Miracle-dz/UniFAR-FTUs huggingface dataset:
Differentially Private Distributed Online Algorithms Over Time-Varying Directed Networks

We consider a private distributed online optimization problem where a set of agents aim to minimize the sum of locally convex cost functions while each desires that the local cost function of individual agent is kept differentially private. To solve such problem, we propose differentially private distributed stochastic subgradient online optimization algorithm over time-varying directed networks. We use differential privacy to preserve the privacy of participating agents. We show that our algorithm preserves differential privacy and achieves logarithmic expected regret under locally strong convexity. Moreover, we also show that square-root expected regret is obtained under local convexity. Furthermore, we reveal the tradeoff between the privacy level and the performance of our algorithm.
Effect of visualization techniques on subjective quality of light field images

Light Field imaging derives from the fundamentals of light field sampling, where the spatial information about a scene can be captured with angular information. That is, the Light Field imaging is based on a camera recording information about the intensity of light from the scene and about the direction of the light rays. The acquired data can be shown to the user in different ways, such as image with digitally extended depth of field, 3D, parallax, and 360 degree display. In this contribution, the impact of different rendering techniques on the Quality of Experience is addressed. The achieved results show that the visualization techniques may have different impact on the perceived quality even when the same content is considered.
Wavelet-based histograms for selectivity estimation

Query optimization is an integral part of relational database management systems. One important task in query optimization is selectivity estimation, that is, given a query P, we need to estimate the fraction of records in the database that satisfy P. Many commercial database systems maintain histograms to approximate the frequency distribution of values in the attributes of relations. In this paper, we present a technique based upon a multiresolution wavelet decomposition for building histograms on the underlying data distributions, with applications to databases, statistics, and simulation. Histograms built on the cumulative data distributions give very good approximations with limited space usage. We give fast algorithms for constructing histograms and using them in an on-line fashion for selectivity estimation. Our histograms also provide quick approximate answers to OLAP queries when the exact answers are not required. Our method captures the joint distribution of multiple attributes effectively, even when the attributes are correlated. Experiments confirm that our histograms offer substantial improvements in accuracy over random sampling and other previous approaches.
Using topic analysis techniques to support comprehensive research paper searches

In an academic paper search to confirm the originality of a user's research, it is important that the search returns comprehensive results relevant to the user's information need. To achieve comprehensive search results, users often relax initially restrictive search formula by adding synonyms and expressions similar to the search words with operator OR, and/or replacing AND with OR operations. However, it is difficult to anticipate all the terms that authors of relevant papers might have used. In addition, the replacement of AND with OR in search phrases can return a large number of unrelated papers. To overcome these issues, we propose a research paper search method based on topic analysis, which uses Boolean search based on the topics assigned to the search words in the search formula and the abstracts that contain any search word. Our method considers synonyms and expressions similar to the search words, which a user might not anticipate, while limiting the number of papers unrelated to the information need in the search result. To investigate the effectiveness of our method, we conducted experiments using the NTCIR-1 and 2 datasets, and confirmed that our method shows a reduction effect on unrelated papers, while maintaining high coverage.
Electrogenetherapy of B16.F10 murine melanoma tumors with an interleukin-28 expressing DNA plasmid

Augmented delivery of cytokine-expressing DNA plasmids to subcutaneous tumors has been demonstrated to result in a level of enhanced anti-tumor activity. One delivery enhancement method which has been evaluated is in vivo electroporation (EP), a contact-dependent delivery technique where electric pulses are hypothesized to augment the transfer of DNA into cells and tissues through the induction of temporary cell membrane pores. Previous work by members of our group, as well as others, has demonstrated the anti-tumor effects of DNA plasmids expressing the cytokines IL-12 and IL-15. In this report the potential anti-tumor activity of a relatively newly-described cytokine, IL-28, was measured when administered intratumorally as a DNA expression plasmid (designated pIL28) to established murine (B16.F10) melanoma tumors. The administration of the IL-28 expressing plasmid was performed through enhanced delivery methods. One method was EP and the other a non-contact dependent technique using a helium plasma stream. IL-28 is a member of the type III interferon family of cytokines that has been characterized as possessing potent anti-viral activity. This cytokine has been demonstrated to function as an adjuvant in small animal model vaccination protocols and stimulates CD8+ CTL responses. In addition, stimulation of anti-tumor activity has been demonstrated in several studies using IL-28. Based on these activities, it was hypothesized that this cytokine could, when delivered through a DNA expression plasmid, mediate anti-tumor activity. The results of this study indicated that enhanced delivery of pIL-28 resulted in attenuation of tumor growth, compared with non-enhanced delivery. Of note, this is the first proof-of-concept experiment, of our knowledge, documenting the ability of a non-contact dependent helium plasma-based delivery method to mediate the enhancement of an anti-tumor effect by a cytokine-expressing DNA plasmid. This suggests the use of the helium plasma delivery method as an alternative or adjunctive method to EP for the effective delivery of agents that possess potential anti-tumor activity.
Selection on skewed characters and the paradox of stasis

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modeling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold's (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson–Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate sample sizes. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date — repeatedly described as more evolutionarily stable than expected — so this skewness should be accounted for when investigating evolutionary dynamics in the wild.
Ecological Impacts of Alien Species: Quantification, Scope, Caveats, and Recommendations

Despite intensive research during the past decade on the effects of alien species, invasion science still lacks the capacity to accurately predict the impacts of those species and, therefore, to provide timely advice to managers on where limited resources should be allocated. This capacity has been limited partly by the context-dependent nature of ecological impacts, research highly skewed toward certain taxa and habitat types, and the lack of standardized methods for detecting and quantifying impacts. We review different strategies, including specific experimental and observational approaches, for detecting and quantifying the ecological impacts of alien species. These include a four-way experimental plot design for comparing impact studies of different organisms. Furthermore, we identify hypothesis-driven parameters that should be measured at invaded sites to maximize insights into the nature of the impact. We also present strategies for recognizing high-impact species. Our recommendations provide a foundation for developing systematic quantitative measurements to allow comparisons of impacts across alien species, sites, and time.
A systematic review and meta-analysis of the incidence of psychotic disorders: the distribution of rates and the influence of gender, urbanicity, immigration and socio-economic level

Background Considering existing knowledge on the relationship between certain environmental factors and incidence rates of psychosis, we carried out a systematic review to provide a broad and updated picture of the incidences of different psychotic disorder subgroups worldwide and how some environmental factors influence these rates. Methods Studies with original data related to the incidence of psychosis (published between 2000 and 2015) were identified via searching electronic databases (CINAHL, MEDLINE, PSYCINFO, PUBMED, and SCOPUS). Data on the following risk factors were extracted: gender, urbanicity, immigration and socio-economic level. Descriptive appraisals of variation in incidence rates (IR) and incidence rate ratios (IRR), with a 95% confidence interval were calculated. In addition, a meta-analysis was performed to calculate IR pooled by diagnosis group and IRR pooled by diagnosis and gender, urbanity, immigration and socio-economic level, using a random effects model. Results We identified 33 reports to analyse. Overall IR per 100 000 persons for non-affective psychoses (IR pooled = 22.53 (16.51–28.54)) were higher than affective psychoses (IR pooled = 7.12 (5.03–9.22)). There was an increase in rates of psychosis in men v. women (IRR pooled = 1.54 (1.37–1.72)), in urban v. rural areas (IRR pooled = 1.64 (1.38–1.95)), in immigrants v. natives (IRR pooled = 3.09 (2.74–3.49)), and in lower socio-economic level areas (IRR pooled = 1.78 (1.43–2.22)). Conclusions IR among different psychotic disorders was found to vary depending on gender, urbanicity, and immigration (as most of the previous literature focuses on non-affective psychosis or schizophrenia).
Full Duplex Wireless Communications for Cognitive Radio Networks

Abstract—As a key in cognitive radio networks (CRNs), dy-namic spectrum access needs to be carefully designed to minimizethe interference and delay to the primary (licensed) users. One ofthe main challenges in dynamic spectrum access is to determinewhen the secondary (unlicensed) users can use the spectrum.In particular, when the secondary user is using the spectrum,if the primary user becomes active to use the spectrum, it isusually hard for the secondary user to detect the primary userinstantaneously, thus causing unexpected interference and delayto primary users. The secondary user cannot detect the presenceof primary users instantaneously because the secondary useris unable to detect the spectrum at the same time while it istransmitting. To solve this problem, we propose the full duplexwireless communications scheme for CRNs. In particular, weemploy the Antennas Cancellation (AC), the RF InterferenceCancellation (RIC), and the Digital Interference Cancellation(DIC) techniques for secondary users so that the secondary usercan scan for active primary users while it is transmitting. Oncedetecting the presence of primary users, the secondary user willrelease the spectrum instantaneously to avoid the interferenceand delay to primary users. We analyze the packet loss rateof primary users in wireless full duplex CRNs, and comparethem with the packet loss rate of primary users in wireless halfduplex CRNs. Our analyses and simulations show that using ourdevelopped wireless full duplex CRNs, the packet loss rate ofprimary users can be signiﬁcantly decreased as compared wit hthat of primary users by using the half duplex CRNs.Index Terms—Cognitive radio networks (CRNs), full duplexCRNs, dynamic spectrum sensing, packet loss rate, interferencecontrol.
Platelets release pathogenic serotonin and return to circulation after immune complex-mediated sequestration

Significance Immune complexes (ICs) form when antibodies encounter their antigens. ICs are present in blood in multiple pathological conditions. Given the abundance of platelets in blood and that they express a receptor for ICs, called Fcγ receptor IIA (FcγRIIA), we examined the impact of ICs in blood in a mouse model. We found that circulating ICs induced systemic shock, characterized by loss of consciousness, by activating platelet FcγRIIA. Shock was mediated by the liberation of serotonin, a molecule better known for its role in the brain, from platelet granules. During shock, platelets were sequestered in the lungs and brain and returned to the blood circulation after their degranulation. Platelets are thus crucial in response to ICs. There is a growing appreciation for the contribution of platelets to immunity; however, our knowledge mostly relies on platelet functions associated with vascular injury and the prevention of bleeding. Circulating immune complexes (ICs) contribute to both chronic and acute inflammation in a multitude of clinical conditions. Herein, we scrutinized platelet responses to systemic ICs in the absence of tissue and endothelial wall injury. Platelet activation by circulating ICs through a mechanism requiring expression of platelet Fcγ receptor IIA resulted in the induction of systemic shock. IC-driven shock was dependent on release of serotonin from platelet-dense granules secondary to platelet outside-in signaling by αIIbβ3 and its ligand fibrinogen. While activated platelets sequestered in the lungs and leaky vasculature of the blood–brain barrier, platelets also sequestered in the absence of shock in mice lacking peripheral serotonin. Unexpectedly, platelets returned to the blood circulation with emptied granules and were thereby ineffective at promoting subsequent systemic shock, although they still underwent sequestration. We propose that in response to circulating ICs, platelets are a crucial mediator of the inflammatory response highly relevant to sepsis, viremia, and anaphylaxis. In addition, platelets recirculate after degranulation and sequestration, demonstrating that in adaptive immunity implicating antibody responses, activated platelets are longer lived than anticipated and may explain platelet count fluctuations in IC-driven diseases.
A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring

A low-power multi-functional electrocardiogram (ECG) signal processor is presented in this paper. To enable long-term monitoring, several architecture-level power saving techniques are proposed, including global cognitive clocking, pseudo-downsampling wavelet transform, adaptive storing, and denoising-based run-length compression. An ultra-low-voltage ADC is designed for low-power signal digitization with adaptive clocking. Through these architecture-level techniques, the total power consumption can be significantly reduced by 63% as compared to the conventional design. Several circuit-level design techniques are also developed, including ultra-low-voltage operation and near-threshold level shifting, to further reduce the power consumption by 33%. In addition, a low-complexity cardiac analysis scheme is proposed to realize comprehensive on-chip cardiac analysis. Implemented in 0.18 μm CMOS process, the proposed cognitive ECG processor consumes only 457 nW at 0.5 V for real-time ECG recording and diagnosis.
Comparative analysis of single precision floating point multiplication using compressor techniques

Compressor models are used to perform arithmetic operations like multiplication, addition etc. in digital signal processing applications such as Fast Fourier Transform, Convolution and Filtering. In order to achieve the high speed, the optimization takes place in all abstraction levels. In this paper, single precision floating point multiplication is developed using different compressor architectures to achieve high speed. Further, first, floating point multipliers are developed with normal 4:2 conventional compressors using XOR gates and further the same multipliers are developed using modified Compressors with XOR-XNOR gates and Multiplexers to achieve optimized delay and area. All the models are coded with Verilog HDL and implemented using Xilinx ISE.
Mentoring as a Knowledge Translation Intervention for Implementing Nursing Practice Guidelines: A Qualitative Study

Abstract An interpretive descriptive qualitative study was conducted to explore the characteristics and outcomes of mentoring used for implementing nursing practice guidelines. We interviewed six mentees, eight mentors, and four program leaders who were involved in the Registered Nurses' Association of Ontario fellowship program in Ontario, Canada. Inductive content analysis was used and study rigor was verified using triangulation of findings and member checking. Mentors were described as accessible, dedicated, and having expertise; mentees were described as enthusiastic, self-directed, and having mixed levels of expertise. The mentoring process included building relationships, developing learning plans, and using teaching and learning activities guided by learning plans to support development of mentees. Mentoring was described as positively impacting mentoring relationships, mentees, mentors, and organizations. A central feature of this fellowship program was the learning plan used to identify mentees’ needs, guide mentoring activities, and monitor measureable outcomes.
Toponym disambiguation in historical documents using semantic and geographic features

Historians are often interested in the locations mentioned in digitized collections. However, place names are highly ambiguous and may change over time, which makes it especially hard to automatically ground mentions of places in historical texts to their real-world referents. Toponym disambiguation is a challenging problem in natural language processing, and has been approached in two different yet related tasks: toponym resolution and entity linking. In this paper, we propose a weakly-supervised method that combines the strengths of both approaches by exploiting both geographic and semantic features. We tested our method against a historical toponym resolution benchmark and improved the state of the art. We also created five datasets and tested the performance of two state-of-the-art out-of-the-box entity linking methods and also improved on their performance when only locations are considered.
Exploration of approximate multipliers design space using carry propagation free compressors

Many emerging application domains, such as machine learning, can tolerate limited amounts of arithmetic inaccuracy. When designing custom compute accelerators for these domains, hardware designers can explore tradeoffs that sacrifice accuracy in order to reduce area, delay, and/or power consumption. This paper explores the design space of approximate multipliers using a family of approximate compressors as building blocks for the partial product reduction tree. We present a tool that allows the user to specify an allowable level of error tolerance, and returns the minimum area, delay, or power approximate multiplier that provides that level of accuracy. Our experimental results indicate that our proposed compressors generate more accurate and more efficient approximate multipliers than existing state-of-the-art techniques.
HMGB1 is involved in autophagy inhibition caused by SNCA/α-synuclein overexpression

SNCA/α-synuclein and its rare mutations are considered as the culprit proteins in Parkinson disease (PD). Wild-type (WT) SNCA has been shown to impair macroautophagy in mammalian cells and in transgenic mice. In this study, we monitored the dynamic changes in autophagy process and confirmed that overexpression of both WT and SNCAA53T inhibits autophagy in PC12 cells in a time-dependent manner. Furthermore, we showed that SNCA binds to both cytosolic and nuclear high mobility group box 1 (HMGB1), impairs the cytosolic translocation of HMGB1, blocks HMGB1-BECN1 binding, and strengthens BECN1-BCL2 binding. Deregulation of these molecular events by SNCA overexpression leads to autophagy inhibition. Overexpression of BECN1 restores autophagy and promotes the clearance of SNCA. siRNA knockdown of Hmgb1 inhibits basal autophagy and abolishes the inhibitory effect of SNCA on autophagy while overexpression of HMGB1 restores autophagy. Corynoxine B, a natural autophagy inducer, restores the deficient cytosolic translocation of HMGB1 and autophagy in cells overexpressing SNCA, which may be attributed to its ability to block SNCA-HMGB1 interaction. Based on these findings, we propose that SNCA-induced impairment of autophagy occurs, in part, through HMGB1, which may provide a potential therapeutic target for PD.
Variable Frame Length Of A Higher Order Speech AR Estimation In A Speech Enhancement System

We study some speech enhancement algorithms based on the iterative Wiener filtering method due to Lim-Oppenheim [2], where the AR spectral estimation of the speech is carried out using a 2nd-order analysis. But in our algorithms we consider an AR estimation by means of cumulant analysis. This work extends some preceding papers due to the authors, providing a different frame length where AR estimation is done. Information of previous speech frames is used to initiate speech AR modelling of the current frame. Two parameters are introduced to dessign Wiener filter at first iteration of this iterative algorithm. These parameters are the Interframe Factor IF and the Previous Frame Iteration PFI. They allow a very important noise suppression after processing only fxst iteration of this algorithm, without any appreciable increase of distortion.
Generation of intermediate viewpoints for scalable adaptation of real world environments for virtual reality

Virtual Reality (VR) is a rapidly growing field with innovative applications. Two main forms of VR content can be identified in current applications: Computer generated 3D environments and adaptations of real world scenarios through means of digital imagery and video. While the latter provides a more realistic experience, scalable content generation methods for adaptations of real world environments to virtual space is still unavailable. Needless to say achieving unrestricted navigability in such environments, on a mobile platform with near real time response is quite challenging. The paper presents the algorithm for scalable intermediate view generation, devised as a part of a research to develop an universal content generation platform for real world environments in virtual reality. The algorithm uses adjacent equirectangular images to recreate the 360° × 180° view of any point in-between, taking directional deformation into account. Input can be equirectangular images captured using any device, including 360 cameras and panoramas captured through mobile phones. The output can be rendered on specialized VR headsets or mobile phones. The algorithm is implemented with mobile platform as the target, thus rendering is optimized for limited resource utilization. The paper presents the concept, design and optimization used in this method.