Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation of dopamine transporter function by α‐synuclein is altered by impairment of cell adhesion and by induction of oxidative stress

Human α‐synuclein accumulates in dopaminergic neurons as intraneuronal inclusions, Lewy bodies, which are characteristic of idiopathic Parkinson's disease (PD). Here, we suggest that modulation of the functional activity of the dopamine transporter (DAT) by α‐synuclein may be a key factor in the preferential degeneration of mesencephalic dopamine (DA)‐synthesizing neurons in PD. In cotransfected Ltk‐, HEK 293, and SK‐N‐MC cells, α‐synuclein induced a 35% decrease in [3H]DA uptake. Biotinylated DAT levels were decreased by 40% in cotransfected cells relative to cells expressing only DAT. DAT was colocalized with α‐synuclein in mesencephalic neurons and cotransfected Ltk‐ cells. Coimmunoprecipitation studies showed the existence of a complex between α‐synuclein and DAT, in specific rat brain regions and cotransfected cells, through specific amino acid motifs of both proteins. The attenuation of DAT function by α‐synuclein was cytoprotective, because DA‐mediated oxidative stress and cell death were reduced in cotransfected cells. The neurotoxin MPP+ (1‐methyl‐4‐phenylpyridinium), oxidative stress, or impairment of cell adhesion ablated the α‐synuclein‐mediated inhibition of DAT activity, which caused increased uptake of DA and increased biotinylated DAT levels, in both mesencephalic neurons and cotransfected cells. These studies suggest a novel normative role for α‐synuclein in regulating DA synaptic availability and homeostasis, which is relevant to the pathophysiology of PD.
Creating an Ontology for the User Profile: Method and Applications

User profiling is commonly employed nowadays to enhance usability as well as to support personalization, adaptivity and other user-centric features. Insofar, application designers model user profiles mainly in an ad-hoc manner, hindering thus application interoperability at the user profile level, increasing the amount of work to be done and the possibility of errors or omissions in the profile model. This work aims at creating a user profile ontology that incorporates concepts and properties used to model the user profile. Existing literature, applications and ontologies related to the domain of user context and profiling have been taken into account in order to create a general, comprehensive and extensible user model. This ontology can be used as a reference model, in order to alleviate the aforementioned issues. The model, available for download, is exemplified through its application in two different areas, personal information management and adaptive visualization.
Efficient suffix trees on secondary storage

We present a new representation for suffix trees, a data structure used in full text searching, that uses little more storage than the log n bits per index point required to store the list of index points. We also show algorithms for maintaining the structure on secondary storage in such a way that we minimize the number of disk accesses while searching and we can efficiently handle changes to the text. Using this new representation, suffix trees are competitive in terms of space with, and actually offer significantly better performance than, existing methods for full text searching. While we present new algorithms and data structures in this paper, the emphasis is on practical searching methods that have been empirically verified against real data.
A Frame-based Characterisation of the Paraconsistent Well-founded Semantics with Explicit Negation

In this work, we present Paraconsistent Well-Founded Semantics with eXplicit negation (WFSXp) by introducing a frame-based semantics. As far as we know, this is the first time that a declarative approach for WFSXp is effectively characterised in terms of a model theory. Dismissing usual techniques based on immediate consequence operators, our definition depicts WFSXp by minimising models satisfying particular criteria. Aware that WFSXp captures a large deal of logic programming semantics (including the main well-founded ones), our approach subsumes indirectly a semantics for them. Then assuming an illustrative tone, by adding some conditions, we also show how it can be adjusted to define Well-Founded Semantics with eXplicit negation (WFSX ), WellFounded Semantics (WFS) as well as Answer Sets. Given its declarative aspects, our work paves the way to define a logical representation of the family of well-founded semantics.
Semaphorin3a Promotes Advanced Diabetic Nephropathy

The onset of diabetic nephropathy (DN) is highlighted by glomerular filtration barrier abnormalities. Identifying pathogenic factors and targetable pathways driving DN is crucial to developing novel therapies and improving the disease outcome. Semaphorin3a (sema3a) is a guidance protein secreted by podocytes. Excess sema3a disrupts the glomerular filtration barrier. Here, using immunohistochemistry, we show increased podocyte SEMA3A in renal biopsies from patients with advanced DN. Using inducible, podocyte-specific Sema3a gain-of-function (Sema3a+) mice made diabetic with streptozotocin, we demonstrate that sema3a is pathogenic in DN. Diabetic Sema3a+ mice develop massive proteinuria, renal insufficiency, and extensive nodular glomerulosclerosis, mimicking advanced DN in humans. In diabetic mice, Sema3a+ exacerbates laminin and collagen IV accumulation in Kimmelstiel-Wilson-like glomerular nodules and causes diffuse podocyte foot process effacement and F-actin collapse via nephrin, αvβ3 integrin, and MICAL1 interactions with plexinA1. MICAL1 knockdown and sema3a inhibition render podocytes not susceptible to sema3a-induced shape changes, indicating that MICAL1 mediates sema3a-induced podocyte F-actin collapse. Moreover, sema3a binding inhibition or podocyte-specific plexinA1 deletion markedly ameliorates albuminuria and abrogates renal insufficiency and the diabetic nodular glomerulosclerosis phenotype of diabetic Sema3a+ mice. Collectively, these findings indicate that excess sema3a promotes severe diabetic nephropathy and identifies novel potential therapeutic targets for DN.
Individual ethics and knowledge management: Arising conflicts

Knowledge management engages a strong personal dimension that enables a possible success or not regarding an organizational knowledge management project. Plus, it engages unforeseen ethical and moral dilemmas at an individual level. Therefore, the aim of this paper is to link philosophical systems and the knowledge management process allowing a comparison between Eastern and Western, regarding the ethical and moral dilemmas that arise at an individual level concerning knowledge workers. Moreover, we will demonstrate that such challenges are similar, and that Floridi’s information theory may provide important answers to that personal dimension of knowledge management.
Augmented particle filtering for efficient visual tracking

Visual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conventional particle filter uses system transition as the proposal distribution, frequently resulting in poor priors for the filtering step. The main reason is that it is difficult, if not impossible, to accurately model the target's motion. Such a proposal distribution does not take into account the current observations. It is not a trivial task to devise a satisfactory proposal distribution for the particle filter. In this paper we advance a general augmented particle filtering framework for designing the optimal proposal distribution. The essential idea is to augment a second filter's estimate into the proposal distribution design. We then show that several existing improved particle filters can be rationalised within this general framework. Based on this framework we further propose variant algorithms for robust and efficient visual tracking. Experiments indicate that the augmented particle filters are more efficient and robust than the conventional particle filter.
Health reform in post conflict Kosovo

The international community undertakes complex interventions in states emerging from war. These interventions include broad efforts to reform the political and institutional structures of the state. After the United Nations took political control of Kosovo in June 1999, it embarked on such a reform program, extremely ambitious in nature. This thesis examines the efforts to rehabilitate and reform the health sector. The immediate post-conflict environment in Kosovo was extremely chaotic. Hundreds of millions of dollars poured into the province, funding the operations of several hundred non-governmental organisations. The initial efforts of the international community in the health sector were focused on coordinating resources and the activities of these organisations. However, Kosovo' s health system was in clear need of widespread reform. The system had been devastated by years of neglect and months of conflict. A reform program was undertaken, with the objectives of establishing a primary care based system, increasing the quality of secondary and tertiary care, modernizing the public health system, and ensuring a cost-effective, equitable health system. By 2004, the reform program had largely failed to meet these objectives. This study examines the reasons that health reform was so difficult utilizing a combination of methods, i.e. a review of literature on peacebuilding, health and conflict, and health reform; analysis of the implementation of reform utilizing primary evidence such as policy documents and health data; and interviews with key stakeholders. Results show two important lessons for other post-conflict interventions. First, the reform program neglected building the capacity of government institutions. If the state does not have the capacity to implement reforms, the sustainability of the health reform process will be undermined. And second, the Kosovo reform program failed to build the foundation for reform before initiating ambitious projects to modernize the health sector.
Preparation and Characterization of Self-Microemulsifying Drug Delivery System of Olmesartan Medoxomil for Bioavailability Improvement

Olmesartan medoxomil (OLM) is an angiotensin II receptor blocker (ARB) antihypertensive agent administered orally that has absolute bioavailability of only 26% due to the poor aqueous solubility (7.75 μg/ml). The aim of the present investigation was to develop a self-microemulsifying drug delivery system (SMEDDS) to enhance the oral absorption of OLM. The solubility of OLM in various oils, surfactants, and cosurfactants was determined. Pseudoternary phase diagrams were constructed using Acrysol EL 135, Tween 80, Transcutol P, and distilled water to identify the efficient self-microemulsification region. Prepared SMEDDS was further evaluated for its emulsification time, drug content, optical clarity, droplet size, zeta potential, in vitro dissolution, and in vitro and ex vivo drug diffusion study. The optimized formulation S2 contained OLM (20 mg), Tween 80 (33%v/v), Transcutol P (33%v/v), and Acrysol EL 135 (34%v/v) had shown the smallest particle size, maximum solubility, less emulsification time, good optical clarity, and in vitro release. The in vitro and ex vivo diffusion rate of the drug from the SMEDDS was significantly higher than that of the plain drug suspension. It was concluded that SMEDDS would be a promising drug delivery system for poorly water-soluble drugs by the oral route.
Structural Alterations of the Social Brain: A Comparison between Schizophrenia and Autism

Autism spectrum disorder and schizophrenia share a substantial number of etiologic and phenotypic characteristics. Still, no direct comparison of both disorders has been performed to identify differences and commonalities in brain structure. In this voxel based morphometry study, 34 patients with autism spectrum disorder, 21 patients with schizophrenia and 26 typically developed control subjects were included to identify global and regional brain volume alterations. No global gray matter or white matter differences were found between groups. In regional data, patients with autism spectrum disorder compared to typically developed control subjects showed smaller gray matter volume in the amygdala, insula, and anterior medial prefrontal cortex. Compared to patients with schizophrenia, patients with autism spectrum disorder displayed smaller gray matter volume in the left insula. Disorder specific positive correlations were found between mentalizing ability and left amygdala volume in autism spectrum disorder, and hallucinatory behavior and insula volume in schizophrenia. Results suggest the involvement of social brain areas in both disorders. Further studies are needed to replicate these findings and to quantify the amount of distinct and overlapping neural correlates in autism spectrum disorder and schizophrenia.
Graph-based skin lesion segmentation of multispectral dermoscopic images

Accurate skin lesion segmentation is critical for automated early skin cancer detection and diagnosis. We present a novel method to detect skin lesion borders in multispectral dermoscopy images. First, hairs are detected on infrared images and removed by inpainting visible spectrum images. Second, skin lesion is pre-segmented using a clustering of a superpixel partition. Finally, the pre-segmentation is globally regularized at the superpixel level and locally regularized in a narrow band at the pixel level.
Ontology Extraction from Existing Educational Content to Improve Personalized e-Learning Experiences

Nowadays, the use of domain ontologies in e-Learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical material and content personalization. However, the ontology building processes is still extremely difficult to achieve. In this paper we present a semi-automatic process based on knowledge extraction from existing SCORM educational content aimed to speed up and facilitate the realization of domain ontologies and the breakdown of SCORM packages in fine-grained, rearrangeable learning objects appropriate for building personalized e-Learning experience.
Development data constraints and the human development index

agency engaging in multi-disciplinary research on the social dimensions of contemporary problems affecting development. Its work is guided by the conviction that, for effective development policies to be formulated, an understanding of the social and political context is crucial. The Institute attempts to provide governments, development agencies, grassroots organizations and scholars with a better understanding of how development policies and processes of economic, social and environmental change affect different social groups. Working through an extensive network of national research centres, UNRISD aims to promote original research and strengthen research capacity in developing countries.
Short-Term Effects of Graphical versus Textual Visualisation of Variables on Program Perception

The empirical evaluation of program visualisation has been based mostly on observations of long-term effects of the program visualisation tools, while possible short-term effects of the visualisations and their relation to the long-term effects have been elided. In order to study short-term effects of visual- isation of variables in a context where the long-term effects are already known, we conducted a controlled experiment, in which we investigated how a person targets her visual attention and what kind of a mental model she constructs, when variables are presented either textually or graphically. The results indicate clear differences in the targeting of visual attention between the visualisation tools: With the graphical tool, the participants targeted their visual attention to vari- ables much more than with the textual tool. With the graphical tool, the increase of visual attention to variables increased the proportion of high-level information in program summaries and decreased the proportion of low-level code-related information.
San Francisco Crime Classification 2015 Fall

We aim to classify the type of crimes committed within San Francisco, given the time and location of a criminal occurrence. This study is important and beneficial. Using data mining approaches, we can predict the location, type and time of criminal occurrences in the city. We also explore some interesting questions, for example, if more crimes occur on certain days of the week or certain times of the day.
Decentralized Detection of Group Formations from Wearable Acceleration Sensors

We propose an approach for detecting collectivebehavior patterns using body-worn sensors in a decentralized,online manner. To reduce complexity, we introduce a set ofcollective behavior primitives as building blocks, adequate fordetection by sensing and communications means. With this, wepresent a generic distributed signal processing procedure suitablefor a decentralized detection of these behavior blocks. In anexperiment, we verify relevant elements of this procedure byevaluating towards which extend body-worn acceleration sensorscan be used to infer whether a set of people is walking togetheras a coherent group. Early results discussed demonstrate thefeasibility of our approach, leading to an outline of next stepsfor reliable detection of collective behavior patterns in real-life.
Fishing new proteins in the twilight zone of genomes: The test case of outer membrane proteins in Escherichia coli K12, Escherichia coli O157:H7, and other Gram‐negative bacteria

We address the problem of clustering the whole protein content of genomes into three different categories—globular, all‐α, and all‐β membrane proteins—with the aim of fishing new membrane proteins in the pool of nonannotated proteins (twilight zone). The focus is then mainly on outer membrane proteins. This is performed by using an integrated suite of programs (Hunter) specifically developed for predicting the occurrence of signal peptides in proteins of Gram‐negative bacteria and the topography of all‐α and all‐β membrane proteins. Hunter is tested on the well and partially annotated proteins (2160 and 760, respectively) of Escherichia coli K 12 scoring as high as 95.6% in the correct assignment of each chain to the category. Of the remaining 1253 nonannotated sequences, 1099 are predicted globular, 136 are all‐α, and 18 are all‐β membrane proteins. In Escherichia coli 0157:H7 we filtered 1901 nonannotated proteins. Our analysis classifies 1564 globular chains, 327 inner membrane proteins, and 10 outer membrane proteins. With Hunter, new membrane proteins are added to the list of putative membrane proteins of Gram‐negative bacteria. The content of outer membrane proteins per genome (nine are analyzed) ranges from 1.5% to 2.4%, and it is one order of magnitude lower than that of inner membrane proteins. The finding is particularly relevant when it is considered that this is the first large‐scale analysis based on validated tools that can predict the content of outer membrane proteins in a genome and can allow cross‐comparison of the same protein type between different species.
A Geometric Approach to Low-Rank Matrix Completion

The low-rank matrix completion problem can be succinctly stated as follows: given a subset of the entries of a matrix, find a low-rank matrix consistent with the observations. While several low-complexity algorithms for matrix completion have been proposed so far, it remains an open problem to devise -type search procedures with provable performance guarantees. The standard approach to the problem, which involves the minimization of an objective function defined using the Frobenius metric, has inherent difficulties: the objective function is not continuous and the solution set is not closed. To address this problem, we consider an optimization procedure that searches for a column (or row) space that is geometrically consistent with the partial observations. The geometric objective function is continuous everywhere and the solution set is the closure of the solution set of the Frobenius metric. We also preclude the existence of local minimizers, and hence establish strong performance guarantees, for special completion scenarios, which do not require matrix incoherence and hold with probability one for arbitrary matrix size.
Genome scale transcriptional response diversity among ten ecotypes of Arabidopsis thaliana during heat stress

In the scenario of global warming and climate change, heat stress is a serious threat to crop production worldwide. Being sessile, plants cannot escape from heat. Plants have developed various adaptive mechanisms to survive heat stress. Several studies have focused on diversity of heat tolerance levels in divergent Arabidopsis thaliana (A. thaliana) ecotypes, but comprehensive genome scale understanding of heat stress response in plants is still lacking. Here we report the genome scale transcript responses to heat stress of 10 A. thaliana ecotypes (Col, Ler, C24, Cvi, Kas1, An1, Sha, Kyo2, Eri, and Kond) originated from different geographical locations. During the experiment, A. thaliana plants were subjected to heat stress (38°C) and transcript responses were monitored using Arabidopsis NimbleGen ATH6 microarrays. The responses of A. thaliana ecotypes exhibited considerable variation in the transcript abundance levels. In total, 3644 transcripts were significantly heat regulated (p < 0.01) in the 10 ecotypes, including 244 transcription factors and 203 transposable elements. By employing a systems genetics approach- Network Component Analysis (NCA), we have constructed an in silico transcript regulatory network model for 35 heat responsive transcription factors during cellular responses to heat stress in A. thaliana. The computed activities of the 35 transcription factors showed ecotype specific responses to the heat treatment.
Development and Validation of the Japanese version of the Savoring Beliefs Inventory (SBI-J)

Savoring is defined as people’s capacity to attend to positive experiences and to regulate positive feelings in response to positive events. The purpose of this study was to develop a Japanese adaptation of the Savoring Beliefs Inventory (SBI-J). The SBI is a self-report measure designed to assess individuals’ beliefs about their ability to savor positive experience within three temporal orientations involving future-focused anticipation of upcoming positive events, present-focused savoring of ongoing positive moments, and past-focused reminiscence about positive memories. After back-translating the SBI, we used an Internet survey to administer the instrument, along with a set of validational criterion measures, to a sample of 520 Japanese adults. Supporting hypotheses and replicating results with Western samples, confirmatory factor analyses revealed that responses to the SBI-J were best conceptualized in terms of five factors reflecting the three, intercorrelated temporal orientations (anticipating, savoring the moment, and reminiscing), as well as two “method” factors involving positive and negative item-valence. Strong, significant correlations among the three temporal SBI-J subscales also support the use of a total score that provides an overall summary of global savoring ability. Each of the three temporal subscales and total score showed acceptable internal consistency reliability and strong one-month test-retest reliability. Correlations of the SBI-J subscales and total score with criterion measures, and gender differences in mean SBI-J scores, support the convergent and discriminant validity of the instrument. These results indicate that the SBI-J is a valid and reliable tool for assessing savoring ability among Japanese adults.