Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of siRNA as a pharmacological tool to assess a role for the transcription factor NF-IL6 in the brain under in vitro and in vivo conditions during LPS-induced inflammatory stimulation

Abstract Background: Studies with NF-IL6-deficient mice indicate that this transcription factor plays a dual role during systemic inflammation with pro- and anti-inflammatory capacities. Here, we aimed to characterize the role of NF-IL6 specifically within the brain. Methods: In this study, we tested the capacity of short interfering (si) RNA to silence the inflammatory transcription factor nuclear factor-interleukin 6 (NF-IL6) in brain cells under in vitro and in vivo conditions. Results: In cells of a mixed neuronal and glial primary culture from the rat area postrema (AP), short interfering RNA (siRNA) directed against NF-IL6 strongly reduced basal and lipopolysaccharide (LPS)-induced nuclear immunoreactivity of this transcription factor, with the strongest effect on astrocytes. The siRNA did not exert inflammatory effects in the primary culture as confirmed by unaltered levels of IL-6 in supernatants. In vivo, intracerebroventricular (i.c.v.) injections of fluorochrome labelled siRNA caused its appearance in relevant brain structures for fever induction pathways such as the vascular organ of lamina terminalis, the subfornical organ, the median preoptic nucleus (MnPO) and the AP in several cell types, including microglial cells. However, i.c. v. injections of siRNA per se caused signs of fever, anorexia and reduced locomotor activity, i.e. sickness behavior. Conclusions: This approach was, thus, not suitable to characterize the role NF-IL6 in the brain in vivo, namely during experimentally induced systemic inflammation.
Distributions, ex situ conservation priorities, and genetic resource potential of crop wild relatives of sweetpotato [Ipomoea batatas (L.) Lam., I. series Batatas]

Crop wild relatives of sweetpotato [Ipomoea batatas (L.) Lam. , I. series Batatas] have the potential to contribute to breeding objectives for this important root crop. Uncertainty in regard to species boundaries and their phylogenetic relationships, the limited availability of germplasm with which to perform crosses, and the difficulty of introgression of genes from wild species has constrained their utilization. Here, we compile geographic occurrence data on relevant sweetpotato wild relatives and produce potential distribution models for the species. We then assess the comprehensiveness of ex situ germplasm collections, contextualize these results with research and breeding priorities, and use ecogeographic information to identify species with the potential to contribute desirable agronomic traits. The fourteen species that are considered the closest wild relatives of sweetpotato generally occur from the central United States to Argentina, with richness concentrated in Mesoamerica and in the extreme Southeastern United States. Currently designated species differ among themselves and in comparison to the crop in their adaptations to temperature, precipitation, and edaphic characteristics and most species also show considerable intraspecific variation. With 79% of species identified as high priority for further collecting, we find that these crop genetic resources are highly under-represented in ex situ conservation systems and thus their availability to breeders and researchers is inadequate. We prioritize taxa and specific geographic locations for further collecting in order to improve the completeness of germplasm collections. In concert with enhanced conservation of sweetpotato wild relatives, further taxonomic research, characterization and evaluation of germplasm, and improving the techniques to overcome barriers to introgression with wild species are needed in order to mobilize these genetic resources for crop breeding.
Displaying Locality: Connecting with Customers and Visitors In-Situ via their Mobile Devices

A large and growing proportion of the general population in the UK and similar nations routinely carry smart phones and access the Internet while on the go. However, especially in rural areas, mobile Internet access can be intermittent and slow, and the particularities of the immediate locality can get lost in the non-geographical vastness of the Internet. In order to understand more about the opportunities and challenges of connecting with customers and visitors in-situ on their mobile phones we extended a media authoring and distribution research system to support both Internet-based and off-Internet situated displays for discovering and downloading local multimedia content. Within a broader participatory process, we ran a workshop with members of the community of a small countryside town, working with participants to understand the local relevance of this kind of system. The ability to work off-Internet was considered important in some specific rural situations. The local and situated character of the system led to a proposal to establish a town-wide network and a common identity through such a system, and through this to steer visitors from entry points (e.g. significant tourist sites) to other sites and enterprises within the town.
Phase control and fast start-up of a magnetron using modulation of an addressable faceted cathode

The use of an addressable, faceted cathode has been proposed as a method of modulating current injection in a magnetron to improve performance and control phase. To implement the controllable electron emission, five-sided and ten-sided faceted planar cathodes employing gated field emitters are considered as these emitters could be fabricated on flat substrates. For demonstration, the conformal finite-difference time-domain particle-in-cell simulation, as implemented in VORPAL, has been used to model a ten-cavity, rising sun magnetron using the modulated current sources and benchmarked against a typical continuous current source. For the modulated, ten-sided faceted cathode case, the electrons are injected from three emitter elements on each of the ten facets. Each emitter is turned ON and OFF in sequence at the oscillating frequency with five emitters ON at one time to drive the five electron spokes of the π-mode. The emitter duty cycle is then 1/6th the Radio-Frequency (RF) period. Simulations show a fas.
The Yale–Brown Obsessive Compulsive Scale

The Yale–Brown Obsessive Compulsive Scale (Y-BOCS) is the most frequently applied test to assess obsessive compulsive symptoms. We conducted a reliability generalization meta-analysis on the Y-BOCS to estimate the average reliability, examine the variability among the reliability estimates, search for moderators, and propose a predictive model that researchers and clinicians can use to estimate the expected reliability of the Y-BOCS. We included studies where the Y-BOCS was applied to a sample of adults and reliability estimate was reported. Out of the 11,490 references located, 144 studies met the selection criteria. For the total scale, the mean reliability was 0.866 for coefficients alpha, 0.848 for test–retest correlations, and 0.922 for intraclass correlations. The moderator analyses led to a predictive model where the standard deviation of the total test and the target population (clinical vs. nonclinical) explained 38.6% of the total variability among coefficients alpha. Finally, clinical implications of the results are discussed.
Failure transitions for joint n-gram models and G2p conversion

This work investigates two related issues in the area of WFSTbased G2P conversion. The first is the impact that the approach utilized to convert a target word to an equivalent finite-state machine has on downstream decoding efficiency. The second issue considered is the impact that the approach utilized to represent the joint n-gram model via the WFST framework has on the speed and accuracy of the system. In the latter case two novel algorithms are proposed, which extend the work from [1 ]t o enable the use of failure-transitions with joint n-gram models. All solutions presented in this work are available as part of the open-source, BSD-licensed Phonetisaurus G2P toolkit [2]. Index Terms: G2P, WFST, model conversion
Age-related multisensory enhancement in a simple audiovisual detection task

Older adults are known to gain more than younger adults from the simultaneous presentation of semantically congruent sensory stimuli. Although these findings are quite exciting, they may not solely be due to age-related differences in multisensory processing. Rather, enhanced integration may be explained by alterations associated with general cognitive slowing. This study utilized a task that eliminated most high-order cognitive processing. As such, no significant differences in unisensory response times were seen; however, older adults actually showed faster multisensory responses than younger adults. Older adults continued to show significantly greater multisensory enhancement than younger adults. Data support the conclusion that differences in multisensory processing for older adults cannot be explained solely by the effects of general cognitive slowing.
Evidence of large‐scale range shift in the distribution of a Palaearctic migrant in Africa

Long‐distance Palaearctic migrant birds are declining at a faster rate than short‐distance migrant or resident species. This is often attributed to changes on their non‐breeding grounds and along their migratory routes. The European honey buzzard (Pernis apivorus) is a scarce migrant in southern Africa that is declining globally. This study assessed the distribution and abundance of honey buzzards in southern Africa over the past four decades and compared it to trends in the East African population to examine possible drivers of population expansion in southern Africa.
A Dynamically Adaptable Hardware Transactional Memory

Most Hardware Transactional Memory (HTM) implementations choose fixed version and conflict management policies at design time. While eager HTM systems store transactional state in-place in memory and resolve conflicts when they are produced, lazy HTM systems buffer the transactional state in specialized hardware and defer the resolution of conflicts until commit time. Each scheme has its strengths and weaknesses, but, unfortunately, both approaches are too inflexible in the way they manage data versioning and transactional contention. Thus, fixed HTM systems may result in a significant performance opportunity loss when they execute complex transactional applications. In this paper, we present DynTM (Dynamically Adaptable HTM), the first fully-flexible HTM system that permits the simultaneous execution of transactions using complementary version and conflict management strategies. In the heart of DynTM is a novel coherence protocol that allows tracking conflicts among eager and lazy transactions. Both the eager and the lazy execution modes of DynTM exhibit very high performance compared to modern HTM systems. For example, the DynTM lazy execution mode implements local commits to improve on previous proposals. In addition, lazy transactions share the majority of hardware support with eager transactions, reducing substantially the hardware cost compared to other lazy HTM systems. By utilizing a simple predictor to decide the best execution mode for each transaction at runtime, DynTM obtains an average speedup of 34% over HTM systems that employ fixed version and conflict management policies.
Epidemiology of anaphylaxis

Purpose of review The purpose of this article is not only to review the epidemiology of anaphylaxis and factors that affect the epidemiology but also to help us understand underlying mechanisms and predisposing factors. This, in turn, has a bearing on efforts related to prevention and management. Recent findings The purpose of this review is to assess the incidence of anaphylaxis and to review the factors that affect this incidence, with special reference to the most common causes, drugs and foods. Factors affecting the incidence are geographic location, sex, atopy, and socioeconomic status. Although no exact incidence, based upon available data, can be established, it is reasonable to assume that 1–2% of the population may be affected. Also, clearly, there is underreporting of episodes. Finally, the incidence of anaphylaxis appears to be increasing. Summary The exact incidence of anaphylaxis is unknown, but appears to be increasing. Foods and drugs are the most common causes. The incidence is affected by geographical location, sex, atopy, and socioeconomic factors.
Strategic Trade and Delegated Competition

Strategic trade theory has been criticized on the grounds that its predictions are overly sensitive to modeling assumptions. For example, Eaton and Grossman (1986) show that Brander and Spencer's (1985) seminal result – i.e., when firms compete by setting quantities the optimal policy involves governments subsidizing their domestic industries – is reversed if the firms compete by setting prices. Applying recent results in duopoly theory, this paper considers three-stage games in which governments choose subsidies, firms' owners choose incentive schemes for their managers, and then the managers compete in the product market. We show that if firms' owners have sufficient control over their managers' behavior, then the optimal strategic trade policy does not depend on whether firms compete by setting prices or quantities. In a linear-demand model in which managers are compensated based on a linear combination of their own firm's profit plus a (possibly negative) multiple of the rival firm's profit, the optimal policy is to subsidize if goods are substitutes and tax if the goods are complements.
Identity-by-Descent-Based Phasing and Imputation in Founder Populations Using Graphical Models

Accurate knowledge of haplotypes, the combination of alleles co‐residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical‐By‐Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long‐range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome‐wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage‐like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853‐860, 2011
Use of Case-Based Reasoning to Enhance Intensive Management of Patients on Insulin Pump Therapy

Background: This study was conducted to develop case-based decision support software to improve glucose control in patients with type 1 diabetes mellitus (T1DM) on insulin pump therapy. While the benefits of good glucose control are well known, achieving and maintaining good glucose control remains a difficult task. Case-based decision support software may assist by recalling past problems in glucose control and their associated therapeutic adjustments. Methods: Twenty patients with T1DM on insulin pumps were enrolled in a 6-week study. Subjects performed self-glucose monitoring and provided daily logs via the Internet, tracking insulin dosages, work, sleep, exercise, meals, stress, illness, menstrual cycles, infusion set changes, pump problems, hypoglycemic episodes, and other events. Subjects wore a continuous glucose monitoring system at weeks 1, 3, and 6. Clinical data were interpreted by physicians, who explained the relationship between life events and observed glucose patterns as well as treatment rationales to knowledge engineers. Knowledge engineers built a prototypical system that contained cases of problems in glucose control together with their associated solutions. Results: Twelve patients completed the study. Fifty cases of clinical problems and solutions were developed and stored in a case base. The prototypical system detected 12 distinct types of clinical problems. It displayed the stored problems that are most similar to the problems detected, and offered learned solutions as decision support to the physician. Conclusions: This software can screen large volumes of clinical data and glucose levels from patients with T1DM, identify clinical problems, and offer solutions. It has potential application in managing all forms of diabetes.
Multi-scale complexity analysis of cardiac variability time series in adult and mid-aged females

Multi-scale entropy (MSE) analysis is being used as a complexity measure to quantify the hidden complexity of heart rate variability (HRV) signals in healthy and diseased states since quite some time. Thereafter the refined MSE (RMSE) was introduced in which refinement was made in the elimination of fast temporal scales by replacing the low pass filter used in original MSE with a butter worth low pass filter. The threshold value `r' is updated as a function of standard deviation (SD) of the filtered scaled time series. In the present study comparative analysis of both these techniques have been done on cardiac time series derived from adult female and mid-aged female groups for a data length of N=4000 and template matching length of m=2. Both these techniques assign higher entropy value to the adult female group than that of mid aged female group. It has been observed that HRV of adult female acquire more complex pattern than that of mid aged female group and it reduces with ageing. RMSE analysis results in better discrimination between both these groups (p<;0.01).
Autism and emotional face‐viewing

Atypical patterns of face‐scanning in individuals with autism spectrum disorder (ASD) may contribute to difficulties in social interactions, but there is little agreement regarding what exactly characterizes face‐viewing in ASD. In addition, little research has examined how face‐viewing is modulated by the emotional expression of the stimuli, in individuals with or without ASD. We used eye‐tracking to explore viewing patterns during perception of dynamic emotional facial expressions in relatively large groups of individuals with (n = 57) and without ASD (n = 58) and examined diagnostic‐ and age‐related effects, after subgrouping children and adolescents (≤18 years), on the one hand, and adults (>18 years), on the other. Results showed that children/adolescents with ASD fixated the mouth of happy and angry faces less than their typically developing (TD) peers, and conversely looked more to the eyes of happy faces. Moreover, while all groups fixated the mouth in happy faces more than in other expressions, children/adolescents with ASD did relatively less so. Correlation analysis showed a similar lack of relative orientation towards the mouth of smiling faces in TD children/adolescents with high autistic traits, as measured by the Autism‐Spectrum Quotient (AQ). Among adults, participants with ASD only attended less to the eyes for neutral faces. Our study shows that the emotional content of a face influences gaze behaviour, and that this effect is not fully developed in children/adolescents with ASD. Interestingly, this lack of differentiation observed in the younger ASD group was also seen in younger TD individuals with higher AQ scores. Autism Res 2017, 10: 901–910. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
Learning dynamics explains human behaviour in Prisoner's Dilemma on networks

Cooperative behaviour lies at the very basis of human societies, yet its evolutionary origin remains a key unsolved puzzle. Whereas reciprocity or conditional cooperation is one of the most prominent mechanisms proposed to explain the emergence of cooperation in social dilemmas, recent experimental findings on networked Prisoner's Dilemma games suggest that conditional cooperation also depends on the previous action of the player—namely on the ‘mood’ in which the player is currently in. Roughly, a majority of people behave as conditional cooperators if they cooperated in the past, whereas they ignore the context and free ride with high probability if they did not. However, the ultimate origin of this behaviour represents a conundrum itself. Here, we aim specifically to provide an evolutionary explanation of moody conditional cooperation (MCC). To this end, we perform an extensive analysis of different evolutionary dynamics for players' behavioural traits—ranging from standard processes used in game theory based on pay-off comparison to others that include non-economic or social factors. Our results show that only a dynamic built upon reinforcement learning is able to give rise to evolutionarily stable MCC, and at the end to reproduce the human behaviours observed in the experiments.
Strategic Pooling of Compounds for High-Throughput Screening

Bringing new medicines to the market depends on the rapid discovery of new and effective drugs, often initiated through the biological testing of many thousands of compounds in high-throughput screening (HTS). Mixing compounds together into pools for screening is one way to accelerate this process and reduce costs. This paper contains both theoretical and experimental data which suggest that careful selection of compounds to be pooled together is necessary in order to reduce the risk of reactivity between compounds within the pools.
Understading Image Restoration Convolutional Neural Networks with Network Inversion

In recent years, Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many image restoration applications. The knowledge of how these models work, however, is still limited. While there have been many attempts at better understanding the inner working of CNNs, they have mostly been applied to classification networks. Because of this, most existing CNN visualization techniques may be inadequate to the study of image restoration architectures. In the paper, we present network inversion, a new method developed specifically to help in the understanding of image restoration Convolutional Neural Networks. We apply our method to underwater image restoration and dehazing CNNs, showing how it can help in the understanding and improvement of these models.
Modeling TCP Throughput with Random Packet Drops

The present report deals with the modeling of the long-term throughput, a.k. a. , send rate, of the Transmission Control Protocol (TCP) under the following assumptions. (i) We consider a single 'infinite source' using a network path from sender to receiver. (ii) Each TCP packet is randomly dropped with probability p; independently of previous drops or any other event/parameter. (iii) The - never changing - receiver window limits the amount of outstanding data. (iv) The receiver acknowledges every packet. (v) The TCP modeled here conforms to the publicly available standards (RFCs) as concerns congestion control. We validate and determine the limits of the different models proposed here using packet-level simulations. The contributions of the present work are the following: (a) We determine three regimes, and their conditions of applicability, depending on p: Linear law regime, square root law regime, and timeout regime. (b) As concerns the relationship between the linear and square root regimes, we give additional insights relatively to previously published work. (c) We give the exact equations governing the TCP send rate in any regime. (d) From the exact equation and under the further condition that the path is not saturated, we give and discuss approximations for the send rate of the NewReno variant of TCP. A by-product of these calculations is the distribution of the sender window, independently of any timing or saturation consideration. (e) These approximations give results that are accurate to a few percent when compared to simulation results. Detailed comparison and sources of errors between theory and simulations are also discussed.