LLukas22/scidocs huggingface dataset:
Tetraphenylphosphonium as a novel molecular probe for imaging tumors.

UNLABELLED
Mitochondrial membrane potential (DeltaPsim)-dependent enhanced uptake of phosphonium salts, including (3)H-tetraphenylphosphonium ((3)H-TPP), in tumor cells, suggests the potential use of phosphonium salts as tracers for tumor imaging. In this study, we characterize the tumor accumulation of (3)H-TPP and compare it with (18)F-FDG in cell culture and in xenograft, metastatic, and inflammation models in living animals.


METHODS
(3)H-TPP and (3)H-FDG accumulation was compared in cell culture with a variety of cell lines in different glucose concentrations. Normal biodistribution and tumor uptake were assessed using nude mice with or without subcutaneous xenograft tumors (C6). To compare the accumulation of (3)H-TPP and (18)F-FDG in a metastatic tumor, severe combined immunodeficiency mice were tail-vein injected with human melanoma cell lines (A375-FL). To characterize the accumulation of (3)H-TPP and (18)F-FDG in inflammation, an inflammatory reaction was induced by subcutaneous injection of Complete Freund's Adjuvant in the left hind paw of Sprague-Dawley rat.


RESULTS
The DeltaPsim data from a separate study and the current (3)H-TPP uptake data showed good correlation (r(2) = 0.82, P < 0.05). (3)H-TPP accumulation was significantly greater than that of (3)H-FDG for glucose >/=100 mg/dL. The biodistribution study of (3)H-TPP showed low uptake in most tissues but high accumulation in the heart and kidneys. (3)H-TPP accumulation in xenograft or metastatic tumors was comparable with that of (18)F-FDG, whereas (3)H-TPP accumulation in inflammatory tissues was markedly lower than that of (18)F-FDG.


CONCLUSION
The sensitive tumor accumulation of (3)H-TPP with less propensity for inflammatory regions warrants further investigation of radiolabeled phosphonium analogs for tumor imaging in living subjects.
ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications

Existing data storage systems offer a wide range of functionalities to accommodate an equally diverse range of applications. However, new classes of applications have emerged, e.g., blockchain and collaborative analytics, featuring data versioning, fork semantics, tamper-evidence or any combination thereof. They present new opportunities for storage systems to efficiently support such applications by embedding the above requirements into the storage. In this paper, we present ForkBase, a storage engine designed for blockchain and forkable applications. By integrating core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort. The storage manages multiversion data and supports two variants of fork semantics which enable different fork worklflows. ForkBase is fast and space efficient, due to a novel index class that supports efficient queries as well as effective detection of duplicate content across data objects, branches and versions. We demonstrate ForkBase’s performance using three applications: a blockchain platform, a wiki engine and a collaborative analytics application. We conduct extensive experimental evaluation against respective state-of-the-art solutions. The results show that ForkBase achieves superior performance while significantly lowering the development effort. PVLDB Reference Format: Sheng Wang, Tien Tuan Anh Dinh, Qian Lin, Zhongle Xie, Meihui Zhang, Qingchao Cai, Gang Chen, Beng Chin Ooi, Pingcheng Ruan. ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications. PVLDB, 11(10): 1137-1150, 2018. DOI: https://doi.org/10.14778/3231751.3231762
Fast and sensitive mapping of nanopore sequencing reads with GraphMap.

Realizing the democratic promise of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. Here we present GraphMap, a mapping algorithm designed to analyse nanopore sequencing reads, which progressively refines candidate alignments to robustly handle potentially high-error rates and a fast graph traversal to align long reads with speed and high precision (>95%). Evaluation on MinION sequencing data sets against short- and long-read mappers indicates that GraphMap increases mapping sensitivity by 10-80% and maps >95% of bases. GraphMap alignments enabled single-nucleotide variant calling on the human genome with increased sensitivity (15%) over the next best mapper, precise detection of structural variants from length 100 bp to 4 kbp, and species and strain-specific identification of pathogens using MinION reads. GraphMap is available open source under the MIT license at https://github.com/isovic/graphmap.
Learning Options in Reinforcement Learning

Temporallyextendedactions(e.g.,macroactions)have proven very usefulin speedinguplearning,ensuringrobustnessandbuilding prior knowledge into AI systems.Theoptionsframework (Precup,2000;Sutton,Precup& Singh, 1999)provides a naturalway of incorporatingsuchactionsinto reinforcement learningsystems,but leavesopentheissueof how goodoptionsmightbeidentified. In this paper , we empiricallyexplorea simpleapproachto creatingoptions. The underlyingassumptionis that the agentwill be asked to performdifferent goal-achievementtasksin anenvironmentthat is otherwisethesameover time. Our approachis basedon theintuition that“bottleneck”states,i.e. statesthatare frequentlyvisitedon systemtrajectories,couldprove to beusefulsubgoals(e.g. McGovern& Barto,2001;Iba,1989). We presentempiricalstudiesof this approachin two gridworld navigationtasks. Oneof the environmentswe exploredcontainsbottleneckstates,andthe algorithm indeedfindsthesestates,asexpected.Thesecondenvironmentis anempty gridworld with no obstacles. Althoughtheenvironmentdoesnot containbottleneckstates,our approachstill finds usefuloptions,which essentiallyallow the agentto travel aroundtheenvironmentmorequickly.
Automated unit test generation during software development: a controlled experiment and think-aloud observations

Automated unit test generation tools can produce tests that are superior to manually written ones in terms of code coverage, but are these tests helpful to developers while they are writing code? A developer would first need to know when and how to apply such a tool, and would then need to understand the resulting tests in order to provide test oracles and to diagnose and fix any faults that the tests reveal. Considering all this, does automatically generating unit tests provide any benefit over simply writing unit tests manually? We empirically investigated the effects of using an automated unit test generation tool (EvoSuite) during development. A controlled experiment with 41 students shows that using EvoSuite leads to an average branch coverage increase of +13%, and 36% less time is spent on testing compared to writing unit tests manually. However, there is no clear effect on the quality of the implementations, as it depends on how the test generation tool and the generated tests are used. In-depth analysis, using five think-aloud observations with professional programmers, confirms the necessity to increase the usability of automated unit test generation tools, to integrate them better during software development, and to educate software developers on how to best use those tools.
Quantum-Accelerated Fractal Image Compression: An Interdisciplinary Approach

Fractal image compression (FIC) is one of the most widely approved image compression approaches for its high compression ratio and quality of retrieved images. However, FIC suffers from high computational cost in searching local self-similarities in natural image. Although many papers aiming at speeding up FIC have been published, they use pre-processing tools or approximation methods. Reducing the intrinsic computational complexity of FIC is still an open problem. Since quantum mechanics based Grover's quantum search algorithm (QSA) is able to achieve square-root speedup over classical algorithms in unsorted database searching, we propose an interdisciplinary approach by using Grover's QSA to reduce the intrinsic computational complexity of FIC in this letter. In particular, both domain blocks and range blocks are represented as quantum states, then Grover's QSA is employed to search the most similar domain block for each range block under the criterion of maximizing quantum fidelity between these two kinds of quantum states. Without sacrificing compression ratio, experimental results show that the execution time of the proposed method is 100 times shorter than that of the baseline FIC. Moreover, retrieved images from our proposal are also less distorted than those from other state-of-the-art FIC approaches.
Fluorescence probing of the interfaces of solid calcium carbonate, calcium hydroxide, and calcium oxide with benzene and heptane

Abstract IR and fluorescence probing studies have been used to investigate the solid surfaces of CaO, Ca(OH) 2 , and CaCO 3 in contact with benzene. IR studies show that organic acids interact with CaO and Ca(OH) 2 to form adsorbed anions, while free acids are adsorbed to CaCO 3 . Pyrene butyric acid, PBA, binds to the surfaces and the fluorescence of the pyrene chromophore reports back on events at the surface. At least two surface sites exist for PBA on all surfaces, one at the solid-benzene interface and one away from the surface in a cleft or pore. Reactions of excited surface-adsorbed PBA with nitromethane, nitroethanol, and nitropropionic acid, which are also bound to the surfaces, fall into two classes. The first class, exhibited by CaCO 3 indicates dynamic quenching where both reactants move on the surface. The second, illustrated by Ca(OH) 2 , shows static quenching where both reactants are bound on the surface in very close proximity. The studies show marked differences between the various surfaces, which has also been observed in a more limited extent on colloids of these materials in oil.
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

Experimental analysis of the performance of a proposed method is a crucial and necessary task in an investigation. In this paper, we focus on the use of nonparametric statistical inference for analyzing the results obtained in an experiment design in the field of computational intelligence. We present a case study which involves a set of techniques in classification tasks and we study a set of nonparametric procedures useful to analyze the behavior of a method with respect to a set of algorithms, such as the framework in which a new proposal is developed. Particularly, we discuss some basic and advanced nonparametric approaches which improve the results offered by the Friedman test in some circumstances. A set of post hoc procedures for multiple comparisons is presented together with the computation of adjusted p-values. We also perform an experimental analysis for comparing their power, with the objective of detecting the advantages and disadvantages of the statistical tests described. We found that some aspects such as the number of algorithms, number of data sets and differences in performance offered by the control method are very influential in the statistical tests studied. Our final goal is to offer a complete guideline for the use of nonparametric statistical procedures for performing multiple comparisons in experimental studies. 2009 Elsevier Inc. All rights reserved.
Numerical simulation of impact tests on GFRP composite laminates

The design of advanced composite structures or components subjected to dynamic loadings requires a deep understanding of the damage and degradation mechanisms occurring within the composite material. The present paper deals with the numerical simulation of low-velocity impact tests on glass fabric/epoxy laminates through the LS-DYNA Finite Element (FE) code. Two laminates of different thickness were subjected to transverse impact at different energy levels and modeled by FE. Solid finite elements combined with orthotropic failure criteria were used to model the composite failure and stress based contact failure between plies were adopted to model the delamination mechanism. The final simulation results showed a good correlation with experimental data in terms of both forceedisplacement curves and material damage. 2011 Elsevier Ltd. All rights reserved.
The role of smartphone usage types , emotional intelligence , social stress , self-regulation , age , and gender

The present study investigates the role of process and social oriented smartphone usage, emotional intelligence, social stress, self-regulation, gender, and age in relation to habitual and addictive smartphone behavior. We conducted an online survey among 386 respondents. The results revealed that habitual smartphone use is an important contributor to addictive smartphone behavior. Process related smartphone use is a strong determinant for both developing habitual and addictive smartphone behavior. People who extensively use their smartphones for social purposes develop smartphone habits faster, which in turn might lead to addictive smartphone behavior. We did not find an influence of emotional intelligence on habitual or addictive smartphone behavior, while social stress positively influences addictive smartphone behavior, and a failure of self-regulation seems to cause a higher risk of addictive smartphone behavior. Finally, men experience less social stress than women, and use their smartphones less for social purposes. The result is that women have a higher chance in developing habitual or addictive smartphone behavior. Age negatively affects process and social usage, and social stress. There is a positive effect on self-regulation. Older people are therefore less likely to develop habitual or addictive smartphone behaviors. 2015 Elsevier Ltd. All rights reserved.
Effects of emergency department expansion on emergency department patient flow.

OBJECTIVES
Emergency department (ED) crowding is an increasing problem associated with adverse patient outcomes. ED expansion is one method advocated to reduce ED crowding. The objective of this analysis was to determine the effect of ED expansion on measures of ED crowding.


METHODS
This was a retrospective study using administrative data from two 11-month periods before and after the expansion of an ED from 33 to 53 adult beds in an academic medical center. ED volume, staffing, and hospital admission and occupancy data were obtained either from the electronic health record (EHR) or from administrative records. The primary outcome was the rate of patients who left without being treated (LWBT), and the secondary outcome was total ED boarding time for admitted patients. A multivariable robust linear regression model was used to determine whether ED expansion was associated with the outcome measures.


RESULTS
The mean (±SD) daily adult volume was 128 (±14) patients before expansion and 145 (±17) patients after. The percentage of patients who LWBT was unchanged: 9.0% before expansion versus 8.3% after expansion (difference = 0.6%, 95% confidence interval [CI] = -0.16% to 1.4%). Total ED boarding time increased from 160 to 180 hours/day (difference = 20 hours, 95% CI = 8 to 32 hours). After daily ED volume, low-acuity area volume, daily wait time, daily boarding hours, and nurse staffing were adjusted for, the percentage of patients who LWBT was not independently associated with ED expansion (p = 0.053). After ED admissions, ED intensive care unit (ICU) admissions, elective surgical admissions, hospital occupancy rate, ICU occupancy rate, and number of operational ICU beds were adjusted for, the increase in ED boarding hours was independently associated with the ED expansion (p = 0.005).


CONCLUSIONS
An increase in ED bed capacity was associated with no significant change in the percentage of patients who LWBT, but had an unintended consequence of an increase in ED boarding hours. ED expansion alone does not appear to be an adequate solution to ED crowding.
Projected impact and cost-effectiveness of a rotavirus vaccination program in India, 2008.

BACKGROUND
To assess the value of rotavirus vaccination in India, we determined the potential impact and cost-effectiveness of a national rotavirus vaccination program.


METHODS
We compared the national rotavirus disease and cost burden with and without a vaccination program and assessed the cost-effectiveness of vaccination. Model inputs included measures of disease and cost burden, vaccine performance, and vaccination coverage and cost. We measured the annual number of health-related events and treatment costs averted, as well as the cost-effectiveness in US dollars per disability-adjusted life-year (DALY) and cost per death averted. One-way sensitivity analyses were performed by individually varying each model input.


RESULTS
With use of a vaccine that has an estimated effectiveness of 50%, a rotavirus vaccination program in India would prevent ~44,000 deaths, ~293,000 hospitalizations, and ~328,000 outpatient visits annually, which would avert $20.6 million in medical treatment costs. Vaccination would be cost-saving at the GAVI Alliance price of $0.15 per dose. At $1.00 per dose, a vaccination program would cost $49.8 million, which would result in an expenditure of $21.41 per DALY averted or $662.94 per life saved. Even at $7.00 per dose, vaccination would be highly cost-effective. In sensitivity analyses, varying efficacy against severe rotavirus disease and vaccine price had the greatest impact on cost-effectiveness.


CONCLUSIONS
A national rotavirus vaccination program in India would prevent substantial rotavirus morbidity and mortality and would be highly cost-effective at a range of vaccine prices. Public health officials can use this locally derived data to evaluate how this highly cost-effective intervention might fit into India's long-term health care goals.
Radiological versus surgical implantation of first catheter for peritoneal dialysis: a randomized non-inferiority trial.

BACKGROUND
The success of peritoneal dialysis (PD) is dependent on timely and adequate PD catheter access. In many centres, including our own, PD catheter insertion technique has evolved by laparoscopic surgery. An alternative method of catheter insertion is performed by radiologists using a percutaneous modified Seldinger technique under fluoroscopic guidance. However, there are no clinical trials comparing these two methods of catheter insertion.


METHODS
From 1 April 1999 to 30 August 2004, we randomly assigned 113 pre-dialysis patients to receive PD catheter insertion using fluoroscopic guidance under local anaesthesia by radiologists or insertion using laparoscopy under general anaesthesia by a surgeon. The primary endpoint was the occurrence of dialysis catheter complications (complication-free catheter survival) by Day 365, a composite endpoint that included complications secondary to mechanical and infectious causes. Secondary endpoints were the occurrence of catheter removal (overall catheter survival) and death from any cause (patient survival) by Day 365, procedure pain, procedure time, procedure room utilization time, length of inpatient admission and direct hospital costs. Results were analysed by univariate and multivariate methods and by Kaplan-Meier survival curves.


RESULTS
Complication-free catheter survival was significantly higher at 42.5% [95% confidence interval (CI) 29.3-55] in the radiological group compared with 18.1% (95% CI 8.9-29.8) in the laparoscopic group (P-value = 0.03). Excess complications in the laparoscopic group included peritonitis, peritoneal dialysate leaks and umbilical herniae. One-year overall catheter survival and 1-year subject survival were not different between the groups. Hospital costs were significantly higher in the laparoscopic group by almost a factor of two.


CONCLUSIONS
Radiological insertion of first PD catheters using fluoroscopy is a clinically non-inferior and cost-effective alternative to surgical laparoscopic insertion.
A Brief Introduction to Neural Networks

Arti cial neural networks are being used with increasing frequency for high dimensional problems of regression or classi cation. This article provides a tutorial overview of neural networks, focusing on back propagation networks as a method for approximating nonlinear multivariable functions. We explain, from a statistician's vantage point, why neural networks might be attractive and how they compare to other modern regression techniques.
Corporate Control Through Board Dismissals and Takeovers

This paper examines some policy issues related to the interaction between internal and external corporate control mechanisms—board dismissals and takeovers—by focusing on the information aggregation and other effects related to this interaction. We model the functioning of corporate control mechanisms as an example of a multilayered principal-agent relationship in which shareholders delegate the task of monitoring management quality to the board and rely on the external takeover market to provide additional disciplining of the manager as well as of the board. This gives rise to two ( ) effects: 1 a substitution effect, whereby the takeover market partially substitutes for board dismissal of the manager, leading to greater lenience toward the manager by a board acting in the shareholders’ best interest, and ( ) 2 a kick-in-the-pants effect, whereby the board is stricter with the manager because it may be dismissed by a successful acquirer who views it as lax. The interaction of these two effects leads to various implications about the behavior of boards and potential acquirers. In particular, a well-functioning ( ) internal control mechanism the board does not obviate the need for external ( ) control takeovers . Moreover, somewhat counterintuitively, there may be a greater incidence of takeovers when the internal control mechanism is working well than when it is not.
Discovering influencers for marketing in the blogosphere

Discovering influential bloggers will not only allow us to understand better the social activities taking place in the blogosphere, but will also provide unique opportunities for sales and advertising. In this paper, we develop an MIV (marketing influential value) model to evaluate the influential strength and identify the influential bloggers in the blogosphere. We analyze three dimensions of blog characteristics (network-based, content-based, and activeness-based factors) and utilize an artificial neural network (ANN) to discover potential bloggers. Based on peer and official evaluations, the experimental results show that the proposed framework outperforms two social-network-based methods (out-degree and betweenness centrality algorithms) and two content-based mechanisms (review rating and popular author approaches). The proposed framework can be effectively applied to support marketers or advertisers in promoting their products or services. 2011 Elsevier Inc. All rights reserved.