Factorizing LambdaMART for cold start recommendations

Recommendation systems often rely on point-wise loss metrics such as the mean squared error. However, in real recommendation settings only few items are presented to a user. This observation has recently encouraged the use of rank-based metrics. LambdaMART is the state-of-the-art algorithm in learning to rank which relies on such a metric. Despite its success it does not have a principled regularization mechanism relying in empirical approaches to control model complexity leaving it thus prone to overfitting. Motivated by the fact that very often the users' and items' descriptions as well as the preference behavior can be well summarized by a small number of hidden factors, we propose a novel algorithm, LambdaMART Matrix Factorization (LambdaMART-MF), that learns a low rank latent representation of users and items using gradient boosted trees. The algorithm factorizes lambdaMART by defining relevance scores as the inner product of the learned representations of the users and items. The low rank is essentially a model complexity controller; on top of it we propose additional regularizers to constraint the learned latent representations that reflect the user and item manifolds as these are defined by their original feature based descriptors and the preference behavior. Finally we also propose to use a weighted variant of NDCG to reduce the penalty for similar items with large rating discrepancy. We experiment on two very different recommendation datasets, meta-mining and movies-users, and evaluate the performance of LambdaMART-MF, with and without regularization, in the cold start setting as well as in the simpler matrix completion setting. In both cases it outperforms in a significant manner current state of the art algorithms

Enabling Thin and Flexible Solid-State Composite Electrolytes by the Scalable Solution Process

All solid-state batteries (ASSBs) have the potential to deliver higher energy densities, wider operating temperature range, and improved safety compared with today's liquid-electrolyte-based batteries. However, of the various solid-state electrolyte (SSE) classes - polymers, sulfides, or oxides - none alone can deliver the combined properties of ionic conductivity, mechanical, and chemical stability needed to address scalability and commercialization challenges. While promising strategies to overcome these include the use of polymer/oxide or sulfide composites, there is still a lack of fundamental understanding between different SSE-polymer-solvent systems and its selection criteria. Here, we isolate various SSE-polymer-solvent systems and study their molecular level interactions by combining various characterization tools. With these findings, we introduce a suitable Li7P3S11SSE-SEBS polymer-xylene solvent combination that significantly reduces SSE thickness (∼50 μm). The SSE-polymer composite displays high room temperature conductivity (0.7 mS cm-1) and good stability with lithium metal by plating and stripping over 2000 h at 1.1 mAh cm-2. This study suggests the importance of understanding fundamental SSE-polymer-solvent interactions and provides a design strategy for scalable production of ASSBs

An interdimensional correlation framework for real-time estimation of six degree of freedom target motion using a single x-ray imager during radiotherapy

© 2017 Institute of Physics and Engineering in Medicine. Increasing evidence suggests that intrafraction tumour motion monitoring needs to include both 3D translations and 3D rotations. Presently, methods to estimate the rotation motion require the 3D translation of the target to be known first. However, ideally, translation and rotation should be estimated concurrently. We present the first method to directly estimate six-degree-of-freedom (6DoF) motion from the target's projection on a single rotating x-ray imager in real-time. This novel method is based on the linear correlations between the superior-inferior translations and the motion in the other five degrees-of-freedom. The accuracy of the method was evaluated in silico with 81 liver tumour motion traces from 19 patients with three implanted markers. The ground-truth motion was estimated using the current gold standard method where each marker's 3D position was first estimated using a Gaussian probability method, and the 6DoF motion was then estimated from the 3D positions using an iterative method. The 3D position of each marker was projected onto a gantry-mounted imager with an imaging rate of 11 Hz. After an initial 110° gantry rotation (200 images), a correlation model between the superior-inferior translations and the five other DoFs was built using a least square method. The correlation model was then updated after each subsequent frame to estimate 6DoF motion in real-time. The proposed algorithm had an accuracy (±precision) of -0.03 ± 0.32 mm, -0.01 ± 0.13 mm and 0.03 ± 0.52 mm for translations in the left-right (LR), superior-inferior (SI) and anterior-posterior (AP) directions respectively; and, 0.07 ± 1.18°, 0.07 ± 1.00° and 0.06 ± 1.32° for rotations around the LR, SI and AP axes respectively on the dataset. The first method to directly estimate real-time 6DoF target motion from segmented marker positions on a 2D imager was devised. The algorithm was evaluated using 81 motion traces from 19 liver patients and was found to have sub-mm and sub-degree accuracy

Dry semi-continuous anaerobic digestion of food waste in the mesophilic and thermophilic modes: New aspects of sustainable management and energy recovery in South Korea

© 2016 Elsevier Ltd In this study, parallel, bench-scale, mesophilic and thermophilic, dry, semi-continuous anaerobic digestion (DScAD) of Korea food waste (FW, containing 22% total solids (TS) and 20% volatile solids (VS)) was investigated thoroughly under varying operational conditions, including hydraulic retention times (HRTs) and organic loading rates (OLRs). The aim was to evaluate the start-up, stability, overall removal efficiency, and inhibitory effects of toxic compounds on process performance over a long-term operation lasting 100 days. The results from both digesters indicate that the simultaneous reduction of VS and the production of gas improved as the HRT decreased or the OLR increased. The highest average rates of VS reduction (79.67%) and biogas production (162.14 m3biogas/ton of FW, 61.89% CH4), at an OLR of 8.62 ± 0.34 kg VS/m3day (25 days of HRT), were achieved under thermophilic DScAD. In addition, the average rates of reduction of VS and the production of biogas in thermophilic DScAD were higher by 6.88% and 16.4%, respectively, than were those in mesophilic DScAD. The inhibitory effects of ammonia, H2S, and volatile fatty acids (VFAs) on methane production was not clear from either of the digesters, although, apparently, their concentrations did fluctuate. This fluctuation could be attributed to the self-adaptation of the microbial well. However, digestion that was more stable and faster was observed under thermophilic conditions compared with that under mesophilic conditions. Based on our results, the optimum operational parameters to improve FW treatment and achieve higher energy yields could be determined, expanding the application of DScAD in treating organic wastes

Quantifying the accuracy and precision of a novel real-time 6 degree-of-freedom kilovoltage intrafraction monitoring (KIM) target tracking system.

Target rotation can considerably impact the delivered radiotherapy dose depending on the tumour shape. More accurate tumour pose during radiotherapy treatment can be acquired through tracking in 6 degrees-of-freedom (6 DoF) rather than in translation only. A novel real-time 6 DoF kilovoltage intrafraction monitoring (KIM) target tracking system has recently been developed. In this study, we experimentally evaluated the accuracy and precision of the 6 DoF KIM implementation. Real-time 6 DoF KIM motion measurements were compared against the ground truth motion retrospectively derived from kV/MV triangulation for a range of lung and prostate tumour motion trajectories as well as for various static poses using a phantom. The accuracy and precision of 6 DoF KIM were calculated as the mean and standard deviation of the differences between KIM and kV/MV triangulation for each DoF, respectively. We found that KIM is able to provide 6 DoF motion with sub-degree and sub-millimetre accuracy and precision for a range of realistic tumour motion

Grain Boundary Induced Bias Instability in Soluble Acene-Based Thin-Film Transistors

Since the grain boundaries (GBs) within the semiconductor layer of organic field-effect transistors (OFETs) have a strong influence on device performance, a substantial number of studies have been devoted to controlling the crystallization characteristics of organic semiconductors. We studied the intrinsic effects of GBs within 5,11-bis(triethylsilylethynyl) anthradithiophene (TES-ADT) thin films on the electrical properties of OFETs. The GB density was easily changed by controlling nulceation event in TES-ADT thin films. When the mixing time was increased, the number of aggregates in asspun TES-ADT thin films were increased and subsequent exposure of the films to 1,2-dichloroethane vapor led to a significant increase in the number of nuleation sites, thereby increasing the GB density of TES-ADT spherulites. The density of GBs strongly influences the angular spread and crystallographic orientation of TES-ADT spherulites. Accordingly, the FETs with higher GB densities showed much poorer electrical characteristics than devices with lower GB density. Especially, GBs provide charge trapping sites which are responsible for bias-stress driven electrical instability. Dielectric surface treatment with a polystyrene brush layer clarified the GB-induced charge trapping by reducing charge trapping at the semiconductor-dielectric interface. Our study provides an understanding on GB induced bias instability for the development of high performance OFETs.1172Ysciescopu

Microfluidic impedance biosensors for monitoring a single and multiple cancer cells in anticancer drug treatments

In this work, we present a novel microfluidic impedance biosensor chip for trapping both a single and multiple cancer cells and monitoring their response to the anti-cancer drug treatment. By designing different sizes of working microelectrodes together with the V-shaped cell capture structures, a single or multiple cells are trapped on the microelectrodes surfaces. In addition, by utilizing the passive pumping method, cells can be trapped and positioned inside the microchannels without the need of using the outer micro pump or syringe. The impedance change induced by the response of cells to the anticancer drug Cisplatin treatment was successfully recorded. The proposed biosensor chip has a great potential for applications in cancer cell research, drug screening, and quantification of cancer cells from various tumor stages. The results of this study open potential research collaborations about development of cost-effective devices and lab-on-chips for early disease detection, studies of cancerous cells and their response to anti-cancer drugs to optimize cancer treatments, characterisation of mechanical properties of cells, new drug delivery mechanisms, and micro and nano manufacturing

Thermophilic anaerobic digestion of model organic wastes: Evaluation of biomethane production and multiple kinetic models analysis

© 2019 Elsevier Ltd The main aim of this work was to test various organic wastes, i.e. from a livestock farm, a cattle slaughterhouse and agricultural waste streams, for its ability to produce methane under thermophilic anaerobic digestion (AD) conditions. The stability of the digestion, potential biomethane production and biomethane production rate for each waste were assessed. The highest methane yield (110.83 mL CH4/g VSadded day) was found in the AD of crushed animal carcasses on day 4. The experimental results were analyzed using four kinetic models and it was observed that the Cone model described the biomethane yield as well as the methane production rate of each substrate. The results from this study showed the good potential of model organic wastes to produce biomethane

Hospital admissions for vitamin D related conditions and subsequent immune-mediated disease: record-linkage studies

PMCID: PMC3729414The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1741-7015/11/171. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited