Joint Deep Modeling of Users and Items Using Reviews for Recommendation

A large amount of information exists in reviews written by users. This source of information has been ignored by most of the current recommender systems while it can potentially alleviate the sparsity problem and improve the quality of recommendations. In this paper, we present a deep model to learn item properties and user behaviors jointly from review text. The proposed model, named Deep Cooperative Neural Networks (DeepCoNN), consists of two parallel neural networks coupled in the last layers. One of the networks focuses on learning user behaviors exploiting reviews written by the user, and the other one learns item properties from the reviews written for the item. A shared layer is introduced on the top to couple these two networks together. The shared layer enables latent factors learned for users and items to interact with each other in a manner similar to factorization machine techniques. Experimental results demonstrate that DeepCoNN significantly outperforms all baseline recommender systems on a variety of datasets.Comment: WSDM 201

Rapid, efficient, and economical synthesis of PET tracers in a droplet microreactor: application to O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET).

BackgroundConventional scale production of small batches of PET tracers (e.g. for preclinical imaging) is an inefficient use of resources. Using O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET), we demonstrate that simple microvolume radiosynthesis techniques can improve the efficiency of production by consuming tiny amounts of precursor, and maintaining high molar activity of the tracers even with low starting activity.ProceduresThe synthesis was carried out in microvolume droplets manipulated on a disposable patterned silicon "chip" affixed to a heater. A droplet of [18F]fluoride containing TBAHCO3 was first deposited onto a chip and dried at 100 °C. Subsequently, a droplet containing 60 nmol of precursor was added to the chip and the fluorination reaction was performed at 90 °C for 5 min. Removal of protecting groups was accomplished with a droplet of HCl heated at 90 °C for 3 min. Finally, the crude product was collected in a methanol-water mixture, purified via analytical-scale radio-HPLC and formulated in saline. As a demonstration, using [18F]FET produced on the chip, we prepared aliquots with different molar activities to explore the impact on preclinical PET imaging of tumor-bearing mice.ResultsThe microdroplet synthesis exhibited an overall decay-corrected radiochemical yield of 55 ± 7% (n = 4) after purification and formulation. When automated, the synthesis could be completed in 35 min. Starting with < 370 MBq of activity, ~ 150 MBq of [18F]FET could be produced, sufficient for multiple in vivo experiments, with high molar activities (48-119 GBq/μmol). The demonstration imaging study revealed the uptake of [18F]FET in subcutaneous tumors, but no significant differences in tumor uptake as a result of molar activity differences (ranging 0.37-48 GBq/μmol) were observed.ConclusionsA microdroplet synthesis of [18F]FET was developed demonstrating low reagent consumption, high yield, and high molar activity. The approach can be expanded to tracers other than [18F]FET, and adapted to produce higher quantities of the tracer sufficient for clinical PET imaging

Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data

Many systems are partially stochastic in nature. We have derived data driven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet activities. For contrast, we include a related data-driven statistical inferencing approach that detects and localizes radiation sources.Comment: Accepted by 2017 International Symposium on Sensor Networks, Systems and Securit

Variation at APOE and STH loci and Alzheimer's disease

BACKGROUND: The apolipoprotein E (APOE) and tau proteins play important roles in the pathological development of Alzheimer's disease (AD). Many studies have shown an association between the APOE gene and AD. Association between AD and the newly discovered saitohin (STH) gene, nested within the intron of the tau gene, has been reported. The present study aimed to elucidate the association between APOE and AD, and between STH and AD in our sample. METHODS: The functional polymorphisms, rs429358 and rs7412, in the APOE gene (which together define the ε2, ε3, and ε4 alleles), and the Q7R SNP in the STH gene, were genotyped in 369 patients with AD and 289 healthy European-Americans. The associations between these two genes and AD were analyzed in a case-control design. RESULTS: Consistent with previously reported results, the frequencies of the APOE ε4 allele, ε4/ε4 genotype and ε3/ε4 genotype were significantly higher in AD cases than controls; the ε4/ε4 genotype frequency was significantly higher in early-onset AD (EOAD) than late-onset AD (LOAD); the frequencies of the ε2 allele, ε3 allele, ε3/ε3 genotype and ε2/ε3 genotype were significantly lower in AD cases than controls. Positive likelihood ratios (LRs(+)) of APOE alleles and genotypes increased in a linear trend with the number of ε4 alleles and decreased in a linear trend with the number of ε2 or ε3 alleles. There was no significant difference in the STH allele and genotype frequency distributions between AD cases and controls. CONCLUSION: This study confirmed that the ε4 allele is a dose-response risk factor for AD and the ε4/ε4 genotype was associated with a significantly earlier age of onset. Moreover, we found that the ε2 allele was a dose-response protective factor for AD and the ε3 allele exerted a weaker dose-response protective effect for risk of AD compared with ε2. In a clinical setting, APOE genotyping could offer additional biological evidence of whether a subject may develop AD, but it is not robust enough to serve as an independent screening or predictive test in the diagnosis of AD. STH variation was not significantly associated with AD in our sample

Heat capacity studies of Ce and Rh site substitution in the heavy fermion antiferromagnet CeRhIn_5;: Short-range magnetic interactions and non-Fermi-liquid behavior

In heavy fermion materials superconductivity tends to appear when long range magnetic order is suppressed by chemical doping or applying pressure. Here we report heat capacity measurements on diluted alloyes of the heavy fermion superconductor CeRhIn_5;. Heat capacity measurements have been performed on CeRh_{1-y}Ir_{y}In_5; (y <= 0.10) and Ce_{1-x}La_{x}Rh_{1-y}Ir_{y}In_5; (x <= 0.50) in applied fields up to 90 kOe to study the affect of doping and magnetic field on the magnetic ground state. The magnetic phase diagram of CeRh_{0.9}Ir_{0.1}In_5; is consistent with the magnetic structure of CeRhIn_5; being unchanged by Ir doping. Doping of Ir in small concentrations is shown to slightly increase the antiferromagnetic transition temperature T_{N} (T_{N}=3.8 K in the undoped sample). La doping which causes disorder on the Ce sublattice is shown to lower T_{N} with no long range order observed above 0.34 K for Ce_{0.50}La_{0.50}RhIn_5;. Measurements on Ce_{0.50}La_{0.50}RhIn_5; show a coexistence of short range magnetic order and non-Fermi-liquid behavior. This dual nature of the Ce 4f-electrons is very similar to the observed results on CeRhIn_5; when long range magnetic order is suppressed at high pressure.Comment: 8 pages, 9 figure

Thermal fission rate around super-normal phase transition

Using Langer's $Im F$ method, we discuss the temperature dependence of nuclear fission width in the presence of dissipative environments. We introduce a low cut-off frequency to the spectral density of the environmental oscillators in order to mimic the pairing gap. It is shown that the decay width rapidly decreases at the critical temperature, where the phase transition from super to normal fluids takes place. Relation to the recently observed threshold for the dissipative fission is discussed.Comment: 12 pages, Latex, Submitted to Physical Review C for publication, 3 Postscript figures are available by request from [email protected]

The temperature and chronology of heavy-element synthesis in low-mass stars

Roughly half of the heavy elements (atomic mass greater than that of iron) are believed to be synthesized in the late evolutionary stages of stars with masses between 0.8 and 8 solar masses. Deep inside the star, nuclei (mainly iron) capture neutrons and progressively build up (through the slow-neutron-capture process, or s-process) heavier elements that are subsequently brought to the stellar surface by convection. Two neutron sources, activated at distinct temperatures, have been proposed: 13C and 22Ne, each releasing one neutron per alpha-particle (4He) captured. To explain the measured stellar abundances, stellar evolution models invoking the 13C neutron source (which operates at temperatures of about one hundred million kelvin) are favoured. Isotopic ratios in primitive meteorites, however, reflecting nucleosynthesis in the previous generations of stars that contributed material to the Solar System, point to higher temperatures (more than three hundred million kelvin), requiring at least a late activation of 22Ne. Here we report a determination of the s-process temperature directly in evolved low-mass giant stars, using zirconium and niobium abundances, independently of stellar evolution models. The derived temperature supports 13C as the s-process neutron source. The radioactive pair 93Zr-93Nb used to estimate the s-process temperature also provides, together with the pair 99Tc-99Ru, chronometric information on the time elapsed since the start of the s-process, which we determine to be one million to three million years.Comment: 30 pages, 10 figure

Phase synchronization of autonomous AC grid system with passivity-based control

This paper discusses a ring‐coupled buck‐type inverter system to harness energy from direct current (DC) sources of electricity. The DC‐DC buck converter circuit is modified with an H‐bridge to convert the DC input voltage to a usable alternating current (AC) output voltage. Passivity‐based control (PBC) with port‐controlled Hamiltonian modelling (PCHM) is a method where the system is controlled by considering not only the energy properties of the system but also the inherent physical structure. PBC is applied to achieve stabilization of the AC output voltage to a desired amplitude and frequency. Unsynchronized output voltages in terms of phase angle or frequency can cause detrimental effects on the system. Phase‐locked loop (PLL) is employed in the ring structure to maintain synchronization of the AC output voltage of all inverter units in the ring‐coupled system

Magnetic control of large room-temperature polarization

Numerous authors have referred to room-temperature magnetic switching of large electric polarizations as The Holy Grail of magnetoelectricity.We report this long-sought effect using a new physical process of coupling between magnetic and ferroelectric relaxor nano-regions. Here we report magnetic switching between the normal ferroelectric state and the ferroelectric relaxor state. This gives both a new room-temperature, single-phase, multiferroic magnetoelectric, PbZr0.46Ti0.34Fe0.13W0.07O3, with polarization, loss (<4%), and resistivity (typically 108 -109 ohm.cm) equal to or superior to BiFeO3, and also a new and very large magnetoelectric effect: switching not from +Pr to negative Pr with applied H, but from Pr to zero with applied H of less than a Tesla. This switching of the polarization occurs not because of a conventional magnetically induced phase transition, but because of dynamic effects: Increasing H lengthens the relaxation time by x500 from 100 ?s, and it couples strongly the polarization relaxation and spin relaxations. The diverging polarization relaxation time accurately fits a modified Vogel-Fulcher Equation in which the freezing temperature Tf is replaced by a critical freezing field Hf that is 0.92 positive/negative 0.07 Tesla. This field dependence and the critical field Hc are derived analytically from the spherical random bond random field (SRBRF) model with no adjustable parameters and an E2H2 coupling. This device permits 3-state logic (+Pr,0,negative Pr) and a condenser with >5000% magnetic field change in its capacitance.Comment: 20 pages, 5 figure