Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Rare Itemset with Automated Support Thresholds

Problem statement: Frequent itemset mining is an important task in data mining to discover the hidden, interesting associations between items in the database based on the user-specified support and confidence thresholds. Approach: In order to find important associations, an appropriate support threshold has to be specified. The support threshold plays a key role in deciding the interesting itemsets. The rare itemsets may not found if a high threshold is set. Some uninteresting itemsets may appear if a low threshold is set. Results: This study proposes an approach to obtain the frequent itemsets involving rare items by setting the support thresholds automatically. Experimental results show that this approach produces rare and frequent itemsets in sparse and dense datasets. According to T20I6D100K, 97.76% of the FIs are generators wherein Mushrooms 1.38% of the FIs are the generators. Conclusion: The proposed algorithm produces both frequent and rare itemsets in an effective way. In future, computational efforts can still be reduced by implementing the algorithm as parallel algorithm.
Semisupervised nonlinear feature extraction for image classification

Feature extraction is of paramount importance for an accurate classification of remote sensing images. Techniques based on data transformations are widely used in this context. However, linear feature extraction algorithms, such as the principal component analysis and partial least squares, can address this problem in a suboptimal way because the data relations are often nonlinear. Kernel methods may alleviate this problem only when the structure of the data manifold is properly captured. However, this is difficult to achieve when small-size training sets are available. In these cases, exploiting the information contained in unlabeled samples together with the available training data can significantly improve data description by defining an effective semisupervised nonlinear feature extraction strategy. We present a novel semisupervised Kernel Partial Least Squares (KPLS) algorithm for non-linear feature extraction. The method relies on combining two kernel functions: the standard RBF kernel using labeled information and a generative kernel directly learned by clustering the data. The effectiveness of the proposed method is successfully illustrated in multi- and hyper-spectral remote sensing image classification: accuracy improvements between +15 - 20% over standard PCA and +10% over advanced kernel PCA and KPLS for both images is obtained. Matlab code is available at http://isp.uv. es for the interested readers.
Development of advanced diagnostic functions in very high volume automotive sensor applications

We present an opportunity for an overall system improvement of a very high volume automotive application based on advanced low-level on-chip signal diagnosis. We put our focus on advanced on-sensor diagnosis and added functionality at the very lowest level close to the magnetic signal of an automotive wheel speed sensor. Besides adding diagnosis for the sensor, this enables diagnostics of the entire mechanical system including the magnetic circuit which is crucial for correct operation. We followed a pre-development path starting with extensive automated measurements, simulations, a micro-controller based implementation, a field programmable gate array (FPGA) and finally a fully integrated application specific integrated circuit (ASIC). ASIC-blocks can be used for integration in the series product. We demonstrate the low-resource implementation of a lowest level sensor diagnostic signal processing circuit based on harmonic distortion analysis. The development path is reviewed with focus on reuse in the light of the specific requirements, advantages and drawbacks of each approach.
Design approaches for taming complexity

We examine the essential characteristics of system complexity and simplicity and we describe a set of general design heuristics to address complexity. We distinguish inherent, irreducible complexity from perceived complexity. We illustrate a little theory of complexity with examples drawn from ultra-large-scale systems: telephony, the Internet, and the power grid. We then show how a toolkit of design approaches that have been developed by system and software architects over the last 15 years can tackle complexity. In particular, architectural patterns and tactics provide systematic means to reduce and manage complexity, both intrinsic and perceived.
Impact of front-back gate coupling on low frequency noise in 28 nm FDSOI MOSFETs

Low-frequency (LF) noise has been studied on 28 nm FDSOI devices with ultra-thin silicon film (7 nm) and thin buried oxide (25 nm). A strong dependence of the noise level on the combination of the front and back biasing voltages was observed, and justified by the coupling effect of both Si/High-K dielectric and Si/SiO2 interface noise sources (channel/front oxide and channel/buried oxide), combined with the change of the Remote Coulomb scattering. From comparisons of the experimental and simulation results, it is shown that the main reason of this dependence is the distance of the charge distribution centroid from the interfaces, which is controlled by both front and back-gate bias voltages, and the way this distance affects the Remote Coulomb scattering coefficient a. A new LF noise model approach is proposed to include all these effects. This also allows us to assess the oxide trap density values for both interfaces.
Isolation and characterization of the papaya MADS-box E-class genes , CpMADS 1 and CpMADS 3 , and a TM 6 lineage gene CpMADS 2

Papaya (Carica papaya L.) plants are polygamous, with female, male, and hermaphroditic flowers. To understand the roles of MADS-box genes in flower development and sex determination, we cloned cDNAs of E-class genes CpMADS1 and CpMADS3 and a TM6 lineage of the B-class gene CpMADS2 from young flower buds of papaya. Reverse transcription-polymerase chain reaction (RT-PCR) and real-time PCR analyses revealed that CpMADS1 and CpMADS3 were preferentially expressed in the carpel and also in petals and stamens. CpMADS2 was expressed in both petals and stamens early during floral development. Comparison of 10 papaya genotypes of 5 different sex phenotypes hermaphrodite, male, female, progeny-all-hermaphrodite, and progeny-all-male by Southern blot analysis of genomic DNAs with probes of the 3 genes revealed similar restriction patterns and copy
Differences in effectiveness of the active living every day program for older adults with arthritis.

OBJECTIVE The authors explored whether demographic and psychosocial variables predicted differences in physical activity for participants with arthritis in a trial of Active Living Every Day (ALED). METHOD Participants (N = 280) from 17 community sites were randomized into ALED or usual care. The authors assessed participant demographic characteristics, self-efficacy, outcome expectations, pain, fatigue, and depressive symptoms at baseline and physical activity frequency at 20-wk follow-up. They conducted linear regression with interaction terms (Baseline Characteristic × Randomization Group). RESULTS Being female (p ≤ .05), less depressed (p ≤ .05), or younger (p ≤ .10) was associated with more frequent posttest physical activity for ALED participants than for those with usual care. Higher education was associated with more physical activity for both ALED and usual-care groups. DISCUSSION ALED was particularly effective for female, younger, and less depressed participants. Further research should determine whether modifications could produce better outcomes in other subgroups.
AERIS: an integrated domain information system for aerospace science and technology

Purpose – The purpose of this paper is to discuss the methodology in building an integrated domain information system with illustrations that provide proof of conceptDesign/methodology/approach – The present work studies the usual search engine approach to information and its pitfalls. A methodology was adopted for construction of a domain‐based information system, known as Aerospace Information System (AERIS), comprising six distinct steps in identifying and sourcing, evaluating and then technically integrating resources into the information system. AERIS is an integrated gateway for resources in the domain of aerospace science and technology. AERIS is designed to provide information from varied sources such as formal publications (e.g. articles), aggregators (e.g. harvesters) and also informal resources such as blogs and discussion fora. Interaction is provided through a simple user interface.Findings – The domain‐based information system with focussed collection and services serves patrons with more pr.
A new event-driven network simulator for Delay-Tolerant Networks (DTNs)

As wireless networking technologies have evolved, wireless networks are deployed in wider areas. In some of them, end-to-end paths may not be guaranteed due to high mobility or low density of network nodes. Delay/Disruption Tolerant Networks (DTNs) or Intermittently Connected Networks (ICNs) are proposed to handle packet delivery in those networks. In DTNs, network simulation may play a critical role for developing new technologies since it is very expensive and time-consuming to perform real experiments. In this paper, we present a new simulation tool for DTNs. This tool is developed with an event-driven manner to accommodate discrete events in packet delivery processes in DTNs, and also it is highly flexible and easily extensible for developing new protocols. We validate the tool with well-known mathematical models of DTNs.
The effects of insulin on mesenteric blood flow in anaesthetized pigs

Infusion of insulin in anaesthetized pigs has been shown to cause an increase in renal blood flow and a decrease in coronary blood flow, which were the net result of a vasoconstriction involving sympathetic α‐adrenoceptor‐mediated mechanisms and of a local vasodilatation involving the endothelial release of nitric oxide. In the present study, the effect of insulin on superior mesenteric blood flow was examined in pentobarbitone‐anaesthetized pigs at constant heart rate, aortic blood pressure, left ventricular contractility and blood levels of glucose and potassium. In 10 pigs, infusion of 0.004 IU kg −1 min−1 of insulin increased mesenteric flow. In five of these pigs, intravenous phentolamine enhanced the increase in mesenteric flow elicited by insulin, a response which was abolished by the subsequent injection of Nω‐nitro‐l‐arginine methyl ester (l‐NAME) into the mesenteric artery. In the remaining five pigs, infusion of insulin after intramesenteric injection of l‐NAME caused a decrease in mesenteric flow. This response was abolished by the subsequent intravenous administration of phentolamine. The present study showed that infusion of insulin in anaesthetized pigs primarily caused a mesenteric vasodilatation, which was the net result of two opposite effects, namely a predominant vasodilatation mediated by the endothelial release of nitric oxide and a sympathetic vasoconstrictor mechanism mediated by α‐adrenoceptors.
Development of bone marrow mesenchymal stem cell culture in vitro.

OBJECTIVE To review the in vitro development of bone marrow mesenchymal stem cells culture (BM-MSC). DATA SOURCES The data cited in this review were mainly obtained from articles listed in Medline and PubMed. The search terms were "bone marrow mesenchymal stem cell" and "cell culture". STUDY SELECTION Articles regarding the in vitro development of BM-MSCs culture, as well as the challenge of optimizing cell culture environment in two-dimensional (2D) vs. 3D. RESULTS Improving the culture conditions increases the proliferation and reduces the differentiation. Optimal values for many culture parameters remain to be identified. Expansion of BM-MSCs under defined conditions remains challenging, including the development of optimal culture conditions for BMSC and large-volume production systems. CONCLUSIONS Expansion of BM-MSCs under defined conditions remains challenges, including the development of optimal culture conditions for BMSC and scale-up to large-volume production systems. Optimal values for many culture parameters remain to be identified.
Mimir: Memory-Efficient and Scalable MapReduce for Large Supercomputing Systems

In this paper we present Mimir, a new implementation of MapReduce over MPI. Mimir inherits the core principles of existing MapReduce frameworks, such as MR-MPI, while redesigning the execution model to incorporate a number of sophisticated optimization techniques that achieve similar or better performance with significant reduction in the amount of memory used. Consequently, Mimir allows significantly larger problems to be executed in memory, achieving large performance gains. We evaluate Mimir with three benchmarks on two highend platforms to demonstrate its superiority compared with that of other frameworks.
Topical coal tar alone and in combination with oral methotrexate in management of psoriasis : a retrospective analysis.

Thirty five patients admitted with psoriasis were analysed. 16 patients received 20% crude coal tar and 19 patients received 20% crude coal tar along with methotrexate in a weekly oral schedule (15mg/wk). After 4 weeks of therapy there was total clearence in 52.6% of the patients with combination therapy, whereas only 12.5% of the patients with conventional therapy achieved this.
An Adaptive Loop Subdivision Algorithm for Keeping Local Features with Mesh Segmentation

How to keep local features of the mesh and adaptive subdivision becomes the research hotspot. Therefore, this paper proposes an adaptive subdivision algorithm with mesh segmentation. This algorithm puts forward a new method of the initial segmentation based on the mesh analyses of the regional growth. And on the basis of the Loop subdivision, the paper gives an adaptive subdivision that can effectively keep local features of triangle meshes. Experimental results show the algorithm, not only holds ideal smooth surface and improves the speed of model rendering, but also overcomes the shortcoming of uniform grid.
Part 11: Pediatric Basic Life Support and Cardiopulmonary Resuscitation Quality

Reprint: The American Heart Association requests that this document be cited as follows: Atkins DL, Berger S, Duff JP, Gonzales JC, Hunt EA, Joyner BL, Meaney PA, Niles DE, Samson RA, Schexnayder SM. Part 11: pediatric basic life support and cardiopulmonary resuscitation quality: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation . 2015;132(suppl 2):S519–S525. Reprinted with permission of the American Heart Association, Inc. This article has been published in Circulation . This 2015 American Heart Association (AHA) Guidelines Update for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC) section on pediatric basic life support (BLS) differs substantially from previous versions of the AHA Guidelines.1 This publication updates the 2010 AHA Guidelines on pediatric BLS for several key questions related to pediatric CPR. The Pediatric ILCOR Task Force reviewed the topics covered in the 2010 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations and the 2010 council-specific guidelines for CPR and ECC (including those published by the AHA) and formulated 3 priority questions to address for the 2015 systematic reviews. In the online version of this document, live links are provided so the reader can connect directly to those systematic reviews on the International Liaison Committee on Resuscitation (ILCOR) Scientific Evidence Evaluation and Review System (SEERS) website. These links are indicated by a superscript combination of letters and numbers (eg, Peds 709). We encourage readers to use the links and review the evidence and appendices. A rigorous systematic review process was undertaken to review the relevant literature to answer those questions, resulting in the 2015 International Consensus on CPR and ECC Science With Treatment Recommendations, “Part 6: Pediatric Basic Life Support and Pediatric Advanced Life Support. ”2,3 This 2015 Guidelines Update covers only those topics reviewed as …
Pleiotropic Effects of YC-1 Selectively Inhibit Pathological Retinal Neovascularization and Promote Physiological Revascularization in a Mouse Model of Oxygen-Induced Retinopathy

Vascular endothelial growth factor (VEGF) and inducible nitric-oxide synthase (iNOS) have been implicated in ischemia-induced retinal neovascularization. Retinal ischemia has been shown to induce VEGF and iNOS expression. It has been postulated that one of the crucial consequences of iNOS expression in the ischemic retina is the inhibition of angiogenesis. Furthermore, iNOS was shown to be overexpressed in Müller cells from patients with diabetic retinopathy. YC-1, a small molecule inhibitor of hypoxia-inducible factor (HIF)-1α, has been shown to inhibit iNOS expression in various tissue models. Our aim was to assess the pleiotropic effects of YC-1 in an oxygen-induced retinopathy (OIR) mouse model and evaluate its therapeutic potential in HIF-1- and iNOS-mediated retinal pathologies. Dual-injections of YC-1 into the neovascular retinas decreased the total retinopathy score, inhibited vaso-obliteration and pathologic tuft formation, and concomitantly promoted physiological retinal revascularization, compared with dimethyl sulfoxide (DMSO)-treated group. Furthermore, YC-1-treated retinas exhibited a marked increase in immunoreactivities for CD31 and von Willebrand factor and displayed significant inhibition in HIF-1α protein expression. Furthermore, YC-1 down-regulated VEGF, erythropoietin, endothelin-1, matrix metalloproteinase-9, and iNOS message and protein levels. When hypoxic Müller and neuoroglial cells were treated with YC-1, iNOS mRNA and protein levels were reduced in a dose-dependent fashion. We demonstrate that YC-1 inhibits pathological retinal neovascularization by exhibiting antineovascular activities, which impaired ischemia-induced expression of HIF-1 and its downstream angiogenic molecules. Furthermore, YC-1 enhanced physiological revascularization of the retinal vascular plexuses via the inhibition of iNOS mRNA and protein expressions. The pleiotropic effects of YC-1 allude to its possible use as a promising therapeutic iNOS inhibitor candidate for the treatment of retinal neovascularization.
Improved Product Ranking For Recommendation Systems

In the new area of information technology, the most important and recognition machine learning technique is Recommender engine. Vast numbers of knowledge discovery techniques are applied by recommender system to the problem of making personalized recommendation for product, information and services during a live interaction (5) . The users which have no sufficient ability to evaluate the, potentially overwhelming, numbers of alternatives, at that time a recommender system is very helpful to those users. Recommender systems provide a personalized and items which are included in ranked list by predicting what the most suitable items are, based on the user's history, preferences and constraints (2) . RS are k -nearest item based collaborative filtering approach. They are obtaining on web which is intelligent. Vast amount of information is available on the web and many visitors which are visit the website that possess the challenges for recommender systems in recent years. The challenges are: They generate high quality recommendations, accomplish lots of recommendations per second for millions of users and items and achieving high data sparsity (5) . The Recommendation Engine Provides the functionality to Ecommerce portal. Where the items are added to shopping cart and similar items are recommended to the user based on their purchase patterns. Recommendation Engine will analyze huge Data sets of User purchase pattern and recommend items to online users based on Machine Learning Algorithms. Keyword: Recommender System, Evaluate, Data Sparsity
Interaction of HLA-DRB1 alleles with CTLA-4 in the predisposition to Graves' disease: the impact of DRB1*07.

OBJECTIVE To study interactions between the two most widely confirmed Graves' disease (GD) loci: HLA-DRB1 and CTLA-4. HLA-DRB1*03 (risk allele) and DRB1*07 (protective allele) were analyzed in this aspect, the linked TNF G(-308)A polymorphism was also considered. DESIGN A case-control study of 429 patients with GD compared to 308 healthy subjects. The impact of genes and their interactions were analyzed by stepwise logistic regression. RESULTS The independent effects of DRB1*03 and DRB1*07 were confirmed in our study both by stratification studies and logistic regression. CTLA-4 did not appear to be associated with GD when the interactions with other genes were considered. By logistic regression we observed a significant interaction between DRB1*07 and CTLA-4 and revealed that CTLA-4 49G attenuated the DRB1*07-related protection, the effect noticed also in three-way stratification studies. We confirmed that the TNF G(-308)A polymorphism is only a marker of the DRB1 status. CONCLUSION Our results stress the importance of complex gene interactions in the multigene predisposition to GD. The interactions between two predisposing loci, DRB1 and CTLA-4, are exerted rather by DRB1*07 than DRB1*03 allele: CTLA-4 acts via switching off the protective DRB1*07 influence, whereas the effect of DRB1*03 is independent.
Texture analysis and fracture identification of lower extremity bones X-ray images

Lower limb bones or lower limb component related to the torso with pelvic ankle interference can be fractured. Fractures can be detected automatically take advantage x-ray images performed using feature extraction methods. Feature Extraction helpful to know existence and location of fracture with x-ray images. This research apply Gray Level Co-Occurrence Matrix (GLCM) and K-Means Clustering Algorithm to analyze texture of lower extremity bones or lower limb bones x-ray images especially on the lower leg bones (cruris) consisting of two long bones (tibia) and leg bone (fibula), as well as the kneecap bone (patella). The GLCM feature extraction process yields an image characteristic with four parameters, i.e. Contrast, Correlation, Energy, and Homogeneity done before clustering steps for identification of fractured or non-fractured (normal) bones. The results accuracy texture analysis of lower extremity bones x-ray images using GLCM Feature Extraction Method and K-Means Clustering Algorithm is 80 percent.