Miracle-dz/UniFAR-FTUs huggingface dataset:
Vascular Calcification in Animal Models of CKD: A Review

Vascular calcification is a significant contributor to the cardiovascular mortality observed in chronic kidney disease (CKD). This review discusses the animal models (5/6 nephrectomy, mouse electrocautery model and dietary adenine) that have been employed in the study of vascular calcification outcomes in CKD. Rodent models of CKD generate a range of severity in the vascular calcification phenotype. Major limitations of the 5/6th nephrectomy model include the requirement for surgery and the need to use either excessive dietary phosphorus or vitamin D. Major limitations of the mouse electrocautery model include the requirement for surgery, the mortality rate when very advanced CKD develops, and resistance to vascular calcification without the use of transgenic animals. This is balanced against the major advantage of the ability to study transgenic animals to further understand the mechanisms associated with either the acceleration or inhibition of calcification. Dietary adenine generates severe CKD and does not require surgery. The major disadvantage is the weight loss that ensues when rats receive a diet containing 0.75% adenine. In summary, animal models are useful to study CKD-associated vascular calcification and the results obtained in these pre-clinical animal studies appear to translate to the evidence, however limited, which exists in humans with CKD.
zSense: Enabling Shallow Depth Gesture Recognition for Greater Input Expressivity on Smart Wearables

In this paper we present zSense, which provides greater input expressivity for spatially limited devices such as smart wearables through a shallow depth gesture recognition system using non-focused infrared sensors. To achieve this, we introduce a novel Non-linear Spatial Sampling (NSS) technique that significantly cuts down the number of required infrared sensors and emitters. These can be arranged in many different configurations; for example, number of sensor emitter units can be as minimal as one sensor and two emitters. We implemented different configurations of zSense on smart wearables such as smartwatches, smartglasses and smart rings. These configurations naturally fit into the flat or curved surfaces of such devices, providing a wide scope of zSense enabled application scenarios. Our evaluations reported over 94.8% gesture recognition accuracy across all configurations.
Donut as I do: Learning from failed demonstrations

The canonical Robot Learning from Demonstration scenario has a robot observing human demonstrations of a task or behavior in a few situations, and then developing a generalized controller. Current work further refines the learned system, often to perform the task better than the human could. However, the underlying assumption is that the demonstrations are successful, and are appropriate to reproduce. We, instead, consider the possibility that the human has failed in their attempt, and their demonstration is an example of what not to do. Thus, instead of maximizing the similarity of generated behaviors to those of the demonstrators, we examine two methods that deliberately avoid repeating the human's mistakes.
Allosteric regulation of deubiquitylase activity through ubiquitination

Ataxin-3, the protein responsible for spinocerebellar ataxia type-3, is a cysteine protease that specifically cleaves poly-ubiquitin chains and participates in the ubiquitin proteasome pathway. The enzymatic activity resides in the N-terminal Josephin domain. An unusual feature of ataxin-3 is its low enzymatic activity especially for mono-ubiquitinated substrates and short ubiquitin chains. However, specific ubiquitination at lysine 117 in the Josephin domain activates ataxin-3 through an unknown mechanism. Here, we investigate the effects of K117 ubiquitination on the structure and enzymatic activity of the protein. We show that covalently linked ubiquitin rests on the Josephin domain, forming a compact globular moiety and occupying a ubiquitin binding site previously thought to be essential for substrate recognition. In doing so, ubiquitination enhances enzymatic activity by locking the enzyme in an activated state. Our results indicate that ubiquitin functions both as a substrate and as an allosteric regulatory factor. We provide a novel example in which a conformational switch controls the activity of an enzyme that mediates deubiquitination.
An Effective and High-quality Query Relaxation Solution on the Deep Web

Because the amount of information contained on the Deep Web is much larger than the surface web, how to use it well has become a popular problem to research. When a query is sent to a deep web resource and the data sources return few results or even no result, a proper query relaxation solution should be adopted to get more satisfactory results to users. In this paper, such a query relaxation solution is presented. First, it solves the problem of relaxing attributes which contain multiple key words by value. That is, such attributes are not simply removed in the relaxation, but the query values of the attributes are modified. Second, when a data source returns many result pages, instead of getting all the pages, it evaluates the quality of the results in the current page to decide whether to send another query to fetch the next page. Thus, the number of query times is reduced. Finally, the experimental results demonstrate that both the result quality and the query efficiency are improved.
Utilizing WordNet and Regular Expressions for Instance-based Schema Matching

Instance-based matching is the process of finding the correspondence of schema elements by comparing the data from different data sources. It is used as an alternative option when the match between schema elements fails. Instance-based matching is applied in many application areas such as website creation and management, schema evolution and migration, data warehousing, database design and data integration. Sometimes the schema information such as (element name, description, data type, etc.) is unavailable or is unable to get the correct match especially when the element name is abbreviation, therefore, if the schema matching failed, the next step is to focus on values stored in the schemas. For these reasons, many recent approaches focus on instance-based matching. In this study, we propose an approach that combines the strength of pattern recognition utilizing regular expressions for numerical domain as well with WordNet for string domain by getting the similarity coefficient in the range of (0,1). In previous approach, the regular expression is achieved with a good accuracy for numerical instances only and is not implemented on string instances because we need to know the meaning of string to decide if there is a match or not. The using of WordNet-based measures for string instances should guarantee to improve the effectiveness in terms of Precision (P), Recall (R) and F-measure (F). This approach is evaluated with real dataset and the results are found better than using just equality measure for string especially if the schemas are disjoint. The approach achieved 95.3% F-measure (F).
Nose biometrics verification using linear object technique

Biometrics technology is evolving. Thus, researches have been done and implemented on many biometrics systems such as hand geometric, palm print, iris, voice gait. All these are sensitive to a number of factors such as background noise, high cost of deployment, inappropriate for large-scale identification, and finally gait-based system by the choice of footwear, nature of clothing, affliction of the legs, walking surface. However, the use of other characteristic feature such as the nose which is not bogged down with the aforementioned factors has been largely unexplored. In this work, geometry is employed for nose identification; the nose alae are measured. The curvature points of the nose alae are selected as the nasal feature using linear object class and triangulation technique. Our experiment was carried out with 100 dataset, the result showed 87% recognition; this shows that nose biometrics, if well explored could be a valuable biometrics traits.
A Glimpse into the Past: The Recent Evolution of Globular Clusters

We present the serendipitous discovery of 195 extragalactic globular clusters (GCs) in one of the deepest optical images ever obtained, a 126 orbit Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) imaging study of the nearby Galactic GC NGC 6397. The distant GCs are all found surrounding a bright elliptical galaxy in the field and are among the faintest objects detected in the image, with magnitudes 26 ≲ F814W ≲ 30. We measure the redshift of the parent elliptical galaxy, using the Gemini Multi-Object Spectrograph (GMOS) on Gemini South, to be z = 0.089 (375 Mpc). This galaxy, and its associated clusters, therefore ranks as one of the most distant such systems discovered to date. The measured light from these clusters was emitted 1.2 Gyr ago (the look-back time) and therefore the optical properties hold clues for understanding the evolution of GCs over the past Gyr. We measure the color function of the bright GCs and find that both a blue and red population exist, and that the colors of each subpopulation are redder than GCs in local elliptical galaxies of comparable luminosity. For the blue clusters, the observed color difference from z = 0.089 to today is only slightly larger than predictions from stellar evolution (e.g., changes in the luminosity and color of the main-sequence turnoff and the morphology of the horizontal branch). A larger color difference is found in the red clusters, possibly suggesting that they are very metal-rich and/or significantly younger than 12 Gyr.
Studies in Computational Statistical Methods with Applications to Pattern Recognition and Data Analysis

Acknowledgements I thank my supervisor, Professor Lasse Holmström, for initially introducing me to the world of nonparametric function estimation and for pointing out fruitful directions during my journey towards this thesis. I am also grateful to Dr. Petri Koistinen for many helpful pieces of advice. The support from the people at the Rolf Nevanlinna Institute is warmly acknowledged. Working with all of you has been a real privilege. I also want to thank the Finnish Graduate School of Stochastics. Especially the yearly Summer School has been an inspiring and refreshing event. I am grateful to all co-authors of the original articles. I thank Professors Esa Nummelin and Antti Penttinen for acting as the pre-printing examiners of this thesis. Last, but not least, I thank my wife Jaana, my daughter Jasinta, and my son Jeter for their love and support. II Lasse Holmström and Fabian Hoti. Reduced kernel regression for fast classification. A note on estimating the posterior density of a quantitative trait locus from a Markov chain Monte Carlo sample. Three family clusters of neuropsychological performance in a sample of multiply affected families with schizophrenia. Submitted for publication.
There and Back Again : Autoencoders for Textual Reconstruction

In this paper, we experiment with the use of autoencoders to learn fixed-vector summaries of sentences in an unsupervised learning task. Sentences as word vectors are fed into an encoder, either a recurrent neural network or convolutional neural network, transformed into a summary vector of fixed size, and then unfolded back into an ordered sentence using a recurrent neural network. This model is analogous to encoder-decoders used in machine translation models, and in fact we posit that the modular space that captures semantic commonalities between two languages in an encoder-decoder can be applied to a single language example by translating a language back to itself. Here, the intermediate vector space is both an encapsulation of a sentence and a seed for reconstructing it, which makes it useful for other natural language processing tasks. The aim of this project is to ultimately create effective semantic representations of variable sized text. We train our model on 10,000 English Wikipedia sentences on an objective function that minimizes the cross-entropy between the input sentence and reconstructed sentence and that minimizes the euclidean distance between the encoding of the reconstruct text and that of the input text, so that insignificant changes or synonyms to output words are not viewed as bad reconstructions. We show that qualitatively there is some success in this model, though it overfits on the trained examples and needs to train on a larger dataset. We show that the autoencoder is able to discern useful English syntax rules that determine the useful features needed for reconstruction.
2 Survey of the field

This project deals with verb-particle constructions (VPCs) in the context of statistical machine translation, with the purpose of finding out if and to what degree they affect translation quality in English and German. Its main goal is to identify which types of VPCs cause translation errors and to find possible solutions to this problem. VPCs are a type of multiword expressions (MWEs), meaning they are lexical items consisting of multiple simplex words that display different kinds of idiosyncrasies [4]. Even though German and English share many common features and both languages exhibit a variety of particle verbs, their behaviour is not always similar. First of all, there are grammatical differences. For example, in English the particle is always separate from the verb root (e.g. eat up), while in German, it can be separated, but does not necessarily have to be (e.g. aufessen: er isst den Kuchen auf ). Secondly, both languages have different VPCs in general. Even though there are cases where VPCs are formed in the same manner (e.g. eat up and aufessen), there are also cases where they are formed with different particles (e.g. step down and zurücktreten), or different verbs (e.g. turn down and ablehnen). While some VPCs translate to other VPCs, there are also particle verbs that translate to simplex verbs or to several alternatives that convey the same meaning, as the following example shows (taken from Bing Translator). Mach die Tür auf! → Open the door! (1)
The dynamical status of the galaxy cluster Abell 115

Aims. We present the results of a new spectroscopic and photometric survey of the hot, binary X‐ray cluster A115 at z = 0.193, containing a radio relic. Methods. Our analysis is based on new spectroscopic data obtained at the Telescopio Nazionale Galileo for 115 galaxies and on new photometric data obtained at the Isaac Newton Telescope in a large field. We combine galaxy velocity and position informa tion to select 85 galaxies recognized as cluster members, determine global dynamical properties and detect substructures. Results. We find that A115 appears as a well isolated peak in the redshif t space, with a global line‐of‐sight (LOS) velocity dispersion �v = 1362 +126 −108 km s −1 . Our analysis confirms the presence of two structures of clus ter‐type well recognizable in the plane of the sky and shows that they differ of∼ 2000 km s −1 in the LOS velocity. The northern, high velocity subcluster (A115N) is likely centred on the second brightest cluster galaxy (BCM‐A, coincident with radio source 3C28) and the northern X‐ray peak. The southern, low velocity subcluster (A115S) is likely centred on the first br ightest cluster galaxy (BCM‐B) and the southern X‐ray peak. We estimate
Reducing P to a Sparse Set using a Constant Number of Queries Collapses P to L

We prove that there is no sparse hard set for P under logspace computable bounded truth-table reductions unless P=L. In case of reductions computable in NC/sup 1/, the collapse goes down to P=NC/sup 1/. We generalize this result by parameterizing the sparseness condition, the space bound and the number of queries of the reduction, apply the proof technique to NL and L, and extend all these theorems to two-sided error randomized reductions in the multiple access model, for which we also obtain new results for NP.
Cooperative particle swarm optimization for TSK-type neural fuzzy systems

This study proposes a cooperative particle swarm optimization (CPSO) to optimize the parameters of the TSK-type neural fuzzy system (TNFS) for classification applications. The proposed CPSO uses cooperative behavior among multiple subswarms to decompose the neural fuzzy systems into rule-based subswarms, and each particle within each subswarm evolves by a specific particle swarm optimization (PSO) separately. Therefore, the CPSO can accelerate the search and increase global search capacity. Finally, the TNFS with CPSO (TNFS-CPSO) is adopted in several classification applications. Experimental results demonstrate that the proposed TNFS-CPSO method has a higher accuracy rate and a faster convergence rate than the other methods.
Patterning and Regulatory Associations of DNA Methylation Are Mirrored by Histone Modifications in Insects

Epigenetic information is an important mediator of the relationship between genotype and phenotype in eukaryotic organisms. One of the most important and widely conserved forms of epigenetic information is the methylation of genes. However, the function of intragenic DNA methylation remains poorly understood. The goal of this study was to gain greater understanding of the nature of intragenic methylation by determining its role in the multilayered epigenetic landscape of insects. We first investigated the evolutionary lability of DNA methylation by examining whether methylation patterns were conserved in the fire ant and honey bee. We found that DNA methylation was targeted to largely overlapping sets of orthologs in both species. Next, we compared intragenic DNA methylation levels in the fire ant and honey bee to comprehensive epigenetic and gene-regulatory data from Drosophila melanogaster orthologs. We observed striking evidence of a conserved association between DNA methylation in fire ants and honey bees, and several active histone modifications, constitutive gene expression, and “broad” promoter architecture in D. melanogaster. Overall, our study illustrates that DNA methylation is a single component of a conserved, integrated, multilayered epigenetic and regulatory landscape in insect genomes.
Capital cities: a taxonomy of capital accounts for knowledge cities

Aims to outline a theoretical and methodological framework for the understanding, design, assessment and benchmarking of knowledge cities (KCs) based on social knowledge capital accounts as common ground for interdisciplinary work between KM and the established field of urban studies and planning. The evolution of urban regions throughout history is analyzed from the perspective of value systems. Under this perspective, the basic configuration of human urban settlements is seen to evolve as the forms of production of social value have done. Alternative concepts of KCs are then discussed, allowing the distinction of three stages of development. Based on this distinction, some critical levels of KC analysis as well as some specific dimensions of urban capital are identified. The requirements for a formal structure of KC capital system are then established as a criterion to identify and value the knowledge accounts of urban regions, specifically in the form of KBD indicators. A taxonomy of capital accounts for KCs – the core part of this work – is introduced and main categories described. Based on these capital accounts, the future of cities is perceived as carrying some critical discontinuities in developmental dynamics. Specifically some breaking points which seem to be implicit and embrionic in any third‐stage KC are discussed. KBD emerges as a disruptive approach that may contribute to overcome the exhaustion of the industrial city and therefore the inertial carry over of its decadence into the future and potentially leapfrog urban regions into the next‐level of communitary value systems.
Scattering of electrons in silicon inversion layers by remote surface roughness

A model to study the effect of the roughness at the poly-Si/SiO2 interface in silicon inversion layers on the electron mobility is obtained. Screening of the resulting perturbation potential by the channel carriers is taken into account, considering Green’s functions for metal–oxide–semiconductor geometry, i.e., taking into account the finite thickness of the gate oxide. Mobility of electrons is evaluated at room temperature by the Monte Carlo method, taking into account the simultaneous contribution of phonon scattering, SiO2/Si interface roughness scattering, Coulomb scattering, and remote surface roughness scattering. The contribution of excited subbands is considered. The resulting remote surface roughness scattering is shown to be strongly dependent on the oxide thickness, and degrades mobility curves at low inversion charge concentrations. The results obtained show that the effect of this scattering mechanism cannot be ignored when the oxide thickness is below 5 nm, (as in actual devices), even when.
Foam Cell Specific LXRα Ligand

Objective The liver X receptor α (LXRα) is a ligand-dependent nuclear receptor and the major regulator of reverse cholesterol transport in macrophages. This makes it an interesting target for mechanistic study and treatment of atherosclerosis. Methods and Results We optimized a promising stilbenoid structure (STX4) in order to reach nanomolar effective concentrations in LXRα reporter-gene assays. STX4 displayed the unique property to activate LXRα effectively but not its subtype LXRβ. The potential of STX4 to increase transcriptional activity as an LXRα ligand was tested with gene expression analyses in THP1-derived human macrophages and oxLDL-loaded human foam cells. Only in foam cells but not in macrophage cells STX4 treatment showed athero-protective effects with similar potency as the synthetic LXR ligand T0901317 (T09). Surprisingly, combinatorial treatment with STX4 and T09 resulted in an additive effect on reporter-gene activation and target gene expression. In physiological tests the cellular content of total and esterified cholesterol was significantly reduced by STX4 without the undesirable increase in triglyceride levels as observed for T09. Conclusions STX4 is a new LXRα-ligand to study transcriptional regulation of anti-atherogenic processes in cell or ex vivo models, and provides a promising lead structure for pharmaceutical development.
Semantically similar visual words discovery to facilitate visual invariance

A major limitation of many image classification and retrieval systems is that they only rely on the visual structure within images. However, images that have a different visual appearance may be semantically related at a higher level conceptualization. This paper presents a framework to deal with this problem by exploiting the well-known bag-of-visual words (BVW) model, to represent visual content. There are two key contributions of this paper. First, a novel approach for visual words construction is presented which takes the spatial information of keypoints into account in order to enhance the quality of visual words generated from extracted keypoints. Second, an approach to discover semantically similar visual word sets is proposed, which enables the BVW model to become invariant to certain changes in visual appearance. Consequently, the BVW model strengthens the discrimination power for visual content classification.
Creativity Development of Students of Pedagogy

The contents of the article is the application of the Harmony Program in Undergraduate Teacher Training. The experiment tested to what extent this program affects creativity of future teachers. On the basis of creativity tests, interpersonal relations scale and questionnaire, positive changes were found in the development of creative skills of the students of the tested group in the area of interpersonal relations, climate, personal profile and attitudes.