Miracle-dz/UniFAR-FTUs huggingface dataset:
Milrinone Attenuates Arteriolar Vasoconstriction and Capillary Perfusion Deficits on Endotoxemic Hamsters

Background and Objective Apart from its inotropic property, milrinone has vasodilator, anti-inflammatory and antithrombotic effects that could assist in the reversal of septic microcirculatory changes. This paper investigates the effects of milrinone on endotoxemia-related microcirculatory changes and compares them to those observed with the use of norepinephrine. Materials and Methods After skinfold chamber implantation procedures and endotoxemia induction by intravenous Escherichia coli lipopolysaccharide administration (2 mg.kg-1), male golden Syrian hamsters were treated with two regimens of intravenous milrinone (0.25 or 0.5 μg.kg-1.min-1). Intravital microscopy of skinfold chamber preparations allowed quantitative analysis of microvascular variables. Macro-hemodynamic, biochemical, and hematological parameters and survival rate were also analyzed. Endotoxemic non-treated animals, endotoxemic animals treated with norepinephrine (0.2 μg.kg-1.min-1), and non-endotoxemic hamsters served as controls. Results Milrinone (0.5 μg.kg-1.min-1) was effective in reducing lipopolysaccharide-induced arteriolar vasoconstriction, capillary perfusion deficits, and inflammatory response, and in increasing survival. Norepinephrine treated animals showed the best mean arterial pressure levels but the worst functional capillary density values among all endotoxemic groups. Conclusion Our data suggests that milrinone yielded protective effects on endotoxemic animals’ microcirculation, showed anti-inflammatory properties, and improved survival. Norepinephrine did not recruit the microcirculation nor demonstrated anti-inflammatory effects.
High Reliable Multi-View Semi-Supervised Learning with Extremely Sparse Labeled Data

Most semi-supervised learning methods assume there are a number of labeled data available in order to learn a classifier which then exploits a large set of unlabeled data. However, for some applications, there are only extremely spare labeled examples attainable (say, one example per category). In this case, these semi-supervised learning methods can not work. In this paper, a new method for seeking more examples with high reliable labels based on the limited labeled data is proposed. By investigating the correlation between different views through canonical correlation analysis, our method can launch semi-supervised learning using only one labeled example from each class. Experiments on text classification show the effectiveness of the proposed method.
Isolation and Characterization of Mycoplasma mycoides Subspecies capri from Milk of Natural Goat Mastitis Cases

Association of Mycoplasma mycoides subspecies capri (Mmc) with natural goat mastitis has been studied earlier largely by detecting the Mmc DNA using molecular methods. However, report on detection of cultivable Mmc isolates from natural goat-mastitis milk is still very rare. In this study, Mmc was isolated from milk samples (n = 171) of goats with or without clinical signs of mastitis. Mmc isolates were further characterized by biochemical and species-specific PCR methods. Intra species strain variation was also studied by 16S amplified rDNA restriction analysis (16S ARDRA). The study recovered a total of 6 Mmc isolates (3.5%). Three types of intraspecies variants among the recovered Mmc isolates were found by 16S ARDRA. The study concluded that Mmc may be an etiological agent of mycoplasmal mastitis in Indian goat herds.
Whose Explanation of Inequality?: Giving Voice to Underrepresented Groups Increases Fit Within Organizations

The underrepresentation of racial minorities is among the greatest challenges facing by organizations today. Here, we investigate the role that an organization’s explanation for this underrepresentation might play in maintaining it. We focus on the distinction between individual-focused and structural-focused explanations of inequality. Individual-focused explanations, such as those that focus on personal preferences, are prevalent in mainstream settings, whereas structural-focused explanations, such as those that focus on a lack of resources and opportunities, are prevalent among underrepresented groups. In two experiments, one in a real-world organizational setting and one in a hypothetical consulting firm, the current research demonstrates that structural-focused explanations of organizations’ inequality produce a greater sense of fit and acceptance among African Americans than do individual-focused explanations. This suggests that how organizations explain inequality plays a role in amplifying or reducing it.
Random walk based entity ranking on graph for multidimensional recommendation

In many applications, flexibility of recommendation, which is the capability of handling multiple dimensions and various recommendation types, is very important. In this paper, we focus on the flexibility of recommendation and propose a graph-based multidimensional recommendation method. We consider the problem as an entity ranking problem on the graph which is constructed using an implicit feedback dataset (e.g. music listening log), and we adapt Personalized PageRank algorithm to rank entities according to a given query that is represented as a set of entities in the graph. Our model has advantages in that not only can it support the flexibility, but also it can take advantage of exploiting indirect relationships in the graph so that it can perform competitively with the other existing recommendation methods without suffering from the sparsity problem.
Utilizing Gravity in Movement-Based Games and Play

This paper seeks to expand the understanding of gravity as a powerful but underexplored design resource for movement-based games and play. We examine how gravity has been utilized and manipulated in digital, physical, and mixed reality games and sports, considering five central and gravity-related facets of user experience: realism, affect, challenge, movement diversity, and sociality. For each facet, we suggest new directions for expanding the field of movement-based games and play, for example through novel combinations of physical and digital elements. Our primary contribution is a structured articulation of a novel point of view for designing games and interactions for the moving body. Additionally, we point out new research directions, and our conceptual framework can be used as a design tool. We demonstrate this in 1) creating and evaluating a novel gravity-based game mechanic, and 2) analyzing an existing movement-based game and suggesting future improvements.
A Cooperative Task Execution Mechanism for Personal Assistant Agents Using Ability Ontology

Personal assistant agents have various abilities to support the user's tasks in the background. They are expected to be run on laptops, portable devices and even on IoT devices. Since their abilities are sometimes restricted by their running environments and hardware, is not always easy for single personal assistance agent to accomplish all the tasks. This paper presents our design and implementation of a cooperative task execution mechanism for cooperative personal assistance agents based on ability ontology.
The Influence of Resource Availability

False memories occur when individuals mistakenly report an event as having taken place when that event did not in fact occur. The DRM (Deese, 1959; Roediger & McDermott, 1995) paradigm provides an effective technique for creating and investigating false memories. In this paradigm participants study a list of words (e.g., SOUR, CANDY,. . .) that are highly associated to a non-presented critical item (e.g., SWEET). The study phase is followed by a test of memory for the study list words. Researchers typically find very high levels of false recall of the critical non-presented item. However, the likelihood of falsely remembering the non-presented critical items can be reduced by presenting studied associates visually rather than auditorally (e.g., Smith & Hunt, 1998). This is referred to as the modality effect in false memory. The current study investigated the role of resource availability in the expression of this modality effect in false recall. In Experiment 1 false recall was reduced in the visual study presentation condition relative to the auditory condition for participants with higher working memory capacity, but not for participants with lower working memory capacity. In Experiment 2 the effect of study modality on false recall was eliminated by the addition of a divided attention task at encoding. Both studies support the proposal that resource availability plays a role in the expression of the modality effect in the DRM paradigm (Smith, Lozito, & Bayen, 2005).
On troubled positions, borders and boundaries among immigrant women in a Swedish context

This contribution discusses representational power and images/concepts Turkish women attending Swedish language courses for immigrants (SFI) experience in accounts about them as migrants in Sweden. Examples from the past but also from the present are used – from a still ongoing debate on troubled positions, borders and boundaries among/about immigrant women. Empirical data (mainly interviews and policy documents) come from revisiting an earlier study from 2002, but also data drawn from later projects and other research. The critical intersectional discussion concerns ethnicity/migration, gender and class and research related to cultural, migration, ethnicity and gender studies. Three themes are discussed; one is about social interaction and the negotiating of ethnicity from an interview, illustrating how the interviewee as well as the interviewer are caught in prevalent discourses and try to handle the straitjacket of labelling. The next theme is about gender, gender equality, “Swedishness” and nation, where SFI can be seen as an arena for educating about gender equality. The last theme focuses on the institutional level, the welfare state and the power of definitions. This section also discusses how the category “immigrant” including “the immigrant woman” are constituted and negotiated in relation to the labour market. Structural conditions as well as agency are not always considered or problematized. The article, a critical reflection on the production of knowledge that researchers as well as various actors are involved in, includes both an ethical and methodological issue, also discussed in the conclusion.
Online Learning Behaviors for Radiology Interns Based on Association Rules and Clustering Technique.

In a hospital, clinical teachers must also care for patients, so there is less time for the teaching of clinical courses, or for discussing clinical cases with interns. However, electronic learning (e-learning) can complement clinical skills education for interns in a blended-learning process. Students discuss and interact with classmates in an e-learning collaborative environment. E-learning can assist clinical training and provides a collaborative environment, but every student has individual learning preferences on the e-learning platform. A typical platform, such as a learning management system (LMS) does not provide individual learning activities for every student. This paper clusters students into two groups: active and inactive groups. In each group, students’ learning behavior patterns, i.e., the association rules for activities, are derived from the transaction data for the LMS. The cluster to which a student belongs defines the online learning behaviors, from the activity association rules. The method then provides individual preferred activities. Teachers instruct students in accordance with their aptitude, as derived from the learning behavior pattern. The cluster analysis shows that students in active group often view teaching videos after completing feedback. Students in the inactive group often view teaching materials after adding posts on a forum.
Claiming too much, delivering too little: testing some of Hofstede’s generalisations

Abstract This paper considers Geert Hofstede’s claim that his national cultural ‘dimension scores’ and related rankings of countries enable effective prediction by examining a causal generalisation he has repeatedly used to illustrate that capability. When tested against cross-sectional and longitudinal empirical data about conflicts in industrial relations, the generalisation is shown not to have predictive power. A second generalisation is then tested, which also fails to demonstrate predictive capability. This paper discusses some characteristics of valid cross-national research in the light of these predictive failures.
Privacy by disaster? Press coverage of privacy and digital technology

Digital technologies challenge the existing expectations of privacy for both individual users and societies at large. Although numerous surveys and experiments have studied how individual users respond to these challenges, we know little about such perceptions and debates in the larger public. This study investigated this question by analysing German media coverage of the issue of privacy during the current age in times of widespread digital technology. We asked which events journalists report when they broach the issue, what aspects of privacy they cover and whether the coverage refers to different kinds of privacy-related events and to different publication contexts. The results showed that it is not necessarily disasters that give coverage a new orientation. Instead, changes come from events that have the potential to enhance privacy in the future. The publication context also influences the presentation of privacy.
Facial expression cloning with fuzzy set clustering

This paper describes work towards a facial expression cloning system that maps pre-existing generic facial expressions from a shape-based face to a muscle-based face. The goal of this work is to create a facial expression cloning algorithm that allows animations to be recorded for one face and transferred to other faces regardless of the underlying model used for the source and target faces. Facial expressions are compared using membership values of fuzzy sets.
Thresholding methods review for microcalcifications segmentation on mammography images in obvious, subtle, and cluster categories

Microcalcifications are the earliest sign of breast carcinoma. Their typical size is about 1 mm, which is why it is difficult to detect for an expert. Therefore, a tool that eases their visualization becomes relevant. Segmentation gives the candidate areas that could contain microcalcifications. A preprocessing step can improve segmentation performance but the algorithm becomes database dependent. This paper compares four commonly used thresholding techniques to segment mammography images having sections divided in three groups: obvious, subtle and clusters; due to their microcalcification contents. The purpose of this paper is to show what technique has a better performance in special relation with mammography images. Best performers are Entropy (68.8%), and Intermodes (50.9%), but further research is needed to improve performance on subtle and cluster microcalcifications considering non-bimodal histograms.
Thoughts on a Protocol Architecture for Vehicular Ad-Hoc Networks

In comparison to other communication networks, Vehicular Ad-hoc Networks (VANETs) have unique requirements with respect to applications, types of communication, self-organization and other issues. In order to meet these requirements, the structuring of functionalities into protocols and their interaction must be re-thought for VANETs. The traditional approach of decomposition of functionality into protocol layers (layered approach) and a protocol design specifically tailored to the needs of VANETs (unlayered approach) lead to two extreme and opposed manifestations of a potential VANET protocol architecture. From these two extreme approaches we derive a stack-based VANET protocol architecture that combines the strengths of both sides. Among the key features of this protocol architecture are VANET-specific protocol layers, a staircase approach for interaction among layers and the use of an information connector for cross-layer information exchange using the publisher/subscriber pattern. We believe that this protocol architecture provides a clear modular structure with flexibility for protocol interaction and information exchange at a reasonable complexity.
Vitamin D Status and Virologic Response to HCV Therapy in the HALT-C and VIRAHEP-C Trials

More than 150 million people worldwide are chronically infected with hepatitis C virus (HCV) and face higher risk of cirrhosis and hepatocellular carcinoma. Highly effective HCV treatments have recently been developed; however, they are costly and therefore poorly suited for application in resource-limited settings where HCV burden is high. Pegylated-interferon alpha (PEG-IFNα) and ribavirin (RBV) therapy is far less costly, but also less effective. Vitamin D supplementation has been proposed as an inexpensive adjuvant to treatment, however, prior epidemiological evidence on its effectiveness is inconsistent, with little data available among African Americans who naturally have lower vitamin D concentrations. We thus evaluated associations between baseline vitamin D status, measured by circulating 25-hydroxyvitamin D (25(OH)D), which is considered to be the best marker of vitamin D status in humans, and subsequent response to PEG-IFNα/RBV therapy in two large clinical trials that together included 1292 patients infected with HCV genotype 1. We used race-stratified logistic regression models to evaluate multivariable-adjusted associations of 25(OH)D with early virologic response (EVR; 2-log10 HCV RNA decline at week 12) and sustained virologic response (SVR). Among African Americans, we saw no associations. Among European Americans, we saw no association with low vitamin D (≤20 ng/mL) versus sufficient concentrations (20-<30 ng/mL). However, patients with 25(OH)D ≥30 ng/mL were actually less likely to attain EVR (OR = 0.64, 95% CI = 0.43–0.94) than those with sufficient concentrations, with a similar but non-significant association observed for SVR (OR = 0.49, 95% CI = 0.20–1.17). Conclusion Higher vitamin D status was not beneficially associated with responses to therapy; if anything, patients with higher vitamin D concentrations were less likely to attain SVR. Our data do not support a role for vitamin D supplementation as an adjuvant therapy for HCV.
Prediction in LMS-type adaptive algorithms for smoothly time varying environments

The aim of this correspondence is to improve the performance of the least mean square (LMS) and normalized-LMS (NLMS) adaptive algorithms in tracking of time-varying models. A new procedure for estimation of weight increments for including in the LMS-type adaptive algorithms is proposed. This procedure applies a simple smoothing on the increment of the estimated weights to estimate the speed of weights. The estimated speeds are then used to predict the weights for the next iteration. The efficiency of the algorithm is confirmed by simulation results. The algorithm has a very low order of arithmetic complexity. Moreover, this procedure could be combined with a wide class of adaptive filters (e.g., RLS, gradient lattice algorithm, etc.) to improve their behaviors. The proposed algorithm is obtained by simplifying a Kalman filter. To this end, a Markov model of second order is considered for the weight vector. This model shows that the estimation of parameter increments inferred from the predicted parameters improves the tracking performance.
Functional Characterization of Fission Yeast Transcription Factors by Overexpression Analysis

In Schizosaccharomyces pombe, over 90% of transcription factor genes are nonessential. Moreover, the majority do not exhibit significant growth defects under optimal conditions when deleted, complicating their functional characterization and target gene identification. Here, we systematically overexpressed 99 transcription factor genes with the nmt1 promoter and found that 64 transcription factor genes exhibited reduced fitness when ectopically expressed. Cell cycle defects were also often observed. We further investigated three uncharacterized transcription factor genes (toe1+–toe3+) that displayed cell elongation when overexpressed. Ectopic expression of toe1+ resulted in a G1 delay while toe2+ and toe3+ overexpression produced an accumulation of septated cells with abnormalities in septum formation and nuclear segregation, respectively. Transcriptome profiling and ChIP-chip analysis of the transcription factor overexpression strains indicated that Toe1 activates target genes of the pyrimidine-salvage pathway, while Toe3 regulates target genes involved in polyamine synthesis. We also found that ectopic expression of the putative target genes SPBC3H7.05c, and dad5+ and SPAC11D3.06 could recapitulate the cell cycle phenotypes of toe2+ and toe3+ overexpression, respectively. Furthermore, single deletions of the putative target genes urg2+ and SPAC1399.04c, and SPBC3H7.05c, SPACUNK4.15, and rds1+, could suppress the phenotypes of toe1+ and toe2+ overexpression, respectively. This study implicates new transcription factors and metabolism genes in cell cycle regulation and demonstrates the potential of systematic overexpression analysis to elucidate the function and target genes of transcription factors in S. pombe.
Scmbug: Policy-based Integration of Software Configuration Management with Bug-tracking

Software configuration management(SCM) and bug-tracking are key components of a successful software engineering project. Existing systems integrating the two have failed to meet the needs of the ASU scalable computing lab, powered by open-source software. An improved solution to the integration problem, designed to accomodate both free and commercial systems alike, is presented. Scmbug offers a policy-based mechanism of capturing and handling integration of SCM events, such as committing software change-sets and labeling software releases, with a bug-tracking system. Synchronous verification checks and the flexibilty to match multiple development models separate this approach from related work. We address design limitations of existing integration efforts, suggest improvements in SCM and bug-tracking systems required to achieve a scalable solution, and document our early integration experiences.
Reference estimation in EEG recordings

This work aims to analyze the reference (montage) problem in electroencephalographic (EEG) recordings. It is well accepted that EEG signals are a mixture of cerebral and extracerebral sources, and the solution to the reference problem depends on the hypothesized mixing model. We focus here on an acquisition model using a distant reference electrode and propose a method for determining and eliminating the reference signal which develops and improves Hu et al. work from [1]. The obtained solution, based on a constrained blind source separation (BSS) algorithm, outperforms the cited method on simulated noisy EEG signals for all noise levels.
Discriminant uncorrelated locality preserving projection

The basis vectors of traditional locality preserving projection (LPP) are statistically correlated. This makes the features extracted are redundant. In addition, LPP is an unsupervised feature extraction method because class information is not used in LPP. In this paper, a discriminant uncorrelated locality preserving projection (DULPP) algorithm is proposed. The DULPP overcomes the shortcomings of traditional LPP. It uses class information of training data when constructing the weighted neighborhood graph. The relationship among data can be described more accurately. Moreover, DULPP can extract features which are statistically uncorrelated. This can make the features extracted not only preserve the local information of original data space but also contain minimum redundancy. The experiment suggests that the proposed algorithm achieves much higher recognition accuracies. The proposed method can be used in video supervision system, target tracking and recognition system to pursue higher recognition accuracies.