80%, respectively in treated group than control group. However, overall mean milk components such as fat, protein, lactose, SNF and TS remained similar between treatment and control groups. Taken together, the above results indicated that DCT increased milk yield by reducing incidence of clinical mastitis during early lactation.
The Soluble Variant Surface Glycoprotein of African Trypanosomes Is Recognized by a Macrophage Scavenger Receptor and Induces IκBα Degradation Independently of TRAF6-Mediated TLR Signaling1

The GPI residues of soluble variant surface glycoprotein (sVSG) molecules released from the membrane of African trypanosomes during infection induce macrophage activation events. In this study, we demonstrate that the trypanosome sVSG molecule binds to the membrane of murine RAW 264.7 macrophages and activates the NF-κB cascade independently of a TLR-mediated interaction. The binding of fluorochrome-labeled sVSG molecules to macrophage membranes was saturable, was inhibited by the scavenger receptor-specific ligand maleylated BSA, and was followed by rapid intracellular uptake of the molecules and subsequent internalization to lysosomal compartments. Inhibition of cellular phagocytic and endocytic uptake processes by cytochalasin B and monodansylcadaverine, respectively, revealed that sVSG internalization was necessary for IκBα degradation and occurred by an actin-dependent, clathrin-independent process. Activation of RAW 264.7 cells by sVSG following treatment of the cells with the TRAF6 inhibitory peptide DIVK resulted in enhanced NF-κB signaling, suggesting both that TRAF6-dependent TLR activation of the pathway alone is not required for signaling and that TLR pathway components may negatively regulate expression of sVSG-induced signaling. These results demonstrate that stimulation of macrophages by sVSG involves a complex process of receptor-mediated binding and uptake steps, leading to both positive and negative signaling events that ultimately regulate cellular activation.
The Effects of Kindergarten Experiences on Children's Elementary Science Achievement

Recent research on brain development suggests that early childhood education has longitudinal influences on children's cognitive, socioemotional, and behavioral outcomes. The purpose of the study was to determine the effects of kindergarten science activities and children's early science and reading performances on their elementary science achievement. A structural equation model was constructed utilizing data from the Early Childhood Longitudinal Study-Kindergarten Class of 1998-99 (ECLS-K), conducted by National Center for Educational Statistics. Results revealed positive effects of enriched science experiences and reading development in kindergarten on children's science achievement at third grade. Children who were more frequently involved in science activities in a richer science environment in kindergarten had higher levels of science achievement at third grade.
Paraclupea seilacheri sp. nov., a double armored herring (Clupeomorpha, Ellimmichthyiformes) from the Albian limestones of Tlayúa quarry, Puebla, Mexico

Paraclupea seilacheri sp. nov. is described in this paper. This ellimmichthyiform fish from the Albian deposits of the Tlayúa quarry, near Tepexi de Rodríguez, Puebla, central Mexico, shows the diagnostic characters of the superorder Clupeomorpha (the otophysic connection, commissure of the supratemporal sensory canal passing through parietals, and the abdominal scute series), order Ellimmichthyiformes (parietals in contact to each other along the midline of the skull; a beryciform foramen in the anterior ceratohyal; three epurals in the caudal skeleton; and a series of predorsal scutes), and family Paraclupeidae (predorsal scutes with increasing sizes in anterioposterior order and postpelvic abdominal scutes with a strong ventral spine). Additionally, the characters of this new Mexican fish are distinctive and support the creation of a new species of the genus Paraclupea, these include a diamond shaped body moderately high; 18 predorsal scutes strongly ornamented with radiating ridges; most posterior predorsal scutes are subrectangular, wider than long; the abdominal scutes are spatula-like; the dorsal process of posttemporal bone is hypertrophied; and the second uroneural is short and distally reaches the end of the first uroneural. The present finding introduces the second species of the genus Paraclupea; a significative increase in the geographical distribution of this genus in the Northern Hemisphere, from eastern China to the southern North America; and the third North American Cretaceous paraclupeid after Tycheroichthys dunveganensis and Scutatoclupea applegatei.
Possibilities of hyperlink application in spatial research

Possibilities of hyperlink application in spatial research The main aim of the paper is to show the selected ways of analysing, the possible interpretations and expectations concerning the analyses of hyperlinks in spatial research. The connections existing in cyberspace for selected self-government websites of Lower Silesia were shown to illustrate the issue. The analyses were conducted for selected websites of self-government units at all levels functioning in Lower Silesia. The paper presents two approaches to the analysis of hyperlinks: analysis of outlinks and inlinks. The presented results allow us to identify some regularities regarding the functioning of connections in cyberspace versus the connections in the real world. From the perspective of self-government websites it can be concluded that the connections in cyberspace reflect the real connections. In the majority of the analysed cases there is a clear connection with the actual scope of activity. The remaining relationships with administrative cities reflect the significance of these cities for the functioning of self-government units in the social, economic, legal, and administrative conditions. Based on the conducted analyses it can be concluded that the study of hyperlinks may be useful in understanding the relationships between geographical space and cyberspace. They may form a new, interesting field of spatial research. We also found some challenges in the study of hyperlinks' spatial aspects: the identification of consistent criteria for determining the websites' ‘location in space’, the possibility of interpreting the research results and the dynamics of the Internet.
Recent Success Stories on Optimization of Railway Systems

Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway cus- tomers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain devel- oping mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice, with a few notable exceptions. In this paper we address three success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will dis- cuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that math- ematical optimization can support the planning of rolling stock resources. Thus, mathematical models and optimization can lead to a greater effi- ciency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry.
Effect of Calcination Temperature on Titanium Oxide Nanocrystallites in the Anatase Phase Synthesized By Sol-Gel Route

Titanium Oxide (TiO2) nanocrystalline powders in the anatase phase with tetragonal structure with the point group 4/mmm and space group I41/amd–D4h 19 have been synthesized using titanium tetra-isopropoxide as the starting precursor. TG/DTA analysis of the precursor material was carried out in order to fix the calcination temperature for the titanium tetra isopropoxide precursor solution. As-prepared samples were annealed at different temperatures of 400 and 600 °C and their physicochemical properties were examined by means of TG/DTA, XRD, RS, PL, SEM/EDS and DC electrical conductivity studies. X -ray diffraction shows that the as-synthesized samples dried at 100oC in air were amorphous, whereas annealed samples were crystalline and tetragonal structure, belongs to the anatase phase (I41/amd). Raman scattering was used to analyze normal Raman active modes of vibration for the confirmation of phase purity of synthesized anatase TiO2 nanocrystalline with calcination temperatures. Using broad luminescent band, its shape and position were discussed in terms of calcination temperature, particle size and crystallites phase. Morphological observations showed spherical agglomerated grains of micrometer size that constitutes nanosized particles. Elemental analysis indicates that the nanoparticles are essentially TiO2 without impurities and contaminations. The semiconducting behavior, DC electric conductivity and the activation energy of synthesized samples were also measured by the electrical resistance measurement system.
Fine-grained Structure-based News Genre Categorization

Journalists usually organize and present the contents of a news article following a well-defined structure. In this work, we propose a new task to categorize news articles based on their content presentation structures, which is beneficial for various NLP applications. We first define a small set of news elements considering their functions (e.g., introducing the main story or event, catching the reader’s attention and providing details) in a news story and their writing style (narrative or expository), and then formally define four commonly used news article structures based on their selections and organizations of news elements. We create an annotated dataset for structure-based news genre identification, and finally, we build a predictive model to assess the feasibility of this classification task using structure indicative features.
Modular invariance property of association schemes, type II codes over finite rings and finite abelian groups and reminiscences of François Jaeger (a survey)

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COMPARISON OF 2 D AND 3 D APPROACHES FOR THE ALIGNMENT OF UAV AND LIDAR POINT CLOUDS

The automatic alignment of 3D point clouds acquired or generated from different sensors is a challenging problem. The objective of the alignment is to estimate the 3D similarity transformation parameters, including a global scale factor, 3 rotations and 3 translations. To do so, corresponding anchor features are required in both data sets. There are two main types of alignment: i) Coarse alignment and ii) Refined Alignment. Coarse alignment issues include lack of any prior knowledge of the respective coordinate systems for a source and target point cloud pair and the difficulty to extract and match corresponding control features (e.g., points, lines or planes) co-located on both point cloud pairs to be aligned. With the increasing use of UAVs, there is a need to automatically co-register their generated point cloud-based digital surface models with those from other data acquisition systems such as terrestrial or airborne lidar point clouds. This works presents a comparative study of two independent feature matching techniques for addressing 3D conformal point cloud alignment of UAV and lidar data in different 3D coordinate systems without any prior knowledge of the seven transformation parameters. * Corresponding author
Experiments with explicit filtering for LES using a finite-difference method

The equations for large-eddy simulation (LES) are derived formally by applying a spatial filter to the Navier-Stokes equations. The filter width as well as the details of the filter shape are free parameters in LES, and these can be used both to control the effective resolution of the simulation and to establish the relative importance of different portions of the resolved spectrum. An analogous, but less well justified, approach to filtering is more or less universally used in conjunction with LES using finite-difference methods. In this approach, the finite support provided by the computational mesh as well as the wavenumber-dependent truncation errors associated with the finite-difference operators are assumed to define the filter operation. This approach has the advantage that it is also 'automatic' in the sense that no explicit filtering: operations need to be performed. While it is certainly convenient to avoid the explicit filtering operation, there are some practical considerations associated with finite-difference methods that favor the use of an explicit filter. Foremost among these considerations is the issue of truncation error. All finite-difference approximations have an associated truncation error that increases with increasing wavenumber. These errors can be quite severe for the smallest resolved scales, and these errors will interfere with the dynamics of the small eddies if no corrective action is taken. Years of experience at CTR with a second-order finite-difference scheme for high Reynolds number LES has repeatedly indicated that truncation errors must be minimized in order to obtain acceptable simulation results. While the potential advantages of explicit filtering are rather clear, there is a significant cost associated with its implementation. In particular, explicit filtering reduces the effective resolution of the simulation compared with that afforded by the mesh. The resolution requirements for LES are usually set by the need to capture most of the energy-containing eddies, and if explicit filtering is used, the mesh must be enlarged so that these motions are passed by the filter. Given the high cost of explicit filtering, the following interesting question arises. Since the mesh must be expanded in order to perform the explicit filter, might it be better to take advantage of the increased resolution and simply perform an unfiltered simulation on the larger mesh? The cost of the two approaches is roughly the same, but the philosophy is rather different. In the filtered simulation, resolution is sacrificed in order to minimize the various forms of numerical error. In the unfiltered simulation, the errors are left intact, but they are concentrated at very small scales that could be dynamically unimportant from a LES perspective. Very little is known about this tradeoff and the objective of this work is to study this relationship in high Reynolds number channel flow simulations using a second-order finite-difference method.
INFLUENCE OF POLYMER CONCENTRATION ON THE PERMEATION PROPERTIES OF NANOFILTRATION MEMBRANES

Driving force membrane processes seem to be most useful for water treatment. Membranes are very effective in removing a wide variety of water contaminants. Therefore, the use of these processes in water purification to replace or to improve conventional treatment has increased. An inherent problem of membranes is fouling, the accumulation of materials (foulants) near, on, or within the membrane that causes a reduction in the amount of product water over time. As a result of fouling, capital and operating costs of membrane systems are higher, making them less attractive. A membrane is an interphase between two adjacent phases acting as a selective barrier, regulating the transport of substances between the two compartments. The main advantages of membrane technology as compared with other unit operations in (bio) chemical engineering are related to this unique separation principle, i.e. the transport selectivity of the membrane. Separations with membranes do not require additives, and they can be performed isothermally at low temperatues and compared to other thermal separation processes at low energy consumption. Nanofiltration (NF) separate or remove small molecules or ions from a solvent (most often water) by means of pressure – driven filtration through a dense polymeric membrane. Combination of selectivity with a high permeability to water and mechanical strength sufficient to withstand high pressures is achieved by using thin film composite membranes comprising a dense film of 10-200 nm (active layer) supported by a thick asymmetric porous film. In this paper is describing the manufacturing processes of Polyethersulfone membranes (PES). A Polyethersulfone membranes was made with different concentration of polymer in N-Methyl-pyrrolidone (NMP) solvents. The influences of the polymer concentration on the membranes permeation properties were studied. After the preparations all membranes were studied for a comparison with cross flow and dead-end equipments to see the flux and permeability of pure water. The permeation results and the SEM photography show the influence of the polymer concentration, increasing concentration permeation properties are decreasing.
Learning confidence measures in the wild

Confidence measures for stereo earned increasing popularity in most recent works concerning stereo, being effectively deployed to improve its accuracy. While most measures are obtained by processing cues from the cost volume, top-performing ones usually leverage on random-forests or CNNs to predict match reliability. Therefore, a proper amount of labeled data is required to effectively train such confidence measures. Being such ground-truth labels not always available in practical applications, in this paper we propose a methodology suited for training confidence measures in a self-supervised manner. Leveraging on a pool of properly selected conventional measures, we automatically detect a subset of very reliable pixels as well as a subset of erroneous samples from the output of a stereo algorithm. This strategy provides labels for training confidence measures based on machine-learning technique without ground-truth labels. Compared to state-of-the-art, our method is neither constrained to image sequences nor to image content. Experimental results on three challenging datasets with three stereo algorithms and three state-of-the-art confidence measures based on machine-learning techniques confirm the effectiveness of our proposal for self-supervised training.
Discovering the structure of natural language sentences by semi-supervised methods

In this thesis, we focus on the problem of automatically syntactically analyzing a language for which there is no syntactically annotated training data. We explore several methods for cross-lingual transfer of syntactic as well as morphological annotation, ultimately based on utilization of bilingual or multilingual sentence-aligned corpora and machine translation approaches. We pay particular attention to automatic estimation of the appropriateness of a source language for the analysis of a given target language, devising a novel measure based on the similarity of part-of-speech sequences frequent in the languages. The effectiveness of the presented methods has been confirmed by experiments conducted both by us as well as independently by other respectable researchers.
Spatial Patternsof Adoption of Just-in-Time Manufacturing

In this paper we study the spatial pattern of Just-in-Time (JIT) adoption for a sample of medium-sized and large Spanish manufacturing firms. The recent literature has shown that location plays a significant role in the adoption of advanced technologies. We argue that the particular role location characteristics play for technology adoption depends on the type of technology. JIT differs from other advanced manufacturing technologies because it relates directly to the spatial coordination of a firms´ internal production organisation with its external productive environment and depends on the quality of the transport system. Our results confirm the distinctive role of location for JIT adoption even after controlling for industry and plant-specific differences. We find that JIT adoption is greater in smaller cities but with higher accessibility indicating that urban congestion in larger urban areas likely reduces the benefits that firms may obtain from JIT implementation.