Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimensionality and the number of parties in legislative elections

This article explores how the party-defined dimensionality of political competition relates to the number of parties competing in legislative elections. It demonstrates that a mathematical relationship between the number of electoral parties and the literature’s concept of dimensionality follows from the variables’ definitions; conversely, it argues that exploring the relationship between the number of electoral parties and a different concept of dimensionality conveys new information. Hence, it first argues that how we conceptualize dimensionality matters. Redirecting attention to the latter relationship, it then hypothesizes that party system fragmentation will go hand-in-hand with the appearance of new conflicts on the political agenda when the electoral system is permissive. Using a time-series cross-sectional dataset that includes at its core a new measure of dimensionality, it finds reasonable support for the hypotheses; however, at the elite level, new parties are found to play less of a role in politicizing new conflicts than expected.
Global MYCN Transcription Factor Binding Analysis in Neuroblastoma Reveals Association with Distinct E-Box Motifs and Regions of DNA Hypermethylation

Background Neuroblastoma, a cancer derived from precursor cells of the sympathetic nervous system, is a major cause of childhood cancer related deaths. The single most important prognostic indicator of poor clinical outcome in this disease is genomic amplification of MYCN, a member of a family of oncogenic transcription factors. Methodology We applied MYCN chromatin immunoprecipitation to microarrays (ChIP-chip) using MYCN amplified/non-amplified cell lines as well as a conditional knockdown cell line to determine the distribution of MYCN binding sites within all annotated promoter regions. Conclusion Assessment of E-box usage within consistently positive MYCN binding sites revealed a predominance for the CATGTG motif (p<0.0016), with significant enrichment of additional motifs CATTTG, CATCTG, CAACTG in the MYCN amplified state. For cell lines over-expressing MYCN, gene ontology analysis revealed enrichment for the binding of MYCN at promoter regions of numerous molecular functional groups including DNA helicases and mRNA transcriptional regulation. In order to evaluate MYCN binding with respect to other genomic features, we determined the methylation status of all annotated CpG islands and promoter sequences using methylated DNA immunoprecipitation (MeDIP). The integration of MYCN ChIP-chip and MeDIP data revealed a highly significant positive correlation between MYCN binding and DNA hypermethylation. This association was also detected in regions of hemizygous loss, indicating that the observed association occurs on the same homologue. In summary, these findings suggest that MYCN binding occurs more commonly at CATGTG as opposed to the classic CACGTG E-box motif, and that disease associated over expression of MYCN leads to aberrant binding to additional weaker affinity E-box motifs in neuroblastoma. The co-localization of MYCN binding and DNA hypermethylation further supports the dual role of MYCN, namely that of a classical transcription factor affecting the activity of individual genes, and that of a mediator of global chromatin structure.
In Economics and Social Sciences Working Papers Series Robust Virtual Implementation with Incomplete Information: towards a Reinterpretation of the Wilson Doctrine Robust Virtual Implementation with Incomplete Information: towards a Reinterpretation of the Wilson Doctrine

We consider robust virtual implementation, where robustness is the requirement that implementation succeed in all type spaces consistent with a given payoff type space as well as with a given space of first-order beliefs about the other agents' payoff types. This last bit, which constitutes our reinterpreta-tion of the Wilson doctrine, allows us to obtain very permissive results. Our first result is that generically, if there are at least three alternatives, any incentive compatible social choice function is robustly virtually implementable in iteratively undominated strategies. Further, we characterize robust virtual implementation in iteratively undominated strategies by means of incentive compatibility and measurability. Our characterization is independent of the presence of monetary transfers or assumptions alike, made in previous studies. Our work also clarifies the measurability condition in connection to the generic diversity of preferences used in our first result. 1 working papers series " Game Theory has a great advantage in explicitly analyzing the consequences of trading rules that presumably are really common knowledge ; it is deficient to the extent it assumes other features to be common knowledge, such as one player's probability assessment about another's preferences or information. I foresee the progress of game theory as depending on successive reductions in the base of common knowledge required to conduct useful analysis of practical problems. Only by repeated weakening of common knowledge assumptions will the theory approximate reality. " Robert Wilson (1987)
Data aggregation in wireless sensor networks: Compressing or forecasting?

Data aggregation is a key problem in wireless sensor networks due to both energy-constrained and bandwidth-constrained. In this paper, we highlight the aggregation benefits in network layer and MAC layer by modeling the energy consumption for some energy-efficient routing protocols and MAC protocols. Besides, we define two parameters, aggregation ratio w and packet size coefficient λ, to evaluate the efficiency of an aggregation method, and we discuss their trade-off. Additionally, we propose comparison between A-ARMA and compressive sensing, which are on behalf of the state-of-the-art forecasting aggregation and compressing aggregation respectively.
A reference interval study for common biochemical analytes in Eastern Turkey: a comparison of a reference population with laboratory data mining

Introduction The aim of this study was to define the reference intervals (RIs) in a Turkish population living in Northeast Turkey (Erzurum) for 34 analytes using direct and indirect methods. In the present study, the regional RIs obtained were compared with other RI studies, primarily the nationwide study performed in Turkey. Materials and methods For the direct method, 435 blood samples were collected from a healthy group of females (N = 218) and males (N = 217) aged between 18 and 65 years. The sera were analysed in Ataturk University hospital laboratory using Roche reagents and analysers for 34 analytes. The data from 1,366,948 records were used to calculate the indirect RIs using a modified Bhattacharya method. Results Significant gender-related differences were observed for 17 analytes. There were also some apparent differences between RIs derived from indirect and direct methods particularly in some analytes (e.g. gamma-glutamyltransferase, creatine kinase, LDL-cholesterol and iron). The RIs derived with the direct method for some, but not all, of the analytes were generally comparable with the RIs reported in the nationwide study and other previous studies in Turkey.There were large differences between RIs derived by the direct method and the expected values shown in the kit insert (e.g. aspartate aminotransferase, total-cholesterol, HDL-cholesterol, and vitamin B12). Conclusions These data provide region-specific RIs for 34 analytes determined by the direct and indirect methods. The observed differences in RIs between previous studies could be related to nutritional status and environmental factors.
A novel semisupervised transductive SVM with spatial similarity for classification of hyperspectral data

In this paper, a novel semisupervised algorithm is proposed with spatial similarity for classification of hyperspectral data based on the transductive support vector machines algorithm. The proposed method exploits the characteristic of the hyperspectral data, in which spatially nearby points are likely to belong to the same class. To utilize this assumption, a novel transductive support vector machines algorithm is proposed. Experimental tests are performed on two hyperspectral data sets. The results show that the proposed algorithm obtains higher classification accuracies.
World Planning for Robots via Hindsight Optimization

Classical planning makes the closed world assumption in which all relevant aspects of the world are known at planning time. While this assumption holds in some domains, in many practical robotics domains the existence of relevant o bjects or the states of relevant fluents are initially unknown and must be actively discovered. Previous proposals for openworld planning either employ complex and expensive knowledge representations or depend on ad hoc assumptions. In thi s paper, we show how hindsight optimization provides a simple and general approach to planning in open and partially observable worlds. Hindsight optimization samples multiple possible worlds that are consistent with the agent’s cur rent knowledge, generates a plan in each respective world, and then selects the action that maximizes expected reward over these samples. While this approach is approximate, we demonstrate both in simulation and on a physical robot that this simple technique performs well and is more scalable tha n previous methods on standard benchmarks.
Randomized Double-Blind Controlled Trial Comparing the Effectiveness of Lumbar Transforaminal Epidural Injections of Particulate and Nonparticulate Corticosteroids for Lumbosacral Radicular Pain.

OBJECTIVE To compare equivalent doses of a nonparticulate (dexamethasone) with a particulate (betamethasone) corticosteroid in lumbar transforaminal epidural steroid injections (TFESIs) in terms of pain, function, and complications. DESIGN Fifty-six patients presenting with debilitating radicular pain were randomized in a double-blind controlled trial to receive a lumbar transforaminal injection of either dexamethasone 7.5 mg (n = 29) or betamethasone 6.0 mg (n = 27). SETTING A pain clinic and physical medicine and rehabilitation department in two academic hospital centres. OUTCOME MEASURES Data were collected at 1-, 3-, and 6-month follow-ups. The primary outcome was pain reduction on a visual analog scale (VAS) at 3 months. Secondary outcomes were functional improvement, as measured by the Oswestry Disability Index (ODI), and number and type of complications. RESULTS No differences on the VAS, analyzed either as a continuous (P = 0.209) or categorical variable (≥50% (P = 0.058) or ≥75% (P = 0.865) improvement) and ODI (P = 0.181) were found between the two groups at 3 months. At 6 months, improvement of ODI score was at the limit of statistical significance in favor of dexamethasone (P = 0.050). Multivariate regression analysis, adjusting for potential confounding variables, showed that differences on the ODI became statistically significant at the 6 month follow-up, also in favor of dexamethasone (adjusted P = 0.003). No serious complications were observed in either group. CONCLUSION According to this study, pain relief and functional improvement are similar for both dexamethasone and betamethasone at 3 months. Considering its safety profile, dexamethasone could be considered as first choice for TFESI. However, given that the study was underpowered, more research is needed to support a recommendation of systematically using dexamethasone in TFESI.
Self-Interest or Altruism, What Difference?

This paper discusses the difficulties involved in relaxing the self-interest assumption as it is traditionally used in conjunction with the assumption of rationality. A formal model of altruistic behavior is developed and employed in the analysis of the problems of burden-sharing among rational allies. It is demonstrated that altruistic behavior among political actors is not, in general, sufficient to remove all areas of contention between the actors although the scope of disagreement is shown to be narrowed by altruistic behavior. Additional applications of the model of non-self-interested behavior are presented and suggested.
ArsMeteo: artworks and tags floating over the planet art

In this paper we present ArsMeteo, a Web 2.0 portal for collecting and sharing digital (or digitalized) artworks, like videos, pictures, poems and music. The ArsMeteo contents are enriched with a variety of meanings by the tagging activity of all users of the community, both authors and visitors. In this setting, innovative artistic approaches to tagging and tag-based browsing has been thoughtin order to create a dynamic and fertile background for artistic experimentation and cooperative artistic creation.
SSD in-storage computing for list intersection

Recently, there has been a renewed interest of in-storage computing in the context of solid state drives (SSDs), called "Smart SSDs. " Smart SSDs allow application-specific code to execute inside SSDs. This allows applications to take advantage of the high internal bandwidth that Smart SSDs provide. This work studies the offloading of list intersection into Smart SSDs, because intersection is prominent in both search engines and analytics queries. Furthermore, intersection is interesting because the algorithms are more complex than plain scans; they are affected by multiple parameters, as we show, and provide lessons that can be used in other operations also. We are interested to know whether Smart SSDs can accelerate the processing of list intersection and reduce the consumed energy. Intuitively, the answer is yes. However, the performance tradeoffs on real devices are complex. We implement list intersection into a real Samsung Smart SSD research prototype. We also provide an analytical model to understand the key factors to the overall performance, and when list intersection can benefit from Smart SSDs. Finally, we conduct experiments on the Samsung Smart SSD. Based on the results (both analytical and experimental), we provide many suggestions for both SSD vendors on how to manufacture powerful Smart SSDs and for applications on how to make full use of the functionalities that Smart SSDs provide.
Interventions to Reduce Adult Nursing Turnover: A Systematic Review of Systematic Reviews

Background: Nurse turnover is an issue of concern in health care systems internationally. Understanding which interventions are effective to reduce turnover rates is important to managers and health care organisations. Despite a plethora of reviews of such interventions, strength of evidence is hard to determine. Objective: We aimed to review literature on interventions to reduce turnover in nurses working in the adult health care services in developed economies. Method: We conducted an overview (systematic review of systematic reviews) using the Cochrane Database of Systematic Reviews, MEDLINE, EMBASE, Applied Social Sciences Index and Abstracts, CINAHL plus and SCOPUS and forward searching. We included reviews published between 1990 and January 2015 in English. We carried out parallel blinded selection, extraction of data and assessment of bias, using the Assessment of Multiple Systematic Reviews. We carried out a narrative synthesis. Results: Despite the large body of published reviews, only seven reviews met the inclusion criteria. These provide moderate quality review evidence, albeit from poorly controlled primary studies. They provide evidence of effect of a small number of interventions which decrease turnover or increase retention of nurses, these being preceptorship of new graduates and leadership for group cohesion. Conclusion: We highlight that a large body of reviews does not equate with a large body of high quality evidence. Agreement as to the measures and terminology to be used together with well-designed, funded primary research to provide robust evidence for nurse and human resource managers to base their nurse retention strategies on is urgently required.
Bayesian Phylogenetics and the Evolution of Gall Wasps

The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.
Readability Indices for Automatic Evaluation of Text Simplification Systems: A Feasibility Study for Spanish

This paper addresses the problem of automatic evaluation of text simplification systems for Spanish. We test whether already-existing readability formulae would be suitable for this task. We adapt three existing readability indices (two measuring lexical complexity and one measuring syntactic complexity) to be computed automatically, which are then applied to a corpus of original news texts and their manual simplifications aimed at people with cognitive disabilities. We show that there is a significant correlation between each of the three readability indices and several linguistically motivated features which might be seen as reading obstacles for various target populations. Furthermore, we show that there is a significant correlation between the two readability indices which measure lexical complexity.
The transformational leader: who is (s)he? A feminist perspective

As women increasingly enter leadership roles that traditionally have been occupied by men, and with the increasing diffusion of transformational leadership theory, there is growing interest in the relationship between gender and transformational leadership. A wide array of feminist theories that have emerged in the last decades offer conceptual lenses, which can enrich an understanding of the role of gender in the organizational context and the study of leadership. This paper explores how various approaches in feminist thought intersect with the study of gender and transformational/charismatic leadership. I reviewed earlier studies with reference to the different feminist approaches, demonstrating how each reveals a different facet in the understanding of gender and transformational leadership. Finally, I point to the perspectives that have been neglected in this stream of research and offer directions for future research.
Performance with MIMO for the Downlink 3GPP LTE Cellular Systems

High spectrum efficiency is one of the goals for 3GPP Long-term Evolution (LTE) cellular networks. This paper provides evaluation of the downlink (DL) transmission in LTE. The evaluation is performed for a regular hexagonal multi-cell deployment, universal frequency reuse scheme2x2 Multiple Input Multiple Output (MIMO) antenna configuration and varying packet scheduling algorithm. This study evaluates the advantages and benefits of combining several spectrum efficiency improvement techniques over multipath selective fading channel conditions and various bandwidth sizes (BW). The proposed paper compares MIMO improvements to Single Input Single Output (SISO) scenario in terms of cell and user throughputs. The evaluation is performed through a custom simulation package developed for this purpose.
The SIDER database of drugs and side effects

Unwanted side effects of drugs are a burden on patients and a severe impediment in the development of new drugs. At the same time, adverse drug reactions (ADRs) recorded during clinical trials are an important source of human phenotypic data. It is therefore essential to combine data on drugs, targets and side effects into a more complete picture of the therapeutic mechanism of actions of drugs and the ways in which they cause adverse reactions. To this end, we have created the SIDER (‘Side Effect Resource’, http://sideeffects.embl.de) database of drugs and ADRs. The current release, SIDER 4, contains data on 1430 drugs, 5880 ADRs and 140 064 drug–ADR pairs, which is an increase of 40% compared to the previous version. For more fine-grained analyses, we extracted the frequency with which side effects occur from the package inserts. This information is available for 39% of drug–ADR pairs, 19% of which can be compared to the frequency under placebo treatment. SIDER furthermore contains a data set of drug indications, extracted from the package inserts using Natural Language Processing. These drug indications are used to reduce the rate of false positives by identifying medical terms that do not correspond to ADRs.
Immunohistochemical Patterns in the Interfollicular Caucasian Scalps: Influences of Age, Gender, and Alopecia

Skin ageing and gender influences on the scalp have been seldom studied. We revisited the changes in the interfollicular scalp. The study was performed on a population of 650 volunteers (300 women and 350 men) for over 7 years. Three age groups were selected in both genders, namely, subjects aged 20–35, 50–60, and 60–70 years. The hair status was further considered according to nonalopecic and alopecic patterns and severity (discrete, moderate, and severe). Biopsies from the parietal area were processed for immunohistochemistry. Stromal cells were distinguished according to the presence of vimentin, Factor XIIIa, CD117, and versican. Blood and lymphatic vessels were highlighted by Ulex europaeus agglutinin-1 and human podoplanin immunoreactivities, respectively. Actinic elastosis was identified by the lysozyme coating of elastic fibres. The epidermis was explored using the CD44 variant 3 and Ki67 immunolabellings. Biplot analyses were performed. Immunohistochemistry revealed a prominent gender effect in young adults. Both Factor XIIIa+ dermal dendrocytes and the microvasculature size decreased with scalp ageing. Alopecia changes mimicked stress-induced premature senescence.