Miracle-dz/UniFAR-FTUs huggingface dataset:
Online incentive mechanism design for smartphone crowd-sourcing

In this paper, we consider the problem of online incentive mechanism design for smart-phone crowd-sourcing. We consider the online setting where users arrive in a sequence and each user participating in crowd-sourcing submits a set of tasks it can accomplish and its corresponding bid. The platform then selects the users and their payments to maximize its utility while ensuring truthfulness, individual rationality, profitability, and polynomial algorithm complexity. The decision whether to accept or reject each user is made instantaneously, with no revocation. We propose an algorithm and show that it satisfies all the four desired properties of an efficient auction. Through extensive simulations, we evaluate the performance of our online algorithm.
Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network

Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.
ε - WGX: Adaptive Edge Probing for Enhancing Incomplete Networks

No matter how meticulously constructed, network datasets are often partially observed and incomplete. For example, most of the publicly available data from online social networking services (such as Facebook and Twitter) are collected via apps, users who make their accounts public, and/or the resources available to the researcher/practitioner. Such incompleteness can lead to inaccurate findings. We introduce the Adaptive Edge Probing problem. Suppose that one has observed a networked phenomenon via some form of sampling and has a budget to enhance the incomplete network by asking for additional information about specific nodes, with the ultimate goal of obtaining the most valuable information about the network as a whole. Which nodes should be further explored? We present ε-WGX, a network-based explore-exploit algorithm for identifying which nodes in the incomplete network to probe. Aggregated over multiple datasets and a wide range of probing budgets, we find that ε-WGX outperforms other explore-exploit strategies and baseline probing strategies. For example, for the task of adding as many nodes as possible, over incomplete networks observed via four popular sampling methods, ε-WGX outperforms the best comparison strategy by 12%-23% on average.
Overhead reducing information dissemination strategies for opportunistic communications

We examined the efficiency of information dissemination assuming a disconnected network architecture where highly mobile nodes form the network. The nodes have different limitations, like short battery life and low computing capabilities. We created IOBIO and MIOBIO, two protocols for information dissemination in this environment. In this article we present the results of several simulations - with a simulator created in OMNeT++ to analyze opportunistic communications - to compare the performance of the two information dissemination methods for a given mobility environment. The results give us an insight how to decrease the cost of communication in such networks.
Sources of satisfaction and stress among Indigenous academic teachers: findings from a national Australian study

Academics of Aboriginal and/or Torres Strait Islander descent are few in number but play a vital role in Australian university teaching. In addition to teaching both Indigenous and non-Indigenous students, they interact with academic colleagues in a context where pressures to “Indigenize” Australian curricula and increase Indigenous enrolments are growing. In this article, we will draw on our nation-wide research with Indigenous academics to further explore this under-researched area of Australian university teaching, and the highs and lows of how Indigenous teachers experience their roles. Our findings reveal that for our Indigenous colleagues, sources of personal and professional satisfaction – as well as stress – appear qualitatively different from those commonly associated with academic work. Of particular concern are the findings in relation to issues of cultural difference on our campuses, played out in the ways Indigenous and non-Indigenous staff and students interact daily. Counterbalancing this potential negativity is the strong, indeed inspiring, commitment on the part of our Indigenous academic participants to the educational futures of their students, and thus, to the futures of Indigenous communities across Australia. The findings raise some thought-provoking questions for individuals and institutions in the higher education systems of our region, and perhaps beyond.
Cell Signaling and Differential Protein Expression in Neuronal Differentiation of Bone Marrow Mesenchymal Stem Cells with Hypermethylated Salvador/Warts/Hippo (SWH) Pathway Genes

Human mesenchymal stem cells (MSCs) modified by targeting DNA hypermethylation of genes in the Salvador/Warts/Hippo pathway were induced to differentiate into neuronal cells in vitro. The differentiated cells secreted a significant level of brain-derived neurotrophy factor (BDNF) and the expression of BDNF receptor tyrosine receptor kinase B (TrkB) correlated well with the secretion of BDNF. In the differentiating cells, CREB was active after the binding of growth factors to induce phosphorylation of ERK in the MAPK/ERK pathway. Downstream of phosphorylated CREB led to the functional maturation of differentiated cells and secretion of BDNF, which contributed to the sustained expression of pERK and pCREB. In summary, both PI3K/Akt and MAPK/ERK signaling pathways play important roles in the neuronal differentiation of MSCs. The main function of the PI3K/Akt pathway is to maintain cell survival during neural differentiation; whereas the role of the MAPK/ERK pathway is probably to promote the maturation of differentiated MSCs. Further, cellular levels of protein kinase C epsilon type (PKC-ε) and kinesin heavy chain (KIF5B) increased with time of induction, whereas the level of NME/NM23 nucleoside diphosphate kinase 1 (Nm23-H1) decreased during the time course of differentiation. The correlation between PKC-ε and TrkB suggested that there is cross-talk between PKC-ε and the PI3K/Akt signaling pathway.
A New Evolutionary Algorithm for Cluster Analysis

(cid:3) Abstract — Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Performance Analysis of EGC Combining over Correlated Nakagami-m Fading Channels

In this paper, performance analysis of diversity technique with equal gain combining method (EGC) with two branches for the detection of signals in wireless communication systems is presented. In the following analysis, it is assumed that the fading via channels is Nakagami-m correlated. The first order statistical characteristics of the system are analysed. Useful formulae for the probability density function (pdf) and cumulative distribution function (cdf) of EGC output SIR are derived, and the effects of the fading severity on the output signal are observed.
An asymptotic analysis of the mean-variance portfolio selection

This paper gives an asymptotic analysis of the mean-variance (Markowitz-type) portfolio selection under mild assumptions on the market behavior. Theoretical results show the rate of underperformance of the risk aware Markowitz-type portfolio strategy in growth rate compared to the log-optimal portfolio strategy, which does not have explicit risk control. Statements are given with and without full knowledge of the statistical properties of the underlying process generating the market, under the only assumption that the market is stationary and ergodic. The experiments show how the achieved wealth depends on the coefficient of risk aversion measured on past NYSE data.
Onion peel water extracts enhance immune status in forced swimming rat model

Onion peel contains a high concentration of quercetin and other flavonoids. In this study, the potential immune-enhancing effects of an onion peel water extract (OPE) supplement were investigated by the rat forced swimming test. OPE was prepared using hot water. Thirty-six male Sprague Dawley rats were fed a pellet diet for 1 week and were then randomly divided into six groups: normal control (NC), forced swimming control (FSC), positive control (quercetin 20 mg/kg), and three groups administered 4, 20, or 100 mg/kg of OPE. Oral drug administration was conducted daily for 4 weeks. All rats, except those of NC group, were forced to swim in water and were considered exhausted when they failed to rise to the water surface to breathe within a 7-s period. Blood lymphocyte counts, immune organ weights, histopathological analysis, and serum interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and interleukin (IL)-12 levels were determined. OPE-treated rats consumed more food and had an increased thymic cortex to medulla ratio than that observed in FSC group rats (P<0.05). The area of the white pulp in the spleens of OPE-treated group rats was increased compared with that in FSC group rats (P<0.05). Furthermore, blood lymphocyte numbers and IFN-γ, TNF-α, and IL-12 concentrations were significantly higher in OPE-fed groups than in FSC group (P<0.05). These results suggest that an OPE supplement can improve the immune status by increasing the number of immune-related cells and specific cytokine levels.
Cuff-less PPG based continuous blood pressure monitoring - A smartphone based approach

Cuff-less estimation of systolic (SBP) and diastolic (DBP) blood pressure is an efficient approach for non-invasive and continuous monitoring of an individual's vitals. Although pulse transit time (PTT) based approaches have been successful in estimating the systolic and diastolic blood pressures to a reasonable degree of accuracy, there is still scope for improvement in terms of accuracies. Moreover, PTT approach requires data from sensors placed at two different locations along with individual calibration of physiological parameters for deriving correct estimation of systolic and diastolic blood pressure (BP) and hence is not suitable for smartphone deployment. Heart Rate Variability is one of the extensively used non-invasive parameters to assess cardiovascular autonomic nervous system and is known to be associated with SBP and DBP indirectly. In this work, we propose a novel method to extract a comprehensive set of features by combining PPG signal based and Heart Rate Variability (HRV) related features using a single PPG sensor. Further, these features are fed into a DBP feedback based combinatorial neural network model to arrive at a common weighted average output of DBP and subsequently SBP. Our results show that using this current approach, an accuracy of ±6.8 mmHg for SBP and ±4.7 mmHg for DBP is achievable on 1,750,000 pulses extracted from a public database (comprising 3000 people). Since most of the smartphones are now equipped with PPG sensor, a mobile based cuff-less BP estimation will enable the user to monitor their BP as a vital parameter on demand. This will open new avenues towards development of pervasive and continuous BP monitoring systems leading to an early detection and prevention of cardiovascular diseases.
CASINO: towards conformity-aware social influence analysis in online social networks

Social influence analysis in online social networks is the study of people's influence by analyzing the social interactions between individuals. There have been increasing research efforts to understand the influence propagation phenomenon due to its importance to information dissemination among others. Despite the progress achieved by state-of-the-art social influence analysis techniques, a key limitation of these techniques is that they only utilize positive interactions (e.g., agreement, trust) between individuals, ignoring two equally important factors, namely, negative relationships (e.g., distrust, disagreement) between individuals and conformity of people, which refers to a person's inclination to be influenced. In this paper, we propose a novel algorithm CASINO (Conformity-Aware Social INfluence cOmputation) to study the interplay between influence and conformity of each individual. Given a social network, CASINO first extracts a set of topic-based subgraphs where each subgraph depicts the social interactions associated with a specific topic. Then it optionally labels the edges (relationships) between individuals with positive or negative signs. Finally, it computes the influence and conformity indices of each individual in each signed topic-based subgraph. Our empirical study with several real-world social networks demonstrates superior effectiveness and accuracy of CASINO compared to state-of-the-art methods. Furthermore, we revealed several interesting characteristics of "influentials" and "conformers" in these networks.
Efficient Generalized Fused Lasso and Its Applications

Generalized fused lasso (GFL) penalizes variables with l1 norms based both on the variables and their pairwise differences. GFL is useful when applied to data where prior information is expressed using a graph over the variables. However, the existing GFL algorithms incur high computational costs and do not scale to high-dimensional problems. In this study, we propose a fast and scalable algorithm for GFL. Based on the fact that fusion penalty is the Lovász extension of a cut function, we show that the key building block of the optimization is equivalent to recursively solving graph-cut problems. Thus, we use a parametric flow algorithm to solve GFL in an efficient manner. Runtime comparisons demonstrate a significant speedup compared to existing GFL algorithms. Moreover, the proposed optimization framework is very general; by designing different cut functions, we also discuss the extension of GFL to directed graphs. Exploiting the scalability of the proposed algorithm, we demonstrate the applications of our algorithm to the diagnosis of Alzheimer’s disease (AD) and video background subtraction (BS). In the AD problem, we formulated the diagnosis of AD as a GFL regularized classification. Our experimental evaluations demonstrated that the diagnosis performance was promising. We observed that the selected critical voxels were well structured, i.e., connected, consistent according to cross validation, and in agreement with prior pathological knowledge. In the BS problem, GFL naturally models arbitrary foregrounds without predefined grouping of the pixels. Even by applying simple background models, e.g., a sparse linear combination of former frames, we achieved state-of-the-art performance on several public datasets.
Effect of Tirapazamine and Mild Temperature Hyperthermia on the Recovery from Radiation-Induced Damage in Pimonidazole-Unlabeled Quiescent Tumor Cell Population

The aim in this study is to examine the effect of tirapazamine (TPZ) and mild temperature hyperthermia (MTH) on the repair of radiation-induced damage in pimonidazole-unlabeled quiescent (Q) tumor cells. Labeling of proliferating (P) cells in C57BL/6J mice bearing EL4 tumors was achieved by continuous administration of 5-bromo-2-deoxyuridine (BrdU). Tumors were irradiated with γ-rays at 1 h after the administration of pimonidazole followed by TPZ treatment or MTH. Twenty-four hours later, assessment of the responses of Q and total (= P + Q) cells were based on the frequencies of micronucleation and apoptosis using immunofluorescence staining for BrdU. The response of the pimonidazole-unlabeled tumor cell fractions was assessed by means of apoptosis frequency using immunofluorescence staining for pimonidazole. With γ-rays only, the pimonidazole-unlabeled cell fraction showed significantly enhanced radio-sensitivity compared with the whole cell fraction more remarkably in Q cells than total cells. However, a significantly greater decrease in radio-sensitivity in the pimonidazole-unlabeled than the whole cell fraction, evaluated using a delayed assay, was more clearly observed in Q cells than total cells. Post-irradiation MTH more remarkably repressed the decrease in radio-sensitivity in the Q cell than the total cells. Post-irradiation TPZ administration produced a large radio-sensitizing effect on both total and Q cells, especially on Q cells. On the other hand, in pimonidazole-unlabeled cell fractions in both total and Q cells, TPZ suppressed the reduction in sensitivity due to delayed assay much more efficiently than MTH, whereas no radio-sensitizing effect was produced. Not only through suppressing the recovery from radiation-induced damage but also through radio-sensitizing effect, post-irradiation TPZ administration is very useful for repressing the increase in the difference in radio-sensitivity due to the delayed assay not only between total and Q tumor cells but also between the pimonidazole-unlabeled and the whole cell fractions within the total and Q tumor cells.
Web scale photo hash clustering on a single machine

This paper addresses the problem of clustering a very large number of photos (i.e. hundreds of millions a day) in a stream into millions of clusters. This is particularly important as the popularity of photo sharing websites, such as Facebook, Google, and Instagram. Given large number of photos available online, how to efficiently organize them is an open problem. To address this problem, we propose to cluster the binary hash codes of a large number of photos into binary cluster centers. We present a fast binary k-means algorithm that works directly on the similarity-preserving hashes of images and clusters them into binary centers on which we can build hash indexes to speedup computation. The proposed method is capable of clustering millions of photos on a single machine in a few minutes. We show that this approach is usually several magnitude faster than standard k-means and produces comparable clustering accuracy. In addition, we propose an online clustering method based on binary k-means that is capable of clustering large photo stream on a single machine, and show applications to spam detection and trending photo discovery.
Linkages Between Women's Provider-Role Attitudes, Psychological Well-Being, and Family Relationships

The primary aim of this investigation was to examine the extent to which the meanings women attach to their provider-role responsibilities are differentially related to their psychological well-being and family relationships and to the division of labor in the home. The sample included 43 dual-earner and 50 single-earner families. In home interviews, wives reported on role overload, depression, satisfaction with the marriage, and attitudes regarding women's and men's roles. Their children completed two measures assessing daily hassles and their relationship with their mother. Reports of daily involvement in household work were obtained from wives and husbands during four telephone interviews. Discriminant function analyses indicated that aspects of women's psychological well-being and marital and parent-child relationships and of the division of labor discriminated women in four different provider groups: main/secondary providers, ambivalent coproviders, coproviders, and homemakers. Wives who were ambivalent about their provider responsibilities tended to report higher levels of depression and overload and significantly lower marital satisfaction. Wives who saw their employment as secondary to that of their husbands reported relatively higher levels of depression and overload but also the highest levels of marital satisfaction.
The Hassan Case: An Analysis of the Issue of Accent Discrimination in American Higher Education

This article addresses the often-hidden accent discrimination issue in higher education. The article begins with an examination of the concept of just what an accent is. Next, the scope of Title VH's protection against discrimination due to national origin is analyzed. The rationale for equating accent and national origin discrimination under Title VH's umbrella is laid out. Then, court rulings in cases of alleged accent discrimination both within and outside of higher education are examined. This sets the stage for an analysis of the decision in Hassan v. Auburn University (1993), which offers important insights into the scope of administrative prerogative to deal with the language and accent issue in higher education. A concluding discussion of the ramifica­ tions of the Hassan court's ruling for higher education in a changing era is then offered. America's colleges and universities enjoy a competitive advantage versus the rest of the world. Around the globe, the quality of American higher education is regarded as unequaled. Higher education institutions in the United States thus stand in a unique position. They have the ability to attract the best and the brightest from countries all over the planet to come to the United States for their academic pursuits—both as students and professors. What is at the core of America's magnetism to attract the best scholars worldwide? Former Harvard University President Derek Bok answered quite clearly that the answer lay in the common currency of the English language. He wrote:
Abelian Higgs hair for an AdS-Schwarzschild black hole

We show that the Abelian Higgs field equations in the background of the four dimensional AdS-Schwarzschild black hole have a vortex line solution. This solution, which has axial symmetry, is a generalization of the AdS spacetime Nielsen-Olesen string. From a numerical study of the field equations, we show that black hole could support an Abelian Higgs field as its Abelian hair. Also, we consider the self-gravity of the Abelian Higgs field both in pure AdS spacetime and the AdS-Schwarzschild black hole background and show that the effect of a string as black hole hair is to induce a deficit angle in the AdS-Schwarzschild black hole.
Wireless power transfer for electric vehicle

In this paper, a review of existing wireless power transfer solutions used in electric vehicle battery charger are provided. The different levels of battery charger are discussed based on the recommended practice by SAE J-113. The concept for each solution is reviewed and evaluated considering the performance of battery charger, power electronic limitations and the circuit topologies. Furthermore, the credits and disadvantages of the wireless power transfer technologies, compensation and power electronics requirement for electric vehicle are discussed and compared in detail. Finally, a proposed circuit topology for resonant inductive wireless charging is presented.