Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the potential for touchless interaction in image-guided interventional radiology

The growth of image-guided procedures in surgical settings has led to an increased need to interact with digital images under sterile conditions. Traditional touch-based interaction techniques present challenges for managing asepsis in these environments leading to suggestions that new touchless interaction techniques may provide a compelling set of alternatives. In this paper we explore the potential for touchless interaction in image-guided Interventional Radiology (IR) through an ethnographic study. The findings highlight how the distribution of labour and spatial practices of this work are organised with respect to concerns about asepsis and radiation exposure, the physical and cognitive demands of artefact manipulation, patient management, and the construction of "professional vision". We discuss the implications of these key features of the work for touchless interaction technologies within IR and suggest that such issues will be of central importance in considering new input techniques in other medical settings.
Forming Interoperability Through Interorganizational Systems Standards

Interoperability is a crucial organizational capability that enables firms to manage information systems (IS) from heterogeneous trading partners in a value network. While interoperability has been discussed conceptually in the IS literature, few comprehensive empirical studies have been conducted to conceptualize this construct and examine it in depth. For instance, it is unclear how interoperability is formed and whether it can improve organizational performance. To fill the gap, we argue that interorganizational systems (IOS) standards are a key information technology infrastructure facilitating formation of interoperability. As an organizational ability to work with external trading partners, interoperability's development depends not only on capability building within firm boundaries but also on community readiness across firm boundaries. Using data collected from 194 organizations in the geospatial industry, we empirically confirm that interoperability is formed via these two different paths. Furthermore, our results show that interoperability acts as a mediator by enabling firms to achieve performance gains from IOS standards adoption. Our study sheds new light on formation mechanisms as well as the business value of interoperability.
Are Silicon Nanoparticles an Interstellar Dust Component?

Silicon nanoparticles (SNPs) with oxide coatings have been proposed as the source of the observed "extended red emission" (ERE) from interstellar dust. We calculate the thermal emission expected from such particles, both in a reflection nebula such as NGC 2023 and in the diffuse interstellar medium (ISM). It is shown that Si/SiO2 SNPs (both neutral and charged) would produce a strong emission feature at 20 μm. The observational upper limit on the 20 μm feature in NGC 2023 imposes an upper limit of less than 0.2 parts per million in Si/SiO2 SNPs. The observed ERE intensity from NGC 2023 then gives a lower bound on the product ηPLf0, where ηPL < 1 is the photoluminescence efficiency for a neutral SNP and f0 ≤ 1 is the fraction of SNPs that are uncharged. For foreground extinction A0.68 μm = 1.2 mag, we find ηPLf0 > 0.24 for Si/SiO2 SNPs in NGC 2023. Measurement of the R-band extinction toward the ERE-emitting region could strengthen this lower limit. The ERE emissivity of the diffuse interstellar medium appears to require ≳42% of solar Si abundance in Si/SiO2 SNPs even with ηPLf0 = 1. We predict IR emission spectra and show that DIRBE photometry appears to rule out such high abundances of free-flying SNPs in the diffuse ISM. We conclude that if the ERE is due to SNPs, they must be either in clusters or attached to larger grains.
Frequent itemsets hiding: A performance evaluation framework

Sensitive knowledge hiding is an essential requirement to prevent disclosure of any sensitive knowledge holding in shared databases. The security of a database may be risked when it is made public as is: because the data mining tools are so sophisticated that the sensitive knowledge can easily be surfaced by receivers. This gives rise to a sanitization process which transforms the original database into another database, the released one, which does not hold the sensitive knowledge but can substitute the original otherwise. In case the sensitive knowledge is of the form frequent itemsets, the resulting concrete problem is called frequent itemsets hiding. A number of algorithms, exploiting different approaches and techniques, for frequent itemsets hiding problem is proposed in the literature. Since finding optimal solutions is NP-Hard, algorithms resort to certain heuristics having different levels of sophistication, complexity, efficiency and effectiveness. This paper presents an evaluation framework which implements recent algorithms belonging to different approaches and a set of metrics to gauge the performance and problem difficulties. The current work also presents an experimental study and its results where four algorithms and seven datasets are involved. Our results indicate that data distortion levels and runtime requirements are quite high, especially for difficult problem instances. Our conclusion is that there are new rooms for more sophisticated and tuneable (w.r.t. effectiveness/efficiency tradeoff) algorithms.
Complexity Classifications for Logic-Based Argumentation

We consider logic-based argumentation in which an argument is a pair (Φ, α), where the support Φ is a minimal consistent set of formulae taken from a given knowledge base (usually denoted by Δ) that entails the claim α (a formula). We study the complexity of three central problems in argumentation: the existence of a support Φ⊆Δ, the verification of a support, and the relevance problem (given ψ, is there a support Φ such that ψ ∈ Φ? ). When arguments are given in the full language of propositional logic, these problems are computationally costly tasks: the verification problem is DP-complete; the others are Σ<sup>p</sup><sub>2</sub>-complete. We study these problems in Schaefer's famous framework where the considered propositional formulae are in generalized conjunctive normal form. This means that formulae are conjunctions of constraints built upon a fixed finite set of Boolean relations Γ (the constraint language). We show that according to the properties of this language Γ, deciding whether there exists a support for a claim in a given knowledge base is either polynomial, NP-complete, coNP-complete, or Σ<sup>p</sup><sub>2</sub>-complete. We present a dichotomous classification, P or DP-complete, for the verification problem and a trichotomous classification for the relevance problem into either polynomial, NP-complete, or Σ<sup>p</sup><sub>2</sub>-complete. These last two classifications are obtained by means of algebraic tools.
Impact of heart failure and exercise capacity on sympathetic response to handgrip exercise.

Peak oxygen uptake (VO(2 peak)) in patients with heart failure (HF) is inversely related to muscle sympathetic nerve activity (MSNA) at rest. We hypothesized that the MSNA response to handgrip exercise is augmented in HF patients and is greatest in those with low VO(2 peak). We studied 14 HF patients and 10 age-matched normal subjects during isometric [30% of maximal voluntary contraction (MVC)] and isotonic (10%, 30%, and 50% MVC) handgrip exercise that was followed by 2 min of posthandgrip ischemia (PHGI). MSNA was significantly increased during exercise in HF but not normal subjects. Both MSNA and HF levels remained significantly elevated during PHGI after 30% isometric and 50% isotonic handgrip in HF but not normal subjects. HF patients with lower VO(2 peak) (<56% predicted; n = 8) had significantly higher MSNA during rest and exercise than patients with VO(2 peak) > 56% predicted (n = 6) and normal subjects. The muscle metaboreflex contributes to the greater reflex increase in MSNA during ischemic or intense nonischemic exercise in HF. This occurs at a lower threshold than normal and is a function of VO(2 peak).
A Decision-Theoretic Formulation for Sparse Stereo Correspondence Problems

Stereo reconstruction is challenging in scenes with many similar-looking objects, as matches between features are often ambiguous. Features matched incorrectly lead to an incorrect 3D reconstruction, whereas if correct matches are missed, the reconstruction will be incomplete. Previous systems for selecting a correspondence (set of matched features) select either a maximum likelihood correspondence, which may contain many incorrect matches, or use some heuristic for discarding ambiguous matches. In this paper we propose a new method for selecting a correspondence: we select the correspondence which minimises an expected loss function. Match probabilities are computed by Gibbs sampling, then the minimum expected loss correspondence is selected based on these probabilities. A parameter of the loss function controls the trade off between selecting incorrect matches versus missing correct matches. The proposed correspondence selection method is evaluated in a model-based framework for reconstructing branching plants, and on simulated data. In both cases it outperforms alternative approaches in terms of precision and recall, giving more complete and accurate 3D models.
The Glass Drop Ceiling: Composition Effects or Implicit Discrimination?

We analyze data from the Bank of Italy's most recent recruitment rounds, in an effort to explain why men consistently score better than women. We focus on the pre-screening stage of the hiring process, a multiple-choice test, where men acquire a preliminary advantage. After observing a higher incidence of questions left blank for women, and a negative correlation between the share of unanswered questions and the final score, we run an experiment on scoring formulas to check for implicit discrimination linked to risk aversion; no evidence of such discrimination is found. Based on a follow-up questionnaire, we also study the role of composition effects. Nearly 40 per cent of the gap in test scores depends on the quality of the candidates: male graduates appear to self-select into the applicant pool more frequently than females do. A further 34 per cent is explained by the fact that the same characteristics tend to produce different effects based on gender. The remaining 26 per cent remains unexplained.
OPTIMAL PRODUCTION OF L-threo-2,3-DIHYDROXYPHENYLSERINE (L-threo-DOPS) ON A LARGE SCALE BY DIASTEREOSELECTIVITY-ENHANCED VARIANT OF L-THREONINE ALDOLASE EXPRESSED IN Escherichia coli

This study examined the efficient production and optimal separation procedures for pure L-threo-3,4-dihydroxyphenylserine (L-threo-DOPS) from a mixture of diastereomers synthesized by whole-cell aldol condensation reaction, harboring diastereoselectivity-enhanced L-threonine aldolase in Escherichia coli JM109. The addition of the reducing agent sodium sulfite was found to stimulate the production of L-threo-DOPS without affecting the diastereoselectivity ratio, especially at the 50 mM concentration. The optimal pH for diastereoselective synthesis was 6.5. The addition of Triton X-100 also strongly affected the synthesis yield, showing the highest conversion yield at a 0.75% concentration; however, the diastereoselectivity of the L-threonine aldolase was not affected. Lowering the temperature to 10°C did not significantly affect the diastereoselectiviy without affecting the synthesis rate. At the optimized conditions, a mixture of L-threo-DOPS and L-erythro-DOPS was synthesized by diastereoselectivity-enhanced L-threonine aldolase from E. coli in a continuous process for 100 hr, yielding an average of 4.0 mg/mL of L-threo-DOPS and 60% diastereoselectivity (de), and was subjected to two steps of ion exchange chromatography. The optimum separation conditions for the resin and solvent were evaluated in which it was found that a two-step process with the ion-exchange resin Dowex 50 W × 8 and activated carbon by washing with 0.5 N acetic acid was sufficient to separate the L-threo-DOPS. By using two-step ion-exchange chromatography, synthesized high-purity L-threo-DOPS of up to 100% was purified with a yield of 71%. The remaining substrates, glycine and 3,4-dihydroxybenzaldehyde, were recovered successfully with a yield of 71.2%. Our results indicate this potential procedure as an economical purification process for the synthesis and purification of important L-threo-DOPS at the pharmaceutical level.
Approximating the coalescent with recombination

The coalescent with recombination describes the distribution of genealogical histories and resulting patterns of genetic variation in samples of DNA sequences from natural populations. However, using the model as the basis for inference is currently severely restricted by the computational challenge of estimating the likelihood. We discuss why the coalescent with recombination is so challenging to work with and explore whether simpler models, under which inference is more tractable, may prove useful for genealogy-based inference. We introduce a simplification of the coalescent process in which coalescence between lineages with no overlapping ancestral material is banned. The resulting process has a simple Markovian structure when generating genealogies sequentially along a sequence, yet has very similar properties to the full model, both in terms of describing patterns of genetic variation and as the basis for statistical inference.
Correlations in Social Neuroscience Aren't Voodoo

Vul, Harris, Winkielman, and Pashler (2009, this issue) claim that many brain-personality correlations in fMRI studies are ''likely . spurious'' (p. 274), and ''should not be believed'' (p. 285). Several of their con- clusions are incorrect. First, they incorrectly claim that whole-brain regressions use an invalid and ''nonindepen- dent'' two-step inferential procedure, a determination based on a survey sent to researchers that only included nondiagnostic questions about the descriptive process of plotting one's data. We explain how whole-brain regres- sions are a valid single-step method of identifying brain regions that have reliable correlations with individual difference measures. Second, they claim that large corre- lations from whole-brain regression analyses may be the result of noise alone. We provide a simulation to demon- strate that typical fMRI sample sizes will only rarely produce large correlations in the absence of any true ef- fect. Third, they claim that the reported correlations are inflated to the point of being ''implausibly high. '' Though biased post hoc correlation estimates are a well-known consequence of conducting multiple tests, Vul et al. make inaccurate assumptions when estimating the theoretical ceiling of such correlations. Moreover, their own ''meta- analysis'' suggests that the magnitude of the bias is ap- proximately.12—a rather modest bias. In an article in this issue, Vul, Harris, Winkielman, & Pashler (2009, this issue) claim that brain-personality correlations in many social neuroscience studies and those in related fields are ''implausibly high'' (p. 274), ''likely . spurious'' (p. 274), and ''shouldnotbebelieved''(p.285). Thearticlewasoriginallytitled ''VoodooCorrelationsinSocialNeuroscience''andwascirculated widely in the scientific community, on the Internet, and in the popularpresspriortopublication.Thewordvoodoo,asappliedto science, carries a strong and specific connotation of fraudulence, aspopularizedbyRobertPark's(2000)book,VoodooScience:The Road From Foolishness to Fraud. Though the title was subse- quently changed to remove the wordvoodoo, the substance of the article and its connotations are unchanged: It is a pointed attack on social neuroscience. Much of the article's prepublication im-
Automated lung nodule segmentation using dynamic programming and EM-based classification

In this paper we present a robust and automated algorithm to segment lung nodules in three dimensional (3D) Computed Tomography (CT) volume dataset. The nodule is segmented out in slice-per-slice basis, that is, we first process each CT slice separately to extract two dimensional (2D) contours of the nodule which can then be stacked together to get the whole 3D surface. The extracted 2D contours are optimal as we utilize dynamic programming based optimization algorithm. To extract each 2D contour, we utilize a shape based constraint. Given a physician specified point on the nodule, we blow a circle which gives us rough initialization of the nodule from where our dynamic programming based algorithm estimates the optimal contour. As a nodule can be calcified, we pre-process a small region-of-interest (ROI), around the physician selected point on the nodule boundary, using the Expectation Maximization (EM) based algorithm to classify and remove calcification. Our proposed approach can be consistently and robustly used to segment not only the solitary nodules but also the nodules attached to lung walls and vessels.
A Lightweight Simulation Framework for the Analysis of Electrified Vehicle Fleets

Replacing combustion vehicles with electric vehicles is a major step towards reducing CO 2 emissions. With regard to this shift, in particular commercial or governmental vehicle fleets are believed to be early adopters. However, the electrification of vehicle fleets is a complex task since it can have a huge impact on companies' day-to-day-business. This article presents a lightweight simulation framework to support the planning process and to study important effects of vehicle fleet electrification. Our discrete event-based approach allows to investigate economical and environmental aspects, such as the impact on operating costs, the required electric energy, or the amount of CO 2 emissions. Based on a given trip schedule (consisting of start time, distance, and duration), the framework allows deriving all necessary information, among others to dimension both the vehicle fleet and the charging infrastructure. We show the usefulness and the capability of our model by presenting results for a mid-sized company's vehicle fleet comprising 100 vehicles.
Understanding and Controlling Response Bias in Needs Assessment Studies

This study demonstrated that estimates of agency awareness in the typical needs assessment study are probably inflated by a response bias labeled “agency awareness overclaiming. ” Overclaimers (respondents who reported being aware of fictitious agencies) reported being aware of more real agencies than other respondents. Estimates of agency awareness may also be biased, because certain segments of the population were more likely to exhibit agency awareness overclaiming. Age was positively correlated with overclaiming, and African Americans were more likely to exhibit agency awareness overclaiming than Caucasians. General overclaiming was correlated with agency awareness overclaiming, but social desirability and acquiescence were not.
Comparison of Approaches for Estimating Incidence Costs of Care for Colorectal Cancer Patients

Background:Estimates of the costs of medical care vary across patient populations, data sources, and methods. The objective of this study was to compare 3 approaches for estimating the incidence costs of colorectal cancer (CRC) care using similar patient populations, but different data sources and methods. Methods:We used 2 data sources, linked SEER-Medicare and Medicare claims alone, to identify newly diagnosed CRC patients aged 65 and older and estimated their healthcare costs during the observation period, 1998 to 2002. Controls were matched by sex, age-group, and geographic location. We compared mean net costs, measured as the difference in total cost between cases and controls, for: (1) a SEER-Medicare cohort, (2) a Medicare claims alone cohort, and (3) a modeled phase of care approach using linked SEER-Medicare data. The SEER-Medicare cohort approach was considered the reference. Results:We found considerable variability across approaches for estimating net costs of care in CRC patients. In the first year after diagnosis, mean net costs were $32,648 (95% CI: $31,826 and $33,470) in the SEER-Medicare cohort. The other approaches understated mean net costs in year 1 by about 16%. Mean net 5-year costs of care were $37,227 (95% CI: $35,711 and $38,744) in the SEER-Medicare cohort, and $30,310 (95% CI: $25,894 and $34,726) in the claims only approach, with the largest difference in the 65 to 69 age group. Mean net 5-year costs of care were more similar to the reference in the modeled phase of care approach ($37,701 [range: $36,972 and $38,446]). Differences from the SEER-Medicare cohort estimates reflect misclassification of prevalent cancer patients as newly diagnosed patients in the Medicare claims only approach, and differences in years of data and assumptions about comparison groups in the modeled phase of care approach. Conclusions:CRC incidence cost estimates vary substantially depending on the strategy and data source for identifying newly diagnosed cancer patients and methods for estimating longitudinal costs. Our findings may inform estimation of costs for other cancers as well as other diseases.
Resource Allocation in Cloud-Based Distributed Cameras

The data collected from millions of public cameras needs to be retrieved, stored, and analyzed. A system is required which needs to allocate significant amounts of resources to analyze large-scale visual data. Cloud computing provides shared storage, computation, and various services to handle such a tremendous amount of data collected from distributed cameras. In order to reduce the overall cost of analysis, this paper presents a resource allocation algorithm that provides cost-effective resources with the degree of demand, scaling automatically in proportion to demand fluctuation. In the cloud, the users prefer reliable resources at minimum cost whereas service providers prefer efficient resources utilization with maximum profit. Hence, it is necessary to have resource bargaining that assures and satisfies both cloud users and service providers. We propose a bargaining scheme using a game theoretic approach to managing cost and resource utilization in cloud-based distributed cameras. Our experiments show that our approach can lead to 10-15% reduction in cost by dynamically utilizing the resources and switching the service provider when it gets a better deal from other service providers.
Increased isolation of ESBL producing Klebsiella pneumoniae with emergence of carbapenem resistant isolates in Pakistan: report from a tertiary care hospital.

OBJECTIVE To report trends of extended spectrum beta lactamase (ESBL), multidrug resistant (MDR) ESBL and emergence of carbapenem resistant ESBL producing isolates of K. pneumoniae from Pakistan. METHODS Retrospective analysis of laboratory data was conducted (2002-2007). K. pneumoniae were isolated and identified from clinical samples using standard microbiological techniques. Antimicrobial susceptibility testing was performed by Kirby Bauer. ESBL was detected using combined disc method. Statistical analysis was performed using SPSS version 13. RESULTS 15914 K. pneumoniae isolates (2002-2007) were analyzed. Significant increase in ESBL and MDR ESBL producing K. pneumoniae (p = or < 0.0001) was observed. We found significant association of ESBL positive K. pneumoniae with age less than 10 years, males and blood isolates (p = 0.001). 0.4% (n=23) of ESBL positive isolates were carbapenem resistant. CONCLUSIONS Increase in ESBL and carbapenem resistant K. pneumoniae is a serious threat to public health requiring continuous surveillance and use of appropriate screening tests for laboratory detection.