Miracle-dz/UniFAR-FTUs huggingface dataset:
SAFFRON: an adaptive algorithm for online control of the false discovery rate

In the online false discovery rate (FDR) problem, one observes a possibly infinite sequence of $p$-values $P_1,P_2,\dots$, each testing a different null hypothesis, and an algorithm must pick a sequence of rejection thresholds $\alpha_1,\alpha_2,\dots$ in an online fashion, effectively rejecting the $k$-th null hypothesis whenever $P_k \leq \alpha_k$. Importantly, $\alpha_k$ must be a function of the past, and cannot depend on $P_k$ or any of the later unseen $p$-values, and must be chosen to guarantee that for any time $t$, the FDR up to time $t$ is less than some pre-determined quantity $\alpha \in (0,1)$. In this work, we present a powerful new framework for online FDR control that we refer to as SAFFRON. Like older alpha-investing (AI) algorithms, SAFFRON starts off with an error budget, called alpha-wealth, that it intelligently allocates to different tests over time, earning back some wealth on making a new discovery. However, unlike older methods, SAFFRON's threshold sequence is based on a novel estimate of the alpha fraction that it allocates to true null hypotheses. In the offline setting, algorithms that employ an estimate of the proportion of true nulls are called adaptive methods, and SAFFRON can be seen as an online analogue of the famous offline Storey-BH adaptive procedure. Just as Storey-BH is typically more powerful than the Benjamini-Hochberg (BH) procedure under independence, we demonstrate that SAFFRON is also more powerful than its non-adaptive counterparts, such as LORD and other generalized alpha-investing algorithms. Further, a monotone version of the original AI algorithm is recovered as a special case of SAFFRON, that is often more stable and powerful than the original. Lastly, the derivation of SAFFRON provides a novel template for deriving new online FDR rules.
Parsing Graphs with Hyperedge Replacement Grammars

Hyperedge replacement grammar (HRG) is a formalism for generating and transforming graphs that has potential applications in natural language understanding and generation. A recognition algorithm due to Lautemann is known to be polynomial-time for graphs that are connected and of bounded degree. We present a more precise characterization of the algorithm’s complexity, an optimization analogous to binarization of contextfree grammars, and some important implementation details, resulting in an algorithm that is practical for natural-language applications. The algorithm is part of Bolinas, a new software toolkit for HRG processing.
A space-division time-division multiple access scheme for high throughput provisioning in WLANs

Directional antennas may dramatically increase the capacity of a wireless LAN by allowing several stations to simultaneously communicate. Since deployment of directive/smart antennas on the customer's terminals is awkward (for technological, cost, robustness, and convenience reasons) it is of interest to deploy advanced antenna solutions only at the access point. When omnidirectional transmissions are used at the mobile stations, the asynchronous nature of the 802.11 MAC handshake structurally limits the possibility to exploit spatial reuse. Significant throughput enhancements can be achieved only at the expense of redesigning (part of) the 802.11 MAC protocol: mainly a form of synchronization is required. This paper addresses this problem and proposes a novel solution, devised to operate in the above scenario. The system operation is based on the joint usage of space division and time division multiple access techniques. A synchronous time-division structure avoids unwanted interference among different antenna coverage regions. Backward compatibility with legacy IEEE 802.11 terminals is also accounted for.
Regularized ROC method for disease classification and biomarker selection with microarray data

MOTIVATION An important application of microarrays is to discover genomic biomarkers, among tens of thousands of genes assayed, for disease classification. Thus there is a need for developing statistical methods that can efficiently use such high-throughput genomic data, select biomarkers with discriminant power and construct classification rules. The ROC (receiver operator characteristic) technique has been widely used in disease classification with low-dimensional biomarkers because (1) it does not assume a parametric form of the class probability as required for example in the logistic regression method; (2) it accommodates case-control designs and (3) it allows treating false positives and false negatives differently. However, due to computational difficulties, the ROC-based classification has not been used with microarray data. Moreover, the standard ROC technique does not incorporate built-in biomarker selection. RESULTS We propose a novel method for biomarker selection and classification using the ROC technique for microarray data. The proposed method uses a sigmoid approximation to the area under the ROC curve as the objective function for classification and the threshold gradient descent regularization method for estimation and biomarker selection. Tuning parameter selection based on the V-fold cross validation and predictive performance evaluation are also investigated. The proposed approach is demonstrated with a simulation study, the Colon data and the Estrogen data. The proposed approach yields parsimonious models with excellent classification performance.
Mesoscale modeling of mechanical deformation of metallic glasses

Plastic deformation of metallic glasses (MGs) has been studied by both atomistic modeling such as molecular dynamics (MD) simulations and continuum modeling. However, heterogeneities above the atomic scale but below the micrometer scale are essential in understanding issues such as shear bands, which usually form at a time scale of 10−5 − 10−3 s with a characteristic thickness of 10− 100 nm. To bridge over the length scale from atomistic to continuum simulations, a physicsbased heterogeneously randomized shear transformation zone (STZ) model is developed by incorporating several key features, i.e., spatial heterogeneities, local order, and strain-induced softening that are missing from previous mesoscale models but are crucial to the understanding of the shear band formation in MGs. The model adopts STZ as the smallest unit of inelastic deformation and treats the macroscopic mechanical behavior of MGs as a stochastic sequence of discrete, spatially heterogeneously randomized STZ transformations, which can be then simulated using the kinetic Monte Carlo (kMC) method. Applications of the model to simulating the bulk MG samples under uniaxial tension tests find that the incorporation of softening plays a key role in localizing plastic shear, while the stress redistribution due to STZ transformation alone cannot lead to the shear band formation. The softening-induced shear instability inside the shear band is found responsible for a “runaway” feature of a local temperature rise, which falls in the same range of the experimental estimate.
Exploring Concept Representations for Concept Drift Detection

textabstractWe present an approach to estimating concept drift in online news. Our method is to construct temporal concept vectors from topicannotated news articles, and to correlate the distance between the temporal concept vectors with edits to the Wikipedia entries of the concepts. We find improvements in the correlation when we split the news articles based on the amount of articles mentioning a concept, instead of calendar-based units of time.
Towards a Stateful Forwarding Abstraction to Implement Scalable Network Functions in Software and Hardware

An effective packet processing abstraction that leverages software or hardware acceleration techniques can simplify the implementation of high-performance virtual network functions. In this paper, we explore the suitability of SDN switches' stateful forwarding abstractions to model accelerated functions in both software and hardware accelerators, such as optimized software switches and FPGA-based NICs. In particular, we select an Extended Finite State Machine abstraction and demonstrate its suitability by implementing the Linux's iptables interface. By doing so, we provide the acceleration of functions such as stateful firewalls, load balancers and dynamic NATs. We find that supporting a flow-level programming consistency model is an important feature of a programming abstraction in this context. Furthermore, we demonstrate that such a model simplifies the scaling of the system when implemented in software, enabling efficient multi-core processing without harming state consistency.
Incorporating polysomnography into obstructive sleep apnoea phenotyping: moving towards personalised medicine for OSA

Obstructive sleep apnoea (OSA) is a major health concern worldwide with multiorgan consequences and the resulting increased economic and social burden.1 OSA is associated with obesity in more than 60% of cases and often with comorbidities including hypertension, arrhythmia, stroke, coronary heart disease and metabolic dysfunction. The comorbidities are of major importance because they have a significant impact on healthcare use and mortality in patients with OSA. Only half of the patients with OSA are symptomatic and a significant percentage of subjects are referred and treated with the goal of limiting their cardiometabolic risk. This heterogeneity in a highly prevalent chronic disease with millions of patients on home-based long-term treatment requires the complete reshaping of patient characterisation and therapeutic strategies.2 Detailed phenotyping is the prerequisite for the development of precision and personalised medicine in chronic disease and particularly in OSA.3 The phenotyping of patients with OSA has been tackled in several different ways. One strategy has been to address the anatomical and physiological traits underlying OSA occurrence and the range of severity.4 The pathophysiological causes of OSA vary considerably between patients. Determining the respective contributions of upper airway anatomy and collapsibility, arousal threshold and loop gain (ventilator drive) will help to predict which therapeutic modality would be beneficial to the appropriately targeted patient subgroups.4 Another topic has been to define distinct OSA clinical phenotypes. Several recent studies exploiting large data sets have used unsupervised cluster analysis to identify distinct phenotypes.5 6 Subgroups have been recognised that varied considerably in age, gender, symptoms, obesity, comorbidities and environmental risk factors.5 6 The most significant differences between clusters were minimally symptomatic versus sleepy patients with OSA, lean versus obese, and among obese patients …
SAT0023 Direct-acting antiviral-based therapy restores immune tolerance in hepatitis c-induced cryoglobulinemia vasculitis

Objectives Interferon-free direct-acting antiviral (DAA)-based therapy has proven to be very effective in patients with hepatitis C virus-cryoglobulinemia vasculitis (HCV-CV). However, their mechanisms of action and their effects on cellular immunity remain poorly defined. Methods 27 HCV-CV patients treated with DAA therapy, 12 healthy donors (HD) and 12 HCV were included. We investigated the effects of DAA-based therapy on cellular and cytokine abnormalities in HCV-CV patients by flow cytometry, cytokine Multiplex and enzyme-linked immunosorbent assay. Results Compared with HD and HCV, pre-DAA abnormalities in HCV-CV patients included a decreased percentage of CD4+CD25hiFoxP3+ regulatory T cells (P<0.01) with increases in IgM+CD21-/low memory B cells (P<0.05), CD4+IFNγ+ (P<0.01), CD4+IL17A+ (P<0.01) and CD4+CXCR5+IL21+ follicular helper T cells (Tfh) (P<0.01). IgM+CD21-/low memory B cells were negatively correlated with regulatory T cells (Tregs) (P=0.03), and positively correlated with Tfh (P=0.03) and serum cryoglobulin levels (P=0.01). DAA-based therapy was associated with an increase in Tregs frequency (1.5% ± 0.18% versus 2.1% ± 0.18%), and decreased IgM+CD21-/low memory B cells and Tfh percentage (35.7% ± 6.1% versus 14.9% ± 3.8%, and 12% ± 1.3% versus 8% ± 0.9%, respectively). B lymphocyte stimulator receptor 3 and programmed death-ligand 1 staining expression on B cells increased in HCV-CV after DAA-based therapy (MFI 37±2.4 versus 47±2.6, P<0.01; and 29±7.3 versus 48±9.3, P<0.05 respectively). Conclusions Our results indicate that DAA-based therapy effectively normalizes many of the disturbances in peripheral B and T lymphocyte homeostasis of HCV-CV patients. Disclosure of Interest None declared
Effect of plant‐based diets on obesity‐related inflammatory profiles: a systematic review and meta‐analysis of intervention trials

Plant‐based dietary interventions have been proposed to reduce obesity induced chronic low‐grade inflammation and hence prevent chronic disease risk; however, human evidence remains unclear. This systematic review and meta‐analysis of intervention trials aimed to assess the effect of plant‐based diets on obesity‐related inflammatory biomarker profiles. Medline, EMBASE and Cochrane Central Register of Controlled Trials (CENTRAL) were searched for articles published until January 2016 and mean differences in biomarkers of inflammatory status were assessed for: C‐reactive protein (CRP), interleukin‐6 (IL‐6), tumour necrosis factor‐alpha (TNF‐ɑ), soluble intercellular adhesion molecule 1 (sICAM), leptin, adiponectin and resistin. Of initially identified 2,583 publications, 29 met the meta‐analysis inclusion criteria [a total of 2,689 participants]. Consumption of plant‐based diets was associated with a reduction in the mean concentrations of the following biomarkers: CRP [effect size, −0.55 mg/l, 95% confidence intervals (CI): −0.78; −0.32, I2 = 94.4%], IL‐6 [effect size, −0.25 ng/l, 95% CI: −0.56; 0.06, I2 = 74%], and, to some degree, sICAM (−25.07 ng/ml [95% CI: −52.32; 2.17, I2 = 93.2%]). No substantial effects were revealed for TNF‐ɑ, resistin, adiponectin and leptin. Plant‐based diets are associated with an improvement in obesity‐related inflammatory profiles and could provide means for therapy and prevention of chronic disease risk.
Subsampled online matrix factorization with convergence guarantees

We present a matrix factorization algorithm that scales to input matrices that are large in both dimensions (i.e., that contains morethan 1TB of data). The algorithm streams the matrix columns while subsampling them, resulting in low complexity per iteration andreasonable memory footprint. In contrast to previous online matrix factorization methods, our approach relies on low-dimensional statistics from past iterates to control the extra variance introduced by subsampling. We present a convergence analysis that guarantees us to reach a stationary point of the problem. Large speed-ups can be obtained compared to previous online algorithms that do not perform subsampling, thanks to the feature redundancy that often exists in high-dimensional settings.
Operational boundaries calculation of permanent magnet assisted synchronous reluctance motor

Operational boundaries calculation of Permanent Magnet assisted Synchronous Reluctance Motor is proposed. Furthermore the analysis of the thermal effects and iron losses on the motor operational boundaries is realized. The different motor analysis is carried out without finite element analysis, so the time required evaluating the envelope curve are reduced. Hence, operational boundaries can be introduced on optimization process of motor design. In this paper, the envelope curve obtained is calculated under the Maxim Torque per Ampere criteria, however another kind of curves, such as minimum losses or maximum efficiency, can be obtained by the same process. Finally, the methodology proposed to calculate operational boundaries is validated with finite element analysis.
Role of management information system in time saving

This Case Study will be used in order to investigate and establish the importance of role of Management Information System in time saving during the payment of automobile tax in Sindh through e-filling methods. Moreover it will also highlight the important factors which are involved as barriers and limit the role of MIS in time saving techniques. The approach which is used in this case study is descriptive research type along with the survey. The data used was collected from the specimen of common people working in different environments along with the officers working at Civic Centre (Automobile Tax Collection Branch excise department). The audience included were all well informed by the process and were eligible to give their opinions on the following research. A system design is also proposed along with an Erd which can be useful in the coming future. This research could likewise be expanded to include different of respondents, for example, paid taxpayers and different types of taxpayers. Paid tax payers are given the rights by their clients to prepare their assessment matters. They use the e-filing system for different types of clients and are more frequent users of the e-filing system than taxpayers who file for themselves. It would be interesting to understand which facets of hazard are larger to them. Different types of taxpayers, for example, company authorized cars may deal with more complex exchanges than single car taxpayers, consequently, they may emphasize different hazard facets when filing in the government form frame electronically
Targeting Corticotropin‐Releasing Factor Projections from the Oval Nucleus of the Bed Nucleus of the Stria Terminalis Using Cell‐Type Specific Neuronal Tracing Studies in Mouse and Rat Brain

The bed nucleus of the stria terminalis (BNST) is known to play a critical role in mediating the behavioural and autonomic responses to stressors. The oval nucleus of the BNST (BNSTov) contains cell bodies that synthesise the stress hormone corticotropin‐releasing factor (CRF). Although afferent fibres originating from the BNSTov have been shown to innervate several key structures of the neuroendocrine and central autonomic system, the question remains as to whether some of these fibres are CRF‐positive. To directly address this question, we injected a ‘floxed’ anterograde tracer (rAAV5/EF1a‐DIO‐mCherry) into the BNSTov of CRFp3.0CreGFP transgenic mice, which express a green fluorescent protein (GFP) under the control of the CRF promoter. Serial sections were then analysed for the presence of double‐labelled fibres in potential projection sites. To determine whether CRF neurons in the rat BNSTov send comparable projections, we infused rat BNSTov with an adeno‐associated viral vector (AAV) in which the human synapsin promoter drives enhanced GFP expression. We then used CRF immunoreactivity to examine double‐labelled fluorescent fibres and axon terminals in projection sites from brain sections of the AAV‐infused rats. We have observed several terminal fields in the mouse and rat brain with double‐labelled fibres in the Dorsal raphe nucleus (DRD), the paraventricular nucleus of the hypothalamus and, to a lesser extent, in the ventral tegmental area. We found double‐labelled terminal boutons in the nucleus accumbens shell, prelimbic cortex and posterior basolateral nucleus of the amygdala. The most intense double‐labelling was found in midbrain, including substantia nigra pars compacta, red nucleus, periaqueductal grey and pontine nuclei, as well as DRD. The results of the present study indicate that CRF neurons are the output neurons of the BNSTov and they send projections not only to the centres of neuroendocrine and autonomic regulation, but also regions modulating reward and motivation, vigilance and motor function, as well as affective behaviour.
Digitally Assisted RF-Analog Self Interference Cancellation for Wideband Full-Duplex Radios

This brief presents a new approach to cancelling self-interference in full-duplex radios. By augmenting minimal-complexity analog cancellation hardware using a radio frequency vector multiplier with the flexibility and effectiveness of a digital baseband rational function finite impulse response (FIR) filter, the proposed approach enables excellent cancellation performance over a wide modulation bandwidth. This algorithm is devised by exploiting a simplified baseband equivalent behavioral model of the front-end of the full-duplex radio. This allows the parameters of the rational function FIR filter to be identified linearly using the least-squares estimation. The hardware proof-of-concept prototype, built using off-the-shelf components, demonstrated minimum self-interference cancellations of 50 and 40 dB for digitally modulated test signals with modulation bandwidths of 20 and 40–120 MHz, respectively.
Hypertrophic Pachymeningitis in Sjögren's Syndrome

Although central nervous system manifestations seem common in primary Sjögren's syndrome, hypertrophic pachymeningitis is rare. We herein describe a case of Sjögren's syndrome that was associated with hypertrophic pachymeningitis. Sjögren's syndrome should be considered as a cause of hypertrophic pachymeningitis.
Advances in Animal In Vitro Fertilization 2

Much progress of relevance to the union of mammalian gametes in laboratory conditions has been reported during the last half century. Early in this interval, it was realized that spermatozoa must undergo the process of capacitation and that conditions for gamete union must, at least crudely, resemble those found at the normal site of fertilization, i.e., within the oviduct. Today it is possible to initiate early embryonic development of just about any mammalian species by co-incubating homologous ova with treated spermatozoa. This review will trace the development of in vitro fertilization (IVF) technology through experimentation with several laboratory and domestic animals. Information regarding nonhuman primates appears in Chapter 16. A few of hundreds of possible examples from available literature reports will be mentioned to illustrate advances in this important area of biological science. Utilization of IVF for enhancing reproductive efficiency, especially for cattle, and in preservation of genetically valuable and endangered animal species promises to impact significantly on animal breeding strategies.
The evolutionary pattern of mutations in glioblastoma reveals therapy-mediated selection

Glioblastoma presents as a heterogeneous disease with poor prognosis despite the use of multimodal therapy. Analysis of genomic DNA changes between initial diagnosis and recurrence in response to standard treatment protocols would enhance understanding of disease progression and better inform new treatment strategies. A cohort of 21 patients with primary glioblastoma were examined between diagnosis and first recurrence. This study presented a rare opportunity to characterize molecular alterations in tumors observed in three patients who received no therapeutic intervention, other than surgery, offering a unique control. We focused this study by comparing the dynamic mutation profiles between the primary tumors and their matched recurrent counterparts. Molecular profiling of tumors was performed using multiplexed targeted deep sequencing of 409 well characterized cancer-associated genes, achieving a mean read depth of 1272 x. Three levels of evidence suggested an evolutionary pattern consistent with a response to therapy-mediated selection pressures exists in treated patients: 1) variant burden was reduced in recurrent tumors, 2) neutral evolutionary dynamics apparent in untreated tumors shifted toward a non-neutral mode of evolution in treated patients at recurrence, and 3) the recurrent tumor of one patient displayed an increased mutation rate attributable to a temozolomide-associated hypermutator phenotype. Our observations suggest that current treatment modalities are likely to fail in achieving long term remission with the majority of relapse samples containing distinct mutations when compared to primary diagnostic samples.