nils-herrmann/clean_scirepeval huggingface dataset:
Intrinsic functional network architecture of human semantic processing: Modules and hubs
Venue: NeuroImage

Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta analysis of 120 neuroimaging studies (Binder et al. 2009) we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN) the left perisylvian network (Module PSN) and the left frontoparietal network (Module FPN) These three dissociable modules were integrated by multiple connector hubs the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control.
Biomarker validation of a decline in semantic processing in preclinical Alzheimer's disease.
Venue: Neuropsychology

Differentially worse performance on category versus letter fluency suggests greater semantic versus retrieval difficulties. This discrepancy, combined with reduced episodic memory, has widespread clinical utility in diagnosing Alzheimer's disease (AD) Our objective was to investigate whether changes in semantic processing, as measured by the discrepancy between category and letter fluency, was detectable in preclinical AD: in clinically normal older adults with abnormal b amyloid (Ab) deposition on positron emission tomography (PET) neuroimaging.  Clinically normal older adults (mean Mini Mental State Exam (MMSE) score 29) were classified as Ab+ (n 70) or Ab (n 205) using Pittsburgh Compound B (PET) imaging. Participants completed letter fluency (FAS; word generation to letters F A S) and category fluency (CAT; word generation to animals, vegetables, fruits) annually (mean follow up 2.42 years) The effect of Ab status on fluency over time was examined using linear mixed models controlling for age, sex, and education. To dissociate effects related to semantic (CAT) versus retrieval processes (CAT and FAS) we repeated models predicting CAT over time, controlling for FAS and likewise for CAT controlling for FAS.  At baseline, the Ab+ group performed better on FAS compared with the Ab group but comparably on CAT. Longitudinally, the Ab+ group demonstrated greater decline on CAT compared with the Ab group (p .0011) This finding remained significant even when covarying for FAS (p .0107) Ab+ participants similarly declined compared with Ab participants on FAS (p .0112) but this effect became insignificant when covarying for CAT (p .1607) CONCLUSION These findings provide biomarker validation for the greater specificity of declines in category versus letter fluency to underlying AD pathology. Our results also suggest that changes in semantic processing occur earlier in the AD trajectory than previously hypothesized.
An Efficient Multi keyword Symmetric Searchable Encryption Scheme for Secure Data Outsourcing

Symmetric searchable encryption (SSE) schemes allow a data owner to encrypt its data in such a way that it could be searched in encrypted form. When searching over encrypted data the retrieved data, search query, and search query outcome everything must be protected. A series of SSE schemes have been proposed in the past decade. In this paper, we are going to propose our an efficient multi keyword symmetric searchable encryption scheme for secure data outsourcing and evaluate the performance of our proposed scheme on a real data set.
Food grade microemulsion systems: canola oil/lecithin:n propanol/water.
Venue: Food chemistry

In this study, the capability of a natural surfactant, lecithin, and the influence of ionic strength, pH, and temperature on some properties of a food grade microemulsion system were evaluated. For this purpose, the pseudoternary phase diagrams of canola oil/lecithin:n propanol/water microemulsions in the presence of different salts (NaCl and CaCl2) ionic strengths, pHs, and temperatures were constructed. Our findings showed that the presence of salts slightly increased the W/O areas on the phase diagrams, whereas pH variation was not effective on the microemulsion formation. The expansion of microemulsion areas with temperature indicated the greater triglycerides solubilization capacity of lecithin based microemulsions at higher temperatures. These findings revealed the efficiency of lecithin based microemulsion system for solubilization of triglycerides which can potentially be used for extraction of edible vegetable oils particularly canola oil.
Measuring Size, Size Distribution, and Polydispersity of Water in Oil Microemulsion Droplets using Fluorescence Correlation Spectroscopy: Comparison to Dynamic Light Scattering.
Venue: The journal of physical chemistry. B

Water in oil microemulsion droplets (MEDs) are thermodynamically stable supramolecular structures formed in a mixture of water and oil, stabilized by surfactant layer. Here we use fluorescence correlation spectroscopy (FCS) to measure the diffusion, and the size, size distribution, and polydispersity of MEDs prepared in ternary mixtures of water/oil/sodium bis(2 ethylhexyl) sulfosuccinate (AOT) in heptane, isooctane, and nonane at (near) single droplet level. We compare FCS data directly to dynamic light scattering (DLS) data, which shows that the optical matching point (OMP) conditions of MEDs in different oils (where excess optical polarizability of droplets vanish) severely influence DLS data, while FCS extracts the accurate size, size distribution, and polydispersity of AOT MEDs in all three oils. This suggests that extreme precaution must be taken in acquiring and explaining DLS data of MEDs in solution. FCS data show nearly identical W0 dependent (peak) size variations of AOT MEDs in all three oils, though a subtle increase in (average) polydispersity of droplets is observed with increase in carbon chain length of oils. Establishing the accuracy of FCS data for AOT MEDs, we further apply FCS to measure the size parameters of MEDs prepared in a quaternary mixture of water/oil/cetyltrimethylammonium bromide (CTAB)/1 butanol in hexane, heptane, and isooctane. Unlike AOT MEDs, FCS data show substantial effect of added cosurfactant (1 butanol) and external oil on size, size distribution and polydispersity of quaternary CTAB MEDs. Analysis of size distributions reveals large variation of polydispersity which possibly indicates the existence of larger shape heterogeneity, together with size heterogeneity, of CTAB MEDs compared to AOT MEDs in solution.
Preparation of starch nanoparticles in water in oil microemulsion system and their drug delivery properties.
Venue: Carbohydrate polymers

In this research, 1 hexadecyl 3 methylimidazolium bromide C16mimBr/butan 1 ol/cyclohexane/water ionic liquid microemulsion was prepared. The effects of n alkyl alcohols, alkanes, water content and temperature on the properties of microemulsion were studied by dilution experiment. The microregion of microemulsion was identified by pseudo ternary phase diagram and conductivity measurement. Then starch nanoparticles were prepared by water in oil (W/O) microemulsion cross linking methods with C16mimBr as surfactant. Starch nanoparticles with a mean diameter of 94.3nm and narrow size distribution (SD=3.3) were confirmed by dynamic light scattering (DLS) Scanning electron microscope (SEM) data revealed that starch nanoparticles were spherical granules with the size about 60nm. Moreover the results of Fourier transform infrared spectroscopy (FTIR) and X ray diffraction (XRD) demonstrated the formation of cross linking bonds in starch molecules. Finally, the drug loading and releasing properties of starch nanoparticles were investigated with methylene blue (MB) as drug model. This work may provide an efficient pathway to synthesis starch nanoparticles.
Multiple approaches to control and assess the size of Pd nanoparticles synthesized via water in oil microemulsion

Pd nanoparticles (NPs) were synthesized by a water in oil (w/o) microemulsion method using the water/AOT/isooctane system. N 2 H 4 and NaBH 4 were used as reducing agents and water to surfactant ratios (w 0 between 3 and 7 were considered. Multiple approaches, considering the physical operations and the synthesis conditions, were followed to assess and control the size of Pd NPs. Thus, the effect of the reduction time, the evaporation temperature and the purification with solvents in the formation of NPs was studied. Smaller NPs and narrower size distributions were obtained by TEM when the NPs were washed with methanol, indicating that a purification stage is needed to assess the influence of the synthesis conditions. Likewise, lower agglomeration and higher hydrophilicity of NPs was observed after washing with methanol. After a reduction time of 10 min, the evaporation of the microemulsion at 298 K led to larger NPs (7.1 9.7 nm) than at 368 K (6.2 7.7 nm) For a reduction time of 60 min, NPs with mean size between 9.1 and 11.7 nm were obtained, and the evaporation temperature only showed influence at high w 0 values. In general, smaller NPs and narrower size distributions were observed in the synthesis carried out with low w 0 values. The type of reducing agent also showed a relevant influence in Pd NPs size.
Morphological and Phylogenetic Analyses of Three Phytopythium Species (Peronosporales, Oomycota) from Brazil
Venue: Cryptogamie, Mycologie

We analyzed the morphology and phylogenetic placement of six isolates of Phytopythium belonging to P. helicoides, P. palingenes and P. vexans that were isolated from water bodies and substrates used for hydroponically grown crops. The molecular data are from the partial large subunit and the complete internal transcribed regions of the ribosomal DNA. These three species are characterized by the presence of ovoid to globose zoosporangia with papillae, internal proliferation as in Phytophthora and mode of zoospore discharge as in Pythium. All isolates showed high morphological and phylogenetic similarity with members of the Clades II and III of Phytopythium. In this paper, Phytopythium palingenes is included for the first time in phylogenetic analyses and our ITS and LSU phylogenies indicated that Aquaperonospora taiwanensis is a synonym of Phytopythium helicoides.
IV Spanish Consensus Conference on Helicobacter pylori infection treatment.
Venue: Gastroenterologia y hepatologia

Helicobacter pylori approximately infect 50% of Spanish population and causes chronic gastritis, peptic ulcer and gastric cancer. Until now, three consensus meetings on H.pylori infection had been performed in Spain (the last in 2012) The changes in the treatment schemes, and the increasing available evidence, have justified organizing the IVSpanish Consensus Conference (March 2016) focused on the treatment of this infection. Nineteen experts participated, who performed a systematic review of the scientific evidence and developed a series of recommendation that were subjected to an anonymous Delphi process of iterative voting. Scientific evidence and the strength of the recommendation were classified using GRADE guidelines. As starting point, this consensus increased the minimum acceptable efficacy of recommended treatments that should reach, or preferably surpass, the 90% cure rate when prescribed empirically. Therefore, only quadruple therapies (with or without bismuth) and generally lasting 14 days, are recommended both for first and second line treatments. Non bismuth quadruple concomitant regimen, including a proton pump inhibitor, clarithromycin, amoxicillin and metronidazole, is recommended as first line. In the present consensus, other first line alternatives and rescue treatments are also reviewed and recommended.
IV Spanish Consensus Conference on Helicobacter pylori infection treatment.

Helicobacter pylori approximately infect 50% of Spanish population and causes chronic gastritis, peptic ulcer and gastric cancer. Until now, three consensus meetings on H.pylori infection had been performed in Spain (the last in 2012) The changes in the treatment schemes, and the increasing available evidence, have justified organizing the IVSpanish Consensus Conference (March 2016) focused on the treatment of this infection. Nineteen experts participated, who performed a systematic review of the scientific evidence and developed a series of recommendation that were subjected to an anonymous Delphi process of iterative voting. Scientific evidence and the strength of the recommendation were classified using GRADE guidelines. As starting point, this consensus increased the minimum acceptable efficacy of recommended treatments that should reach, or preferably surpass, the 90% cure rate when prescribed empirically. Therefore, only quadruple therapies (with or without bismuth) and generally lasting 14 days, are recommended both for first and second line treatments. Non bismuth quadruple concomitant regimen, including a proton pump inhibitor, clarithromycin, amoxicillin and metronidazole, is recommended as first line. In the present consensus, other first line alternatives and rescue treatments are also reviewed and recommended.
Metabarcoding of marine nematodes evaluation of similarity scores used in alignment based taxonomy assignment approach
Venue: Biodiversity data journal

The diversity of organisms is being commonly accessed using metabarcoding of environmental samples. Reliable identification of barcodes is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task, including alignment based approach that uses Basic Local Alignment Search Tool (BLAST) algorithm. This publication evaluates the variability of 5' end of 18S rRNA barcoding region as expressed by similarity scores (alignment score and identity score) produced by BLAST, and its impact on barcode identification to family level taxonomic categories. New information In alignment based taxonomy assignment approach, reliable identification of anonymous OTUs to supraspecific taxa depends on the correct application of similarity thresholds. Since various taxa show different level of genetic variation, practical application of alignment based approach requires the determination and use of taxon specific similarity thresholds.
Object Tracking Using Minimum Spanning Tree One Class Classifier
Venue: 2016 9th International Symposium on Computational Intelligence and Design (ISCID)

In the traditional discriminative object tracking methods, similar to the target, background is often taken mistakenly as a single negative class to train two class classifiers despite including various objects with different distributions. A novel method based on one class classifier is proposed for object tracking. It takes background as a collection of all other classes except the target. Object tracking is viewed as a one class classification problem correspondingly. Firstly, the tracking results in the recent few frames are collected as the target training samples. Secondly, a k nearest graph is built based on these training samples and the most representative samples are selected on the basis of their own local average degrees to construct a minimum spanning tree. Then an one class classifier based on the minimum spanning tree is trained to model the target. Lastly the similarity scores of candidates drawn from a particle filter are evaluated by the trained one class classifier and the one with highest score is taken as the tracking result in current frame and used to update the training sample set and the one class classifier. Empirical results on challenging video sequences demonstrate the superior performance of our method in robustness and accuracy to state of the art methods.
A primal dual approximation algorithm for a two depot heterogeneous traveling salesman problem
Venue: Optim. Lett.

Surveillance applications require a collection of heterogeneous vehicles to visit a set of targets. We consider a fundamental routing problem that arises in these applications involving two vehicles. Specifically, we consider a routing problem where there are two heterogeneous vehicles that start from distinct initial locations and a set of targets. The objective is to find a tour for each vehicle such that each of the targets is visited at least once by a vehicle and the sum of the distances traveled by the vehicles is minimal. We consider an important special case of this routing problem where the travel costs satisfy the triangle inequality and the following monotonicity property: the first vehicle's cost of traveling between any two targets is at most equal to the second vehicle's cost of traveling between the same targets. We present a primal dual algorithm for this case that provides an approximation ratio of 2.
Feasibility Study of Aseptic Homogenization: Affecting Homogenization Steps on Quality of Sterilized Coconut Milk

Coconut milk is one of the most important protein rich food sources available today. Separation of an emulsion into an aqueous phase and cream phase is commonly occurred and this leads an unacceptably physical defect of either fresh or processed coconut milk. Since homogenization steps are known to affect the stability of coconut milk. This work was aimed to study the effect of homogenization steps on quality of coconut milk. The samples were subject to high speed homogenization in the range of 5000 15000 rpm under sterilize temperatures at 120 140 degC for 15 min. The result showed that emulsion stability increase with increasing speed of homogenization. The lower fat particles were generated and easy to disperse in continuous phase lead to high stability. On the other hand, the stability of coconut milk decreased, fat globule increased, L value decreased and b value increased when the high sterilization temperature was applied. Homogenization after heating led to higher stability than homogenization before heating due to the reduced particle size of coconut milk after aggregation during sterilization process. The results implied that homogenization after sterilization process might play an important role on the quality of the sterilized coconut milk.
High power high safety battery with electrospun Li3V2(PO4)3 cathode and Li4Ti5O12 anode with 95% energy efficiency

Li 3 V 2 (PO 4 3 (LVP) and Li 4 Ti 5 O 12 (LTO) were chosen as the cathode and the anode to build a full battery owing to their robust structures. Electrospinning method was adopted to control the electrode materials with the expected microstructures nanowires that shorten solid state diffusion pathway and enhance the surface area for improving their electrochemical performances. LVP cathode and LTO anode can deliver reversible specific capacities of 108 and 149 mAh/g at a rate of 5 C, respectively. No appreciable degradation can be perceived in both electrodes over 500 cycles. In addition, the relatively high voltage of LTO anode ensures the safe rapid charge and discharge (no dendrite growth) and the minimal or no initial loss of lithium ions as there is no formation of SEI layer. A full battery with LVP cathode and LTO anode delivers a maximum power density of 12,046 W/kg, reaching the strength of supercapacitors, while offers a high energy density of 90 Wh/kg at a power density of 1,350 W/kg with a charging or discharge time of 7 min. This battery demonstrates an energy storage efficiency close to 95% at a rate of 2 C and maintains 90% efficiency at 20 C.
subgraph2vec: Learning Distributed Representations of Rooted Sub graphs from Large Graphs
Venue: ArXiv

In this paper, we present subgraph2vec, a novel approach for learning latent representations of rooted subgraphs from large graphs inspired by recent advancements in Deep Learning and Graph Kernels. These latent representations encode semantic substructure dependencies in a continuous vector space, which is easily exploited by statistical models for tasks such as graph classification, clustering, link prediction and community detection. subgraph2vec leverages on local information obtained from neighbourhoods of nodes to learn their latent representations in an unsupervised fashion. We demonstrate that subgraph vectors learnt by our approach could be used in conjunction with classifiers such as CNNs, SVMs and relational data clustering algorithms to achieve significantly superior accuracies. Also, we show that the subgraph vectors could be used for building a deep learning variant of Weisfeiler Lehman graph kernel. Our experiments on several benchmark and large scale real world datasets reveal that subgraph2vec achieves significant improvements in accuracies over existing graph kernels on both supervised and unsupervised learning tasks. Specifically, on two realworld program analysis tasks, namely, code clone and malware detection, subgraph2vec outperforms state of the art kernels by more than 17% and 4% respectively.
Learning Distributed Representations for Recommender Systems with a Network Embedding Approach
Venue: AIRS

In this paper, we present a novel perspective to address recommendation tasks by utilizing the network representation learning techniques. Our idea is based on the observation that the input of typical recommendation tasks can be formulated as graphs. Thus, we propose to use the k partite adoption graph to characterize various kinds of information in recommendation tasks. Once the historical adoption records have been transformed into a graph, we can apply the network embedding approach to learn vertex embeddings on the k partite adoption network. Embeddings for different kinds of information are projected into the same latent space, where we can easily measure the relatedness between multiple vertices on the graph using some similarity measurements. In this way, the recommendation task has been casted into a similarity evaluation process using embedding vectors. The proposed approach is both general and scalable. To evaluate the effectiveness of the proposed approach, we construct extensive experiments on two different recommendation tasks using real world datasets. The experimental results have shown the superiority of our approach. To the best of our knowledge, it is the first time that a network representation learning approach has been applied to recommendation tasks.
A Broadband Almost Digital RF Transmitter With an Efficient Power Amplifier
Venue: IEEE Transactions on Microwave Theory and Techniques

A new architecture of an almost digital RF transmitter is proposed. It consists of easy to have functional modules. Among the modules, a broadband Doherty amplifier is focused through a modified design approach. A proof of concept transmitter is built and measured. It demonstrates quite comparable performances: more than 40% of power amplifier efficiency, adjacent channel leakage ratios between 26 and 37 dB, and average 2.6% of error vector magnitude over a frequency band from 0.7 to 1.1 GHz, which corresponds to a fractional bandwidth of 44% when it is driven by a signal with 5.6 dB of peak to average power ratio.