Miracle-dz/UniFAR-FTUs huggingface dataset:
Impaired cerebrovascular reactivity in multiple sclerosis.

IMPORTANCE Cerebrovascular reactivity (CVR) is an inherent indicator of the dilatory capacity of cerebral arterioles for a vasomotor stimulus for maintaining a spontaneous and instant increase of cerebral blood flow (CBF) in response to neural activation. The integrity of this mechanism is essential to preserving healthy neurovascular coupling; however, to our knowledge, no studies have investigated whether there are CVR abnormalities in multiple sclerosis (MS). OBJECTIVE To use hypercapnic perfusion magnetic resonance imaging to assess CVR impairment in patients with MS. DESIGN, SETTING, AND PARTICIPANTS A total of 19 healthy volunteers and 19 patients with MS underwent perfusion magnetic resonance imaging based on pseudocontinuous arterial spin labeling to measure CBF at normocapnia (ie, breathing room air) and hypercapnia. The hypercapnia condition is achieved by breathing 5% carbon dioxide gas mixture, which is a potent vasodilator causing an increase of CBF. MAIN OUTCOMES AND MEASURES Cerebrovascular reactivity was calculated as the percent increase of normocapnic to hypercapnic CBF normalized by the change in end-tidal carbon dioxide, which was recorded during both conditions. Group analysis was performed for regional and global CVR comparison between patients and controls. Regression analysis was also performed between CVR values, lesion load, and brain atrophy measures in patients with MS. RESULTS A significant decrease of mean (SD) global gray matter CVR was found in patients with MS (3.56 [0.81]) compared with healthy controls (5.08 [1.56]; P = .001). Voxel-by-voxel analysis showed diffuse reduction of CVR in multiple regions of patients with MS. There was a significant negative correlation between gray matter CVR and lesion volume (R = 0.6, P = .004) and a significant positive correlation between global gray matter CVR and gray matter atrophy index (R = 0.5, P = .03). CONCLUSIONS AND RELEVANCE Our quantitative imaging findings suggest impairment in functional cerebrovascular pathophysiology, by measuring a diffuse decrease in CVR, which may be the underlying cause of neurodegeneration in MS.
A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems

Firefly algorithm FA is a nature-inspired optimisation algorithm that can be successfully applied to continuous optimisation problems. However, lot of practical problems are formulated as discrete optimisation problems. In this paper a hybrid discrete firefly algorithm HDFA is proposed to solve the multi-objective flexible job shop scheduling problem FJSP. FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimisation objectives - the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithms discretisation which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm DFA is combined with local search LS method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems.
A Computational Approach to Identify a Potential Alternative Drug With Its Positive Impact Toward PMP22

Mutations in the Peripheral Myelin Protein 22 (PMP22) leads to Charcot Marie Tooth type 1A (CMT1A, a subtype of CMT1) disease which is the most common inherited neuropathy of peripheral nervous system. In the present study, we used series of in silico prediction methods to screen and identify the most deleterious non‐synonymous SNPs (nsSNPs) in PMP22 gene. Out of 48 nsSNPs, five nsSNPs (L16P, L19P, T23R, W28R, and L147R) associated with PMP22 were predicted to be highly deleterious and destabilizing the protein. To explore the possible structure‐function relationship, we employed abinitio modeling strategy using the CABS‐fold server to predict the three‐dimensional structure models in the absence of crystallized structures in PMP22 protein. We used Cytoscape 3.4.0 plugin Integrated Complex Traits Networks interface (iCTNet) to identify the probable drug‐gene interactions in PMP22 gene. A total of 22 chemical compounds yielded from the aforementioned tool was subjected to Molinspiration and OSIRIS program to screen and identify the potent drug molecules for further analysis. Five chemical compounds with excellent bioavailability and drug relevant property were selected for molecular docking simulation study. We modeled five mutant structures at their corresponding positions and performed molecular docking simulation analysis using AutoDock Tools (ADT) version 1.5. 6 and ArgusLab 4.0. 1 tools to analyze their interaction patterns and binding efficacy. Based on the results obtained from the computational study, we predict that estradiol could be a potential drug of choice for treating patients with CMT1A which needs larger attention from biologists in the near future. J. Cell. Biochem. 118: 3730–3743, 2017. © 2017 Wiley Periodicals, Inc.
Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.
Perception of weight and psychological variables in a sample of Spanish adolescents

Background: This study explored the relationship between body mass index (BMI) and weight perception, self-esteem, positive body image, food beliefs, and mental health status, along with any gender differences in weight perception, in a sample of adolescents in Spain. Methods: The sample comprised 85 students (53 females and 32 males, mean age 17.4 ± 5.5 years) with no psychiatric history who were recruited from a high school in Écija, Seville. Weight and height were recorded for all participants, who were then classified according to whether they perceived themselves as slightly overweight, very overweight, very underweight, slightly underweight, or about the right weight, using the question “How do you think of yourself in terms of weight? ”. Finally, a series of questionnaires were administered, including the Irrational Food Beliefs Scale, Body Appreciation Scale, Self Esteem Scale, and General Health Questionnaire. Results: Overall, 23.5% of participants misperceived their weight. Taking into account only those with a normal BMI (percentile 5–85), there was a significant gender difference with respect to those who perceived themselves as overweight (slightly overweight and very overweight); 13.9% of females and 7.9% of males perceived themselves as overweight (χ2 = 3.957, P < 0.05). There was a significant difference for age, with participants who perceived their weight adequately being of mean age 16.34 ± 3.17 years and those who misperceived their weight being of mean age 18.50 ± 4.02 years (F = 3.112, P < 0.05). Conclusion: Misperception of overweight seems to be more frequent in female adolescents, and mainly among older ones. Misperception of being overweight is associated with a less positive body image, and the perception of being very underweight is associated with higher scores for general psychopathology.
A self-resetting spiking phase-change neuron

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.
Localization of the low-density lipoprotein receptor-related protein regions involved in binding to the A2 domain of coagulation factor VIII

Summary Catabolism of coagulation factorVIII (FVIII) is mediated by lowdensity lipoprotein receptor-related protein (LRP). The ligandbinding sites of LRP are formed by complement-type repeats (CR), and CR clusters II and IV bind most of LRP ligands. FVIII contains two major LRP-binding sites located in the A2 and A3 domains. This study was aimed to identify specific complementtype repeats of LRP involved in interaction with the A2 site and to probe their functional importance in A2 catabolism. We generated individual LRP clusters II, III and IV, along with nine overlapping CR triplets encompassing clusters II and IV in a baculovirus expression system and studied their interaction with isolated A2. In surface plasmon resonance (SPR) assay, A2 bound to clusters II and IV with KDs 22 and 39 nM, respectively, and to the majority of CR triplets with affinities in the range of KDs 25–90 nM. Similar affinities were determined for A2 interaction with a panel of CR doublets overlapping cluster II (CR 3–4, 4–5, 5–6 6–7 and 7–8). These LRP fragments inhibited the binding of 125I-A2 to LRP in solid-phase assay,LRP-mediated internalization of 125I-A2 in cell culture and 125I-A2 clearance from the mouse circulation. Point mutations of critical A2 residues of the LRPbinding site resulted in differential reduction or abolishment of its binding to LRP fragments. We conclude that A2 interacts with LRP via multiple binding sites spanning CR 3–8 in cluster II and CR 23–29 in cluster IV, and the minimal A2-binding unit of LRP is formed by two adjacent CR.
Vesper: Measuring Time-to-Interactivity for Web Pages

Everyone agrees that web pages should load more quickly. However, a good definition for “page load time” is elusive. We argue that, for pages that care about user interaction, load times should be defined with respect to interactivity: a page is “loaded” when above-the-fold content is visible, and the associated JavaScript event handling state is functional. We define a new load time metric, called Ready Index, which explicitly captures our proposed notion of load time. Defining the metric is straightforward, but actually measuring it is not, since web developers do not explicitly annotate the JavaScript state and the DOM elements which support interactivity. To solve this problem, we introduce Vesper, a tool that rewrites a page’s JavaScript and HTML to automatically discover the page’s interactive state. Armed with Vesper, we compare Ready Index to prior load time metrics like Speed Index; across a variety of network conditions, prior metrics underestimate or overestimate the true load time for a page by 24%–64%. We introduce a tool that optimizes a page for Ready Index, decreasing the median time to page interactivity by 29%–32%.
HokieGo at 2017 PM Task: Genetic Programming based re-ranking method In Biomedical Information Retrieval

This paper summarizes our efforts on TREC 2017 Precision Medicine Track. We present a genetic programming based learning-to-rank algorithm. We perform two training experiments on 2014 and 2016 TREC CDS data and apply the pre-trained model as re-ranking method to improve the performance. In addition, two utility functions, CHK and FFP4, have been used for the training optimization.
Optimal Range-Difference-Based Localization Considering Geometrical Constraints

This paper proposes a new type of algorithm aimed at finding the traditional maximum-likelihood (TML) estimate of the position of a target given time-difference-of-arrival (TDOA) information, contaminated by noise. The novelty lies in the fact that a performance index, akin to but not identical with that in maximum likelihood (ML), is a minimized subject to a number of constraints, which flow from geometric constraints inherent in the underlying problem. The minimization is in a higher dimensional space than for TML, and has the advantage that the algorithm can be very straightforwardly and systematically initialized. Simulation evidence shows that failure to converge to a solution of the localization problem near the true value is less likely to occur with this new algorithm than with TML. This makes it attractive to use in adverse geometric situations.
Fast Algorithms for Diameter-Optimally Augmenting Paths and Trees

We consider the problem of augmenting an [Formula: see text]-vertex graph embedded in a metric space, by inserting one additional edge in order to minimize the diameter of the resulting graph. We present exact algorithms for the cases when (i) the input graph is a path, running in [Formula: see text] time, and (ii) the input graph is a tree, running in [Formula: see text] time. We also present an algorithm for paths that computes a [Formula: see text]-approximation in [Formula: see text] time.
Evaluation of fatigue limit characteristics of lamellar pearlitic steel in consideration of microstructure

In this study, tensile and fatigue tests were performed to evaluate the fatigue limit of lamellar pearlitic steel used for manufacturing railroad rail. The fatigue ratio of lamellar pearlitic steel was lower than that of general steels, the reason for which is unknown. Fatigue cracks initiated in pearlitic steel at a very early stage of the fatigue test. Then, it was speculated that the steel should be treated as that with initial defects. In order to determine the initial defect size in the ultra-low cycle fatigue test, tensile tests were performed. The tensile test results clarified that the crack initiation size depends on the crystal structure. In order to predict the fatigue limit of the pearlitic steel, the prediction method proposed by Murakami was applied to the steel. The measured defect sizes were applied to the prediction method, and fatigue tests were performed. The predicted fatigue limit and the test results were in good agreement. In addition, in order to evaluate the crystal structure at the location of the fatigue crack initiation, electron backscatter diffraction pattern (EBSD) analyses were performed. The analysis results revealed that the crack initiation depends on the pearlite block. Then, we concluded that the fatigue limit of pearlitic steel can be predicted by Murakami's method and the defect size is pearlite block size. Then, decreasing the pearlite block size would cause an improvement in the fatigue limit of the pearlitic steel.
A Network Meta‐Analysis of Non‐Melanoma Skin Cancer (NMSC) Treatments: Efficacy and Safety Assessment

The mainstream treatments for non‐melanoma skin cancer (NMSC) include photodynamic therapy (PDT), surgery excision (SE), cryotherapy (CT), imiquimod (IM), radiotherapy (RT), 5‐fluorouracil (FU), and vehicle (VE). Our network meta‐analysis (NMA) was aimed at evaluating the efficacy and safety of these seven treatments and providing superior ones. After searching the trials from Embase and PubMed and screening with our criteria, we conducted the NMA with software R 3.2. 3 and STATA 13.0. Complete lesion response (CLR), complete lesion clearance (CLC), cumulative recurrence probabilities (CRP), and adverse effects (AEs) were considered as outcomes and displayed as odds ratios (ORs) and 95% credible intervals (CrI). The surface under the cumulative ranking curve (SUCRA) was calculated to rank each treatment on each index. The consistency of direct and indirect evidence was also assessed by node‐splitting and heat plot methods. Data from 18 trials with 3706 patients were included. Both IM and SE were demonstrated significantly higher CLR rate than VE (OR = 9.12, 95% CrI = 1.92–47.5; OR = 26.1, 95% CrI = 1.92‐347; respectively), while only IM was proved to be statistically better than VE in CLC rate (OR = 7.03, 95% CrI = 1.51–32.8). No significant difference was observed concerning CRP, and IM was more likely to induce AEs than VE (OR = 4.44, 95% CrI = 1.58–13.9). The SUCRA results indicated that SE was the treatment with best ranking in the entire three efficacy indexes and a relatively high safety. Taking efficacy and safety into account, our study recommended SE as the optimal regimen for NMSC with high efficacy considering CLR, CLC, and CRP and moderate AEs when compared with other interventions. J. Cell. Biochem. 118: 3686–3695, 2017. © 2017 Wiley Periodicals, Inc.
Material Characterization of Roselle Fibre (Hibiscus sabdariffa L.) as Potential Reinforcement Material for Polymer Composites

Recently,in line with rising environmental concerns,n researchers are now replacing synthetic fibres with natural ones as the main component in composites.Natural fibres are preferred to synthetic fibres because of several advantages such as biodegradable,light weight, low cost and good mechanical properties.Roselle is one of the plants found to be suitable to be used to produce natural fibres.In this work,we analysed the physical, thermal and mechanical characteristics of roselle fibre. Roselle fibre has good physical properties which lead to the dimensional stability of the composite product.The result obtained indicated that the moisture content of roselle fibre is 10.9%,while water absorption is 286.5%. Thermal gravimetric analysis (TGA) was conducted to understand the thermal stability of roselle fibre at high temperature.The results show that the initial degradation of roselle fibre starts at 225 °C and completes the decomposition of the lignocellulosic component at 400 4C. A tensile test was conducted to investigate the mechanical properties of roselle fibre.The tensile strength of roselle fibre is 130 - 562 MPa.On the basis of the properties of roselle fibres obtained,we concluded that roselle fibre is one of the good natural fibres that can be used as reinforced material for the manufacturing of polymer composites for different applications,while at the same time saving the cost required to manage the agro waste.
Ninjurin1 Assembles Into a Homomeric Protein Complex Maintained by N‐linked Glycosylation

Ninjurin1 (Ninj1) is a cell surface protein known as a homophilic adhesion molecule. Previous studies have shown a trans‐interaction of Ninj1 between immune cells and endothelial cells; however, little is known about Ninj1 modification and structure in the cis‐interaction. We showed that Ninj1 assembles into a homomeric complex via a cis‐interaction mediated by the intracellular region and N‐glycosylation at Asn60. We identified cis‐interaction between Ninj1 proteins using CFP‐ and YFP‐tagged Ninj1 by Förster resonance energy transfer using a confocal microscope and fluorescence‐activated cell sorter. We further observed the Ninj1 homomeric complexes composed of two to six monomeric Ninj1 molecules by a formaldehyde cross‐linking assay. Co‐immunoprecipitation assays with epitope‐tagged truncated Ninj1 suggested that the intracellular region encompassing Leu101–Ala110 participates in Ninj1 homomer assembly. Ninj1 N‐glycosylation was characterized by treatment of tunicamycin and substitution of Asn to Gln or Ala. Fluorescence‐activated cell sorting‐based Förster resonance energy transfer assays further demonstrated that N‐glycosylation is indispensable for the Ninj1 cis‐interaction, and a formaldehyde cross‐linking assay confirmed that interruption of N‐glycosylation by Asn substitution disrupted Ninj1 homomeric complex formation. In silico analysis revealed that Ninj1 is highly conserved in vertebrates and that the conserved sequence contains an N‐glycosylation motif and cis‐interacting intracellular region, which participate in Ninj1 homomer assembly. Taken together, these data show that Ninj1 assembles into a homomeric protein complex and that N‐glycosylation is a prerequisite for Ninj1 homomer assembly. J. Cell. Biochem. 118: 2219–2230, 2017. © 2017 Wiley Periodicals, Inc.
Optimizing Trade-offs Among Stakeholders in Real-Time Bidding by Incorporating Multimedia Metrics

Displaying banner advertisements (in short, ads) on webpages has usually been discussed as an Internet economics topic where a publisher uses auction models to sell an online user's page view to advertisers and the one with the highest bid can have her ad displayed to the user. This is also called real-time bidding (RTB) and the ad displaying process ensures that the publisher's benefit is maximized or there is an equilibrium in ad auctions. However, the benefits of the other two stakeholders - the advertiser and the user - have been rarely discussed. In this paper, we propose a two-stage computational framework that selects a banner ad based on the optimized trade-offs among all stakeholders. The first stage is still auction based and the second stage re-ranks ads by considering the benefits of all stakeholders. Our metric variables are: the publisher's revenue, the advertiser's utility, the ad memorability, the ad click-through rate (CTR), the contextual relevance, and the visual saliency. To the best of our knowledge, this is the first work that optimizes trade-offs among all stakeholders in RTB by incorporating multimedia metrics. An algorithm is also proposed to determine the optimal weights of the metric variables. We use both ad auction datasets and multimedia datasets to validate the proposed framework. Our experimental results show that the publisher can significantly improve the other stakeholders' benefits by slightly reducing her revenue in the short-term. In the long run, advertisers and users will be more engaged, the increased demand of advertising and the increased supply of page views can then boost the publisher's revenue.