Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of DBSCALE Clustering Algorithm for Weather Forecasting

Cluster analysis in data processing could be a main application of business. This investigation describes to gift DBSCALE algorithmic rule that extends enlargement seed choice into a DBSCAN algorithm rule. And also describes the density primarily based cluster conception and also describes its hierarchical extra space OPTICS has been planeed recently, and one among inthe main triumphant approaches to cluster. Aim of this analysis work is to manoeuvre on the advances cluster. During this work the planned procedure focuses on decrease the quantity of seeds points and additionally reduce the execution time cost of looking out neighbourhood information. And hierarchical cluster procedure are often helpful to those attention-grabbing subspaces so as to calculate a latitude for north and south cities and additional calculate line of longitude of various cities and also clustered them. Keywords— Data mining, Data Clustering Analysis, Density Based Clustering, Optics Algorithm, DBSCAN, IDBSCAN, KIDBSAN, DBSCALE.
Formaldehyde Distribution over North America: Implications for Satellite Retrievals of Formaldehyde Columns and Isoprene Emission

[1] Formaldehyde (HCHO) columns measured from space provide constraints on emissions of volatile organic compounds (VOCs). Quantitative interpretation requires characterization of errors in HCHO column retrievals and relating these columns to VOC emissions. Retrieval error is mainly in the air mass factor (AMF) which relates fitted backscattered radiances to vertical columns and requires external information on HCHO, aerosols, and clouds. Here we use aircraft data collected over North America and the Atlantic to determine the local relationships between HCHO columns and VOC emissions, calculate AMFs for HCHO retrievals, assess the errors in deriving AMFs with a chemical transport model (GEOS-Chem), and draw conclusions regarding space-based mapping of VOC emissions. We show that isoprene drives observed HCHO column variability over North America; HCHO column data from space can thus be used effectively as a proxy for isoprene emission. From observed HCHO and isoprene profiles we find an HCHO molar yield from isoprene oxidation of 1.6 ± 0.5, consistent with current chemical mechanisms. Clouds are the primary error source in the AMF calculation; errors in the HCHO vertical profile and aerosols have comparatively little effect. The mean bias and 1σ uncertainty in the GEOS-Chem AMF calculation increase from <1% and 15% for clear skies to 17% and 24% for half-cloudy scenes. With fitting errors, this gives an overall 1σ error in HCHO satellite measurements of 25–31%. Retrieval errors, combined with uncertainties in the HCHO yield from isoprene oxidation, result in a 40% (1σ) error in inferring isoprene emissions from HCHO satellite measurements.
EUCLID: automatic classification of proteins in functional classes by their database annotations

UNLABELLED A tool is described for the automatic classification of sequences in functional classes using their database annotations. The Euclid system is based on a simple learning procedure from examples provided by human experts. AVAILABILITY Euclid is freely available for academics at http://www.gredos. cnb.uam. es/EUCLID, with the corresponding dictionaries for the generation of three, eight and 14 functional classes. CONTACT E-mail: valencia@cnb.uam. es SUPPLEMENTARY INFORMATION The results of the EUCLID classification of different genomes are available at http://www.sander. ebi.ac. uk/genequiz/. A detailed description of the different applications mentioned in the text is available at http://www.gredos. cnb.uam. es/EUCLID/Full_Paper
Resource alignment in the category management of builders’ merchants

Previous retailer–supplier research reports both positive and negative collaboration outcomes. Resource alignment, or how collaborating actors’ resources affect each other, is a concept that has been brought forward to explain when collaboration increases performance. As the category management of builders’ merchants (BMs) involves actors with different sets of resources, the resource alignment framework can be used to better understand the outcomes of collaboration in category management. The aim of this paper is to explore resource alignment among actors involved in the category management of BMs. The paper is based on interviews with top managers in Swedish BMs. Complementary and supplementary resources held by the involved actors are identified for four distinguished category management activities. Resources needed to further improve the business are also identified. Three propositions are formulated, explaining how supplementary and complementary resources are interrelated and how the situation influences the need for supplementary resources. The description of resource alignment supports retailers and their suppliers concerning how to assign roles and responsibilities in category management activities. While the retailers themselves are often well equipped to manage pricing and inventory management, the supplier can support assortment and marketing management.
Memory Capacity for Sequences in a Recurrent Network with Biological Constraints

The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage and replay of sequences of patterns that represent behavioral events. Here we present a theoretical framework to calculate a sparsely connected network's capacity to store such sequences. As in CA3, only a limited subset of neurons in the network is active at any one time, pattern retrieval is subject to error, and the resources for plasticity are limited. Our analysis combines an analytical mean field approach, stochastic dynamics, and cellular simulations of a time-discrete McCulloch-Pitts network with binary synapses. To maximize the number of sequences that can be stored in the network, we concurrently optimize the number of active neurons, that is, pattern size, and the firing threshold. We find that for one-step associations (i.e., minimal sequences), the optimal pattern size is inversely proportional to the mean connectivity c, whereas the optimal firing threshold is independent of the connectivity. If the number of synapses per neuron is fixed, the maximum number P of stored sequences in a sufficiently large, nonmodular network is independent of its number N of cells. On the other hand, if the number of synapses scales as the network size to the power of 3/2, the number of sequences P is proportional to N. In other words, sequential memory is scalable. Further-more, we find that there is an optimal ratio r between silent and nonsilent synapses at which the storage capacity = P/[c (1 +r)N] assumes a maximum. For long sequences, the capacity of sequential memory is about one order of magnitude below the capacity for minimal sequences, but otherwise behaves similar to the case of minimal sequences. In a biologically inspired scenario, the information content per synapse is far below theoretical optimality, suggesting that the brain trades off error tolerance against information content in encoding sequential memories.
Named data aggregation in wireless sensor networks

In this paper, we present a novel named data aggregation method dedicated to wireless sensor networks. The method relies on an adaptation of the CCNx protocol implementation that we have extended with in-network processing functions to aggregate named data efficiently. We have implemented and tested our solution with the Contiki operating system which is an operating system for resources-constrained embedded systems and wireless sensor networks. Our simulation and measurement results using the Cooja simulator and physical nodes show that our solution has a small overhead in terms of exchanged messages and provides acceptable data retrieval delays.
Trend Analysis of News Topics on Twitter

paper focus on trend analysis of news topics on Twitter, which include trend prediction and reasons analysis for the changes of trend. We first present a novel method to predict the trends of topics on Twitter based on MACD (Moving Average Convergence-Divergence) indicator. It is one of the simplest and most effective tendency indicators in technique analysis of stocks. We improve the original MACD indicator according to the characteristics of news topics on Twitter, define a new concept as trend momentum and use it to predict the trend of news topics. Then, we propose some reasons for the variation of trends. Experimental results show that the trend prediction is simple and effective. And, the reasons for variation of trends are also verified.
Bayesian Network Parameter Learning using EM with Parameter Sharing

This paper explores the effects of parameter sharing on Bayesian network (BN) parameter learning when there is incomplete data. Using the Expectation Maximization (EM) algorithm, we investigate how varying degrees of parameter sharing, varying number of hidden nodes, and different dataset sizes impact EM performance. The specific metrics of EM performance examined are: likelihood, error, and the number of iterations required for convergence. These metrics are important in a number of applications, and we emphasize learning of BNs for diagnosis of electrical power systems. One main point, which we investigate both analytically and empirically, is how parameter sharing impacts the error associated with EM's parameter estimates.
Implications of hypoxia tolerance for wetland refugia use in Lake Nabugabo, Uganda

Aquatic hypoxia can affect predator-prey interactions by altering the success rate of the predator and/or the vulnerability of prey. For example, in the Lake Victoria basin of East Africa, native prey exploit hypoxic wetlands as refugia from predation by introduced Nile perch (Lates niloticus). Here, it is predicted that species exploitation of wetlands depends on their hypoxia tolerance relative to the heterogeneity of wetland hypoxia. In this study, we compared the hypoxia tolerance of four fish taxa that differ in their use of hypoxic wetlands in Lake Nabugabo, Uganda: the cichlid Pseudocrenilabrus multicolor victoriae that inhabits the dense swamp interior; and three taxa that inhabit wetland ecotones including Nile tilapia (Oreochromis niloticus), L. niloticus and juvenile endemic haplochromine cichlids. We characterised hypoxia tolerance by exposing fish to progressive hypoxia and quantifying variation in aquatic surface respiration (ASR). The effect of body size on tolerance was explored in L. niloticus by quantifying ASR behaviour across a range of size classes. ASR behaviour was also compared between O. niloticus groups from wetland versus open-water habitats to detect habitat-associated intraspecific variation. The most tolerant taxon was the swamp specialist P. multicolor, indicated by its low ASR thresholds and small percentage of fish using ASR during the final sample interval. The other three taxa did not differ in ASR behaviour, and no differences were detected between O. niloticus groups. Body size effects were present for L. niloticus suggesting a lower tolerance to hypoxia in larger-bodied individuals, thus limiting their ability to penetrate wetlands.
Application of an interleukin 2 slow delivery system to the immunotherapy of established murine colon 26 adenocarcinoma liver metastases.

We evaluated the antitumor effect of an interleukin 2 (IL-2) slow delivery system, the IL-2 minipellet, using a murine hepatic metastasis model. The IL-2 minipellet consists of atelocollagen derived from natural bovine skin together with 1 x 10(6) units of recombinant IL-2. Administration of the IL-2 minipellet was performed into the spleens of BALB/c mice after translocation of the spleens to the s.c. position. Administration produced detectable serum IL-2 levels for 72 h. The IL-2 minipellet was evaluated for its efficacy against hepatic metastases from colon 26 adenocarcinoma in the BALB/c mice. Both the administration of the IL-2 minipellet alone and its combination with the injection of 5 x 10(7) lymphokine-activated killer cells resulted in significant reductions of the number of metastatic nodules. Moreover, increased survival of mice bearing colon 26 adenocarcinoma was noted in these two treatment groups. To investigate the mechanism of the IL-2 minipellet activity, we tested the lytic potential of splenocytes obtained after administration of the IL-2 minipellet in a 51Cr release assay. Cytotoxicity against YAC-1 cells and colon 26 cells was significantly augmented on Day 2 after minipellet administration. These results demonstrated that local administration of the IL-2 minipellet into the hepatic circulation was extremely effective against metastatic liver cancer.
Improved Approximation Algorithms for Earth-Mover Distance in Data Streams

For two multisets $S$ and $T$ of points in $[\Delta]^2$, such that $|S| = |T|= n$, the earth-mover distance (EMD) between $S$ and $T$ is the minimum cost of a perfect bipartite matching with edges between points in $S$ and $T$, i.e., $EMD(S,T) = \min_{\pi:S\rightarrow T}\sum_{a\in S}||a-\pi(a)||_1$, where $\pi$ ranges over all one-to-one mappings. The sketching complexity of approximating earth-mover distance in the two-dimensional grid is mentioned as one of the open problems in the literature. We give two algorithms for computing EMD between two multi-sets when the number of distinct points in one set is a small value $k=\log^{O(1)}(\Delta n)$. Our first algorithm gives a $(1+\epsilon)$-approximation using $O(k\epsilon^{-2}\log^{4}n)$ space and works only in the insertion-only model. The second algorithm gives a $O(\min(k^3,\log\Delta))$-approximation using $O(\log^{3}\Delta\cdot\log\log\Delta\cdot\log n)$-space in the turnstile model.
Question categorization using SVM based on different term weighting methods

— This paper deals with the performance of Question Categorization based on four different term weighting methods. Term weighting methods such as tf*idf, qf*icf, iqf*qf*icf and vrf together with SVM classifier were used for categorization. From the experiments conducted using both linear and nonlinear SVM, term weighting method iqf*qf*icf showed better performance in question categorization than other methods.
A \forgetful" Weak Consistency Protocol

The single address space or DSM memory model has been the focus of substantial research. One major issue is providing a usable programming model with minimum overheadd12, 11]. Normally DSM systems allow the programmer to assume that the program is executing in a sequentially consistent manner. To achieve high performance DSM memory protocols use information derived from program synchronisation operations to perform consistency activities only when absolutely necessary. A survey of recent publications indicates that development has settled on about three major protocols: Weak Consistency, Release Consistency, and Processor Consistency (WC,RC,PC))13]. In order to generate further improvement in performance, protocols of these types need to be analysed and optimised. Many optimisations have already been introduced. Write pipelining has been proposed to reduce update delayss10]. Lazy invalidation policies have been investigatedd9]. Attempts have also been made to use knowledge about how data objects are manipulated to customize the manner in which consistency is enforcedd3]. Most approaches assume that conveying written data to memory and carrying out any associated consistency activity are an indivisible unit. Often called a \write perform". This paper examines the beneets of decoupling the memory update process from the dissemination of invalidations. Forgetful consistency uses a low cost cache hardware modiication to perform selective cache ushing on each node. This purges shared data at consistency events, eliminating the need for invalidation messages and the associated hardware. Forgetful consistency performs very well in comparison to a standard write pipelined weak consistency protocol. The forgetful protocol eliminates invalidation messages, and results in an overall reduction in hardware complexity. A signiicant byproduct is an overall decrease in network utilisation by each application. These factors combine to yield improvements in execution speed of up to 30% for some applications on large machines. Even larger improvements can be obtained for some codes on smaller architectures.
Opinion mining about a product by analyzing public tweets in Twitter

In this paper we have explained the detailed work done in developing a system which can be used for the purpose of opinion analysis of a product or a service. The system readily processes the tweets by pulling data from tweeter posts, preprocessing it and connecting to Alchemy API by REST call method. and showing the result graphically. We have given the analysis for the product Samsung Galaxy Our proposed system access the public tweets by API and filters them for Samsung Galaxy. The analysis is being carried out as to classify the sentiment as positive, negative or neutral.
Primordial Germ Cell-Like Cells Differentiated In Vitro from Skin-Derived Stem Cells

Background We have previously demonstrated that stem cells isolated from fetal porcine skin have the potential to form oocyte-like cells (OLCs) in vitro. However, primordial germ cells (PGCs), which must also be specified during the stem cell differentiation to give rise to these putative oocytes at more advanced stages of culture, were not systematically characterized. The current study tested the hypothesis that a morphologically distinct population of cells derived from skin stem cells prior to OLC formation corresponds to putative PGCs, which differentiate further into more mature gametes. Methodology/Principal Findings When induced to differentiate in an appropriate microenvironment, a subpopulation of morphologically distinct cells, some of which are alkaline phosphatase (AP)-positive, also express Oct4, Fragilis, Stella, Dazl, and Vasa, which are markers indicative of germ cell formation. A known differentially methylated region (DMR) within the H19 gene locus, which is demethylated in oocytes after establishment of the maternal imprint, is hypomethylated in PGC-like cells compared to undifferentiated skin-derived stem cells, suggesting that the putative germ cell population undergoes imprint erasure. Additional evidence supporting the germ cell identity of in vitro-generated PGC-like cells is that, when labeled with a Dazl-GFP reporter, these cells further differentiate into GFP-positive OLCs. Significance The ability to generate germ cell precursors from somatic stem cells may provide an in vitro model to study some of the unanswered questions surrounding early germ cell formation.
The Effect of User Perceptions of System Features on ENS Assessment

Electronic negotiation systems (ENSs) feature a wide range of capabilities for setting up and conducting negotiations between the parties (Kersten and Lai 2007). These capabilities include both communication facilities, as well as analytical features that help the negotiator to manage his/her preferences as well as inform decision making in constructing offers and assessing counter-offers. In this regard it would be valuable for the ENS designers to know which design features of these systems are being perceived as useful by the negotiators. This works aims at understanding how the user perceptions of ENS features influence the assessment of ENS.
Targeting Sphingosine Kinase 1 in Carcinoma Cells Decreases Proliferation and Survival by Compromising PKC Activity and Cytokinesis

Sphingosine kinases (SK) catalyze the phosphorylation of proapoptotic sphingosine to the prosurvival factor sphingosine 1-phosphate (S1P), thereby promoting oncogenic processes. Breast (MDA-MB-231), lung (NCI-H358), and colon (HCT 116) carcinoma cells were transduced with shRNA to downregulate SK-1 expression or treated with a pharmacologic SK-1 inhibitor. The effects of SK-1 targeting were investigated by measuring the level of intracellular sphingosine, the activity of protein kinase C (PKC) and cell cycle regulators, and the mitotic index. Functional assays included measurement of cell proliferation, colony formation, apoptosis, and cell cycle analysis. Downregulation of SK-1 or its pharmacologic inhibition increased intracellular sphingosine and decreased PKC activity as shown by reduced phosphorylation of PKC substrates. In MDA-MB-231 cells this effect was most pronounced and reduced cell proliferation and colony formation, which could be mimicked using exogenous sphingosine or the PKC inhibitor RO 31-8220. SK-1 downregulation in MDA-MB-231 cells increased the number of cells with 4N and 8N DNA content, and similar effects were observed upon treatment with sphingosine or inhibitors of SK-1 or PKC. Examination of cell cycle regulators unveiled decreased cdc2 activity and expression of Chk1, which may compromise spindle checkpoint function and cytokinesis. Indeed, SK-1 kd cells entered mitosis but failed to divide, and in the presence of taxol also failed to sustain mitotic arrest, resulting in further increased endoreduplication and apoptosis. Our findings delineate an intriguing link between SK-1, PKC and components of the cell cycle machinery, which underlines the significance of SK-1 as a target for cancer therapy.
Joint segmentation and classification with fully convolutional networks

This paper describes a joint segmentation and classification approach that exploits global image features to validate the predictions from local appearance descriptors and to ensure their consistent labeling. The in-between interplay is encoded by a parameter-learning process of a unified deep learning model embedding a fully convolution network (FCN) portion. Although FCN has a relatively large recept field, the integration of the image content as a whole makes the prediction more reasonable and logical, since coincidences in local neighborhoods are more likely to be depressed given global guidance. We also propose a content-sensitive co-occurrence priori for label compatibility, which provides additional constraints for bilateral filtering based CRF to delineate the object boundary. Experimental results show that our model outperforms most of the state-of-the-art works with an intersection-over-union score of 77.0% on the Pascal VOC 2012 segmentation benchmark.
Encouraging Diversity in the Rural Classroom.

This report addresses the need to assess teacher attitudes toward teaching culturally diverse youth in West Virginia. West Virginia ranks as the second most rural state in the nation, with a 64 percent rural population. Nevertheless, West Virginia's culture is becoming increasingly pluralistic, and many students are finding that they cannot identify with the middle-class values, perceptions, and expectations of their teachers. To address this problem, teacher training programs should provide teachers with the awareness and the competencies to meet the instructional needs of students from diverse backgrounds. The Cultural Difference Theory suggests that minority children are unsuccessful in school because schools do not capitalize on the experiences that these children bring to the learning environment. Therefore, teachers should integrate experiences from the students' culture into the curriculum, place less emphasis on ethnicity and social characteristics, and accentuate the individual strengths of students. Also discussed is the importance of creating an effective learning environment and developing special programs to encourage acceptance of cultural diversity by both teachers and students. (LP) *ithicir*h*ft***Ich**ItYt**************h****hich********k********************* Reproductions supplied by ORS are the best that can be made from the original document. ***********************************************************************