Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Stack Single-Radio Communication Architecture for UAV Acting As a Mobile Node to Collect Data in WSNs

The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzing these works, it is apparent that mobile nodes used in such scenarios are typically equipped with at least two different radio interfaces. The present work presents a Dual-Stack Single-Radio Communication Architecture (DSSRCA), which allows a UAV to communicate in a bidirectional manner with a WSN and a Sink node. The proposed architecture was specifically designed to support different network QoS requirements, such as best-effort and more reliable communications, attending both UAV-to-WSN and UAV-to-Sink communications needs. DSSRCA was implemented and tested on a real UAV, as detailed in this paper. This paper also includes a simulation analysis that addresses bandwidth consumption in an environmental monitoring application scenario. It includes an analysis of the data gathering rate that can be achieved considering different UAV flight speeds. Obtained results show the viability of using a single radio transmitter for collecting data from the WSN and forwarding such data to the Sink node.
STFMap: query- and feature-driven visualization of large time series data sets

Since many applications rely on time-based data, visualizing temporal data and helping experts explore large time series data sets are critical in many application domains. In this interactive system preview, we argue that time series often carry structural features that can, if efficiently identified and effectively visualized, help reduce visual overload and help the user quickly focus on the relevant portions of the data sets. Relying on this observation, we introduce a novel STFMap system, which includes four innovative query- and feature-driven time series data set visualization techniques: (a) segment-maps, (b) warp-maps, (c) stretch-maps, and (d) feature-maps. These rely on the salient temporal features of the time series and their alignments with respect to the given user query to help users explore the data set in a query-driven fashion.
Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

Global scientific collaborations, such as ATLAS, continue to push the network requirements envelope. Data movement in this collaboration is routinely including the regular exchange of petabytes of datasets between the collection and analysis facilities in the coming years. These requirements place a high emphasis on networks functioning at peak efficiency and availability; the lack thereof could mean critical delays in the overall scientific progress of distributed data-intensive experiments like ATLAS. Network operations staff routinely must deal with problems deep in the infrastructure; this may be as benign as replacing a failing piece of equipment, or as complex as dealing with a multi-domain path that is experiencing data loss. In either case, it is crucial that effective monitoring and performance analysis tools are available to ease the burden of management. We will report on our experiences deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. The US ATLAS collaboration has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.
Gene expression signature with independent prognostic significance in epithelial ovarian cancer.

PURPOSE Currently available clinical and molecular prognostic factors provide an imperfect assessment of prognosis for patients with epithelial ovarian cancer (EOC). In this study, we investigated whether tumor transcription profiling could be used as a prognostic tool in this disease. METHODS Tumor tissue from 68 patients was profiled with oligonucleotide microarrays. Samples were randomly split into training and validation sets. A three-step training procedure was used to discover a statistically significant Kaplan-Meier split in the training set. The resultant prognostic signature was then tested on an independent validation set for confirmation. RESULTS In the training set, a 115-gene signature referred to as the Ovarian Cancer Prognostic Profile (OCPP) was identified. When applied to the validation set, the OCPP distinguished between patients with unfavorable and favorable overall survival (median, 30 months v not yet reached, respectively; log-rank P = .004). The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. The hazard ratio for death in the unfavorable OCPP group was 4.8 (P = .021 by Cox proportional hazards analysis). CONCLUSION The OCPP is an independent prognostic determinant of outcome in EOC. The use of gene profiling may ultimately permit identification of EOC patients appropriate for investigational treatment approaches, based on a low likelihood of achieving prolonged survival with standard first-line platinum-based therapy.
Deterministic extractors for bit-fixing sources by obtaining an independent seed

An {n, k)-bit-fixing source is a distribution X over {0, 1}/sup n/ such that there is a subset of k variables in X/sub 1/, . , X/sub n/ which are uniformly distributed and independent of each other, and the remaining n - k variables are fixed. A deterministic bit-fixing source extractor is a function E : {0, l}/sup n/ /spl rarr/ {0, l}/sup m/ which on an arbitrary (n, k)-bit-fixing source outputs m bits that are statistically-close to uniform. Recently, Kamp and Zuckerman (2003) gave a construction of deterministic bit-fixing source extractor that extracts /spl Omega/(k/sup 2//n) bits, and requires k > /spl radic/n. In this paper we give constructions of deterministic bit-fixing source extractors that extract (1 -o(1))k bits whenever k > (log n)/sup c/ for some universal constant c > 0. Thus, our constructions extract almost all the randomness from bit-fixing sources and work even when k is small. For k /spl Gt/ /spl radic/n the extracted bits have statistical distance 2/sup -n/spl Omega/(1)/ from uniform, and for k /spl les/ /spl radic/n the extracted bits have statistical distance k/sup -/spl Omega/(1)/ from uniform. Our technique gives a general method to transform deterministic bit-fixing source extractors that extract few bits into extractors which extract almost all the bits.
Who was white? The disappearance of non-European white identities and the formation of European racial whiteness

Abstract This article provides a critical history of the conflation of European and white identities. It commences with an overview of pre-modern white identities in China and the Middle East. The production of a racialized European white identity is then examined. The obsessional, exclusionary character of European racial whiteness is related to the gradual marginalization of non-European white identities. Drawing primarily on late nineteenth-century and early twentieth-century commentaries, it is also argued that the excessive idealization of whiteness characteristic of its modern European form engenders an unstable and contradictory identity: in societies structured upon class, ethnic and gender hierarchies the‘burden of whiteness’ cannot be equally apportioned. The article concludes with some observations on the challenge historical geographical studies of white identities present to contemporary anti-racists.
Removing Mixture Noise from Medical Images Using Block Matching Filtering and Low-Rank Matrix Completion

In this paper, an efficient medical image denoising method based on low-rank matrix completion and block matching filtering is proposed. The effectiveness of the algorithm in removing the mixed noise is demonstrated through the results. The results also proved the effectiveness of this algorithm in removing noise from regular structures. This method results in comparable performance with significantly lower computation complexity.
RandomBoost: Simplified Multiclass Boosting Through Randomization

We propose a novel boosting approach to multiclass classification problems, in which multiple classes are distinguished by a set of random projection matrices in essence. The approach uses random projections to alleviate the proliferation of binary classifiers typically required to perform multiclass classification. The result is a multiclass classifier with a single vector-valued parameter, irrespective of the number of classes involved. Two variants of this approach are proposed. The first method randomly projects the original data into new spaces, while the second method randomly projects the outputs of learned weak classifiers. These methods are not only conceptually simple but also effective and easy to implement. A series of experiments on synthetic, machine learning, and visual recognition data sets demonstrate that our proposed methods could be compared favorably with existing multiclass boosting algorithms in terms of both the convergence rate and classification accuracy.
Towards an automated innovization method for handling discrete search spaces

Following manual observation of hidden relationships present in Pareto-optimal (PO) solutions of a multi-objective optimization problem, an automated Innovization procedure was suggested earlier for extracting innovative design principles. The goal was to obtain closed form and simple to understand relations that exist among PO solutions in a design or other problems. The proposed automated Innovization method was developed for handling continuous variable spaces. Since, most practical design problems have discrete variables in their descriptions, the aim of this study is to extend the earlier automated Innovization procedure to handle discrete variable spaces. We discuss the difficulties posed to an automated procedure due to the search space granularity and demonstrate the working of our proposed method on one numerical problem and two engineering design problems. Our study amply demonstrates that the extension of a real-parameter automated Innovization is not straightforward to discrete spaces, however such a procedure for discrete spaces raises new challenges which must be addressed for handling problems with mixed continuous-discrete search space problems.
Depression in Primary Care—More like Asthma Than Appendicitis: The Michigan Depression Project

Objective: To explore the relationships between detection, treatment, and outcome of depression in the primary care setting, based upon results from the Michigan Depression Project (MDP). Methods: A weighted sample of 425 adult family practice patients completed a comprehensive battery of questionnaires exploring stress, social support, overall health, health care utilization, treatment attitudes, self-rated levels of stress and depression, along with the Center for Epidemiologic Studies Depression Scale (CES-D), the Hamilton Rating Scale for Depression (HAM-D), and the Structured Clinical Interview for DSM-III (SCID), which served as the criterion standard for diagnosis. A comparison sample of 123 depressed psychiatric outpatients received the same assessment battery. Family practice patients received repeated assessment of depressive symptoms, stress, social support, and health care utilization over a period of up to 60 months of longitudinal follow-up. Results: The central MDP findings confirm that significant differences in past history, severity, and impairment exist between depressed psychiatric and family practice patients, that detection rates are significantly higher for severely depressed primary care patients, and that clinicians use clinical cues such as past history, distress, and severity of symptoms to “detect” depression in patients at intermediate and mild levels of severity. As well, there is a lack of association between detection and improved outcome in primary care patients. Conclusion: These results call into question the assumption that “depression is depression” irrespective of the setting and physician, and they are consistent with a model of depressive disorder as a subacute or chronic condition characterized by clinical parameters of severity, staging, and comorbidity, similar to asthma. This new model can guide further investigation into the epidemiology and management of mood disorders in the primary care setting.
Formal and informal nationalism

Abstract This article argues that nationalism is an essentially dual phenomenon with its crucial loci in the formal organization of the state on the one hand, and in civil society on the other. Formal nationalism is connected with the demands of the modern nation‐state, including bureaucratic organization and meritocratic ideology, cultural uniformity and political consensus among the inhabitants. Informal nationalism is identified in collective events, such as ritual celebrations and international sports competitions, taking place in civil society. Both these aspects of nationalism have been discussed in the recent literature, but it has not been common to distinguish between them. It is argued here that the two nationalisms are not reducible to each other; both are equally ‘authentic’, but they can be contradictory. Although the discussion is intended to have general relevance for theories of nationalism, it draws its empirical material from nationalist ideologies in two recently invented, poly‐ethnic n.
Lack of Association Between the Matrix Metalloproteinase-2-1306 C > T Polymorphism and Breast Cancer Susceptibility : a Meta-analysis

Breast cancer is the most frequent cancer and the principal cause of cancer-related death in female population around the world, accounting for 23% of new cases and 14% of total deaths globally (Jemal et al., 2011). Factors that are associated with increased risk of breast cancer include nulliparity (Hulka and Moorman 2001), postmenopausal hormone therapy (Hulka and Moorman 2001), alcohol consumption (Baan et al., 2007), high birth weight (Silva Idos et al., 2008) and so on. Although many environmental factors have been identified, the association between many genetic factors and breast cancer risk is still unclear and breast cancer is still lethal since many patients are presented with advanced stage at diagnosis (O’Shaughnessy 2005). Thus, early detection through gene indicators for breast cancer is valuable. Matrix metalloproteinases (MMPs) are a family of endopeptidases, capable of degrading both extracellular
The Message Design Logics of Organizational Change

This study investigated the influence of context in the production of messages by stakeholders about organizational change. We analyzed messages produced in response to hypothetical organizational change scenarios. The message production task was implemented within a 2×2 experimental design (N = 1,205) fielded at three different organizations. We included multiple replications for each manipulation, and multilevel structural equation modeling allowed for analysis across scenario replications. Results indicated that perceptions of change and context do influence message design mediated by intensity of beliefs about a change. The study extends message design logics theory and contributes to a conceptualization of stakeholder interaction during organizational change as a problem of communication design.
Opposition-Based Differential Evolution for Optimization of Noisy Problems

Differential evolution (DE) is a simple, reliable, and efficient optimization algorithm. However, it suffers from a weakness, losing the efficiency over optimization of noisy problems. In many real-world optimization problems we are faced with noisy environments. This paper presents a new algorithm to improve the efficiency of DE to cope with noisy optimization problems. It employs opposition-based learning for population initialization, generation jumping, and also improving population's best member. A set of commonly used benchmark functions is employed for experimental verification. The details of proposed algorithm and also conducted experiments are given. The new algorithm outperforms DE in terms of convergence speed.
Motivation driven learning for interactive synthetic characters

Adaptation capability and a transparent motivation system greatly aid real time interactions between humans and synthetic characters. These components enhance the life-like impression that the characters make, and enable comfortable communication between the characters and human participants. We extended the behavioral action selection system of Blumberg[2] and Kline[14] with these needs in mind, and developed a creature kernel that enables the designing of a character with communicative motivational and emotional states, and learning abilities based on feedback from the motivation system. In this paper, we introduce this new approach to character design, and how various learning algorithms have been incorporated within this framework. The main characters for an interactive installation, (void*): A cast of characters, have been created using this developed creature kernel. We describe results with examples of alteration of attitudes, learning of concepts, and formation of emotional reactions to locations based on experience.
Running head : 1 OsHTAS enhances heat tolerance in rice

Running head: 1 OsHTAS enhances heat tolerance in rice 2 3 Corresponding author: 4 Jumin Tu 5 Institute of Crop Science 6 Zhejiang University 7 866 Yuhangtang Road 8 Hangzhou, 310058, China 9 Tel: +86-0571-88982835 10 Fax: +86-0571-88982835 11 E-mail: jtu@zju.edu. cn 12 13 Cuicui Zhang 14 Institute of Crop Science 15 Zhejiang University 16 866 Yuhangtang Road 17 Hangzhou, 310058, China 18 Tel: +86-0571-88982835 19 Fax: +86-0571-88982835 20 E-mail: zhangcuicui@zju.edu. cn 21 22 Research area: 23 Signaling and Response, Stress Biology 24 25 26 Plant Physiology Preview. Published on November 12, 2015, as DOI:10.1104/pp.15. 00879
Validation of Type 2 Diabetes Risk Variants Identified by Genome-Wide Association Studies in Northern Han Chinese

Background: More than 60 genetic susceptibility loci associated with type 2 diabetes mellitus (T2DM) have been established in populations of Asian and European ancestry. Given ethnic differences and environmental factors, validation of the effects of genetic risk variants with reported associations identified by Genome-Wide Association Studies (GWASs) is essential. The study aims at evaluating the associations of T2DM with 29 single nucleotide polymorphisms (SNPs) from 19 candidate genes derived from GWASs in a northern Han Chinese population. Method: In this case-control study, 461 T2DM-diagnosed patients and 434 controls were recruited at the Jidong oil field hospital (Hebei, China) from January 2009 to October 2013. A cumulative genetic risk score (cGRS) was calculated by summation of the number of risk alleles, and a weight GRS (wGRS) was calculated as the sum of risk alleles at each locus multiplied by their effect sizes for T2DM, using the independent variants selected. Result: The allelic frequency of the “A” allele at rs17106184 (Fas-associated factor 1, FAF1) was significantly higher in the T2DM patients than that of the healthy controls (11.7% vs. 6.4%, p < 0.001). Individuals in the highestquartile of wGRS had an over three-fold increased risk for developing T2DM compared with those in the lowest quartile (odds ratio = 3.06, 95% CI = 1.92–4.88, p < 0.001) adjusted for age, sex, BMI, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP) and diastolic blood pressure (DBP). The results were similar when analyzed with the cGRS. Conclusions: We confirmed the association between rs17106184 (FAF1) and T2DM in a northern Han Chinese population. The GRS calculated based on T2DM susceptibility variants may be a useful tool for predicting the T2DM susceptibility.
Who commits the base rate fallacy?

processes. On our reading, this is the force of much of the recent work on reasoning. Cohen's claim that a theory of competence is all one needs for a theory of reasoning may also rest on an ill-conceived analogy: that theories of competence are to psychology what idealized models are to the natural sciences. Though widely drawn, this parallel is inaccurate. Idealizations in the natural sciences for example, the ideal gas laws or the Hardy-Weinberg law of equilibrium may describe the behavior of entities or systems under ideal conditions. Nevertheless, they are not used to do so. Idealized laws, rather, provide a way to describe an ideal state so that departures from the ideal may be explained in terms of factors predictable by parameters of the model. To date, psychologists have been unable to find idealized models that may be treated in this way with any success. Chomsky's theory of competence, for instance, though somewhat descriptive of speech produced under ideal circumstances, never provided a model in which everyday linguistic behavior could be explained. Similarly, competence models of reasoning will carry no weight as scientific idealizations unless formulated in such a way that departures from idealized behavior can be explained in terms of the idealized mechanisms.
Candidemia epidemiology and susceptibility profile in the largest Brazilian teaching hospital complex.

INTRODUCTION Although the spectrum of fungi causing bloodstream fungal infections continues to expand, Candida spp. remains responsible for the majority of these cases. OBJECTIVE The purpose of this study was to characterize the candidemia epidemiology, species distribution and antifungal susceptibility patterns at a Brazilian tertiary teaching public hospital with 2,500 beds. METHODS Records from the microbiology laboratory were used to identify patients with positive blood cultures during 2006. The in vitro activity of amphotericin B, caspofungin, itraconazole, fluconazole, voricanozole, and posaconazole were determined using the Etest method. RESULTS One hundred and thirty-six cases of candidemia were identified and 100 strains were available for antifungal susceptibility testing. The overall incidence of candidemia was 1.87 cases/1.000 admissions and 0.27 cases/1.000 patient-days. Among the patients, 58.1% were male, and the median age was 40 years old. C. albicans was the most common species (52.2%), followed by C. parapsilosis (22.1%), C. tropicalis (14.8%), and C. glabrata (6.6%). All strains were susceptible to amphotericin B with a MIC90 of 0.5 µg/mL. Overall susceptibility for voriconozole, fluconazole, and caspofungin was > 97% with a MIC90 of 0.064, 4.0 and 1.0 µg/mL, respectively. For itraconazole the susceptibility rate was 81% with a MIC90 of 0.5 µg/mL. Posaconazole also demonstrated good in vitro activity with a MIC90 of 0.25 µg/mL. CONCLUSION This is the first antifungal susceptibility report in our institution.