Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the Uncertainty of Surgical Procedure Times: Comparison of Log-normal and Normal Models

Background: Medical institutions are under increased economic pressure to schedule elective surgeries efficiently to contain the costs of surgical services. Surgical scheduling is complicated by variability inherent in the duration of surgical procedures. Modeling that variability, in turn, provides a mechanism to generate accurate time estimates. Accurate time estimates are important operationally to improve operating room utilization and strategically to identify surgeons, procedures, or patients whose duration of surgeries differ from what might be expected. Methods: The authors retrospectively studied 40,076 surgical cases (1,580 Current Procedural Terminology–anesthesia combinations, each with a case frequency of five or more) from a large teaching hospital, and attempted to determine whether the distribution of surgical procedure times more closely fit a normal or a log-normal distribution. The authors tested goodness-of-fit to these data for both models using the Shapiro–Wilk test. Reasons, in practice, the Shapiro–Wilk test may reject the fit of a log-normal model when in fact it should be retained were also evaluated. Results: The Shapiro–Wilk test indicates that the log-normal model is superior to the normal model for a large and diverse set of surgeries. Goodness-of-fit tests may falsely reject the log-normal model during certain conditions that include rounding errors in procedure times, large sample sizes, untrimmed outliers, and heterogeneous mixed populations of surgical procedure times. Conclusions: The authors recommend use of the log-normal model for predicting surgical procedure times for Current Procedural Terminology–anesthesia combinations. The results help to legitimize the use of log transforms to normalize surgical procedure times before hypothesis testing using linear statistical models or other parametric statistical tests to investigate factors affecting the duration of surgeries.
“I’m Missing Something”: (Non) Nativeness in Prospective Teachers as Spanish and English Speakers

Abstract Rooted in the need to confront the pervasive and harmful effect of the myth of the native speaker and affiliated language ideologies, this article shares the findings of a research study conducted in two public Colombian universities. The study examined participants’ self-perceived (non) nativeness as speakers of Spanish and English. Using surveys and interviews within a mixed-method approach, the study found that participants perceived themselves as over-empowered in their being native Spanish speakers. Conversely, as speakers of English, most prospective teachers feared the disadvantages of not achieving native-like abilities, but they were confident in their university programs and their previous experience as English learners to achieve their language learning education goals.
Reasoning about knowledge: a survey

In this survey, I attempt to identify and describe some of the common threads that tie together work in reasoning about knowledge in such diverse elds as philosophy, economics, linguistics, artiicial intelligence, and theoretical computer science, with particular emphasis on work of the past ve years, particularly in computer science. It is a revised and updated version of a paper entitled \Reasoning about knowledge: a survey circa 1991", which appears in the
Conditional Expectation and Martingales Supplemental Material for Advanced Channel Coding

These notes are intended to introduce concentration inequalities for martingales with bounded increments. The final section also provides a gentle introduction to conditional expectation based on sigma fields. In contrast to providing a firm foundation for measure-theoretic probability, the primary goal is to introduce the language and intuition used in the study of martingales. The presentation is based on [1] but adds a few examples and details.
Complementary balanced words over an arbitrary finite alphabet

A binary word is balanced if the numbers of 1-bits in any 2 subwords of equal length differ by at most 1. The structure of m ≥ 3 complementary balanced binary words χ is determined. We prove that they must be characteristic words of Beatty words bnαj + γjc, and that two of the binary words must have identical densities of 1-bits, except possibly in the case where one of the αj is a proper rational (denominator ≥ 2). For m ≤ 7, the exceptional case is characterized completely. It is further shown that the above results are equivalent to analogous properties of complementary Beatty words and words on an alphabet of 2m letters.
Two-state Bose-Hubbard model in the hard-core boson limit

Phase transition into the phase with Bose-Einstein (BE) condensate in the two-band Bose-Hubbard model with the particle hopping in the excited band only is investigated. Instability connected with such a transition (which appears at excitation energies $\delta \delta_{\mathrm{crit}}\approx-0.12\lvert t_0' \rvert$). At $\mu<0$ the phase transition mostly remains to be of the second order. The behaviour of the BE-condensate order parameter is analyzed, the $(\Theta,\mu)$ and $(\lvert t_0' \rvert,\mu)$ phase diagrams are built and localizations of tricritical points are established. The conditions are found at which the separation on the normal phase and the phase with the BE condensate takes place.
Opportunities for leveraging OS virtualization in high-end supercomputing.

This paper examines potential motivations for incorporating virtualization support in the system software stacks of high-end capability supercomputers. We advocate that this will increase the flexibility of these platforms significantly and enable new capabilities that are not possible with current fixed software stacks. Our results indicate that compute, virtual memory, and I/O virtualization overheads are low and can be further mitigated by utilizing well-known techniques such as large paging and VMM bypass. Furthermore, since the addition of virtualization support does not affect the performance of applications using the traditional native environment, there is essentially no disadvantage to its addition.
Managing user acceptance: an empirical investigation in the context of business intelligence standard software

This study suggests and tests a model for the systematic evaluation of management activities in company-wide standard software implementations using the example of a business intelligence (BI) software package. The proposed model builds on an extended technology acceptance model (TAM), previous research on IT implementation success factors and reviews of relevant change management variables. Using structural equation modelling, several hypotheses are tested. The investigated management variables demonstrate significant influences on the psychological acceptance factors included in the model. Seven out of ten hypotheses are confirmed. In addition, the model explains a substantial amount of variance in actual user behaviour measured with a system-based indicator. Practical implications for the implementation of company-wide standard software in organisations are discussed.
Incorporating scene constraints into the triangulation of airborne oblique images

An increasing number of airborne systems equipped with oblique viewing cameras are reported being operational, such as Pictometry, FLI-MAP, 3K or PFIFF. The oblique images are today mainly used for visualization purposes, but they are also interesting for instance for cadastre applications. In order to optimize the exterior orientation, and eventually also to calibrate the interior orientation and distortion parameters, it is a common means in close-range photogrammetry related literature to incorporate scene constraints into the block adjustment. As oblique airborne cameras image vertical man made structures like building façades, it becomes possible to introduce strong geometric constraints also here. Examples are horizontal and vertical line features at façades and the rectangular alignment of these features. In this paper we introduce our own approach to airborne image triangulation, where the mentioned constraints are explicitly exploited in the block adjustment of images from multiple camera devices, including self-calibration. The influence of the scene constraints is validated by comparing the results from our approach to results obtained from the commercial software packages LPS 9.2, ImageModeler 2009, and Boujou 4.1. All these systems have different properties with respect to the incorporation of scene constraints and options for self-calibration. A data set of oblique and vertical images from a FLI-MAP 400 (Fugro Aerial Mapping B.V.) flight over Enschede is used for the experiments. The experiments reveal that the easily definable scene constraints enhance the overall result of bundle block adjustment and self-calibration. Due to the restricted self-calibration capabilities for multiple camera set-ups the results from LPS are not optimal. In addition, it is not possible to incorporate scene constraints into LPS. In contrast, ImageModeler and Boujou are focussing on the use of uncalibrated consumer cameras and show also more options with respect to the use of constraints. All types of constraints can be incorporated only in our own approach and at the same time our method allows the self-calibration of multiple devices. Because of those reasons our method resulted in the best overall solution.
Accessing Private Network via Firewall Based On Preset Threshold Value

Many of the private services are made readily available to the users publically from emerging technologies such as web services, cloud computing, service-oriented architecture in an more effective and efficient manner. However, the users still suffer from security leakages by unauthorized one. Firewalls are the vital elements in network security. The worthiness of the firewall mainly depends on the quality of policies deployed in the firewall. Deploying and configuring firewall policies are more tedious and error-prone. In this Paper, we present an effective policy anomaly management framework for firewalls, anomalies are identified using rule-based segmentation technique and are derived effective anomaly resolution . In certain, we also make use of grid-based visualization technique, providing an intuitive cognitive sense about policy anomaly. User's requests are allowed to access the private network based on preset threshold value. In particular, we also demonstrate how effectively our approach can identify and overcome anomalies in firewall policies through various experiments. General Terms: Firewall, Policy anomaly management framework, Segmentation, Threshold value.
Alignment-Based Similarity of People Trajectories Using Semi-directional Statistics

This paper presents a method for comparing people trajectories for video surveillance applications, based on semi-directional statistics. In fact, the modelling of a trajectory as a sequence of angles, speeds and time lags, requires the use of a statistical tool capable to jointly consider periodic and linear variables. Our statistical method is compared with two state-of-the-art methods.
Lefty is expressed in mouse endometrium in estrous cycle and peri-implantation period.

BACKGROUND Reproductive tissues are unique structures that exhibit cyclic stromal remodelling during menstrual cycles in humans. Ebaf/lefty participates in tissue remodelling of human endometrium by induction of matrix metalloproteases (MMP). METHODS We describe the temporal expression and spatial distribution of lefty and tissue remodelling events in mouse endometrium. RT-PCR and real-time PCR were used to identify mRNA expression and western blots to analyse Lefty protein. Immunolocalization was performed with specific antibodies and horseradish peroxidase staining. RESULTS Lefty was expressed in endometrium throughout the estrous cycle. Expression of MMP (MMP-2, -3, -7 and -14) was higher at estrus, metestrus and/or diestrus while collagen content of endometrium decreased in these phases. During pregnancy, lefty levels were higher on days 3-5 and were minimal by day 9. Similarly, expression of endometrial MMP was higher on days 3 and 5 of pregnancy and was low on day 9. During pregnancy, loss of collagen was initiated on day 3, persisted to day 5, and led to a significantly reduced collagen on day 9. Immunoreactive lefty decorated basal laminae, and was associated with extracellular matrix in stroma. CONCLUSIONS Regulated expression and spatial distribution of lefty in mouse endometrium confines its biological impact on tissues that undergo remodelling during estrous cycle and pregnancy.
An Emergent Approach to Text Analysis Based on a Connectionist Model and the Web

In this paper, we present a method to provide proactive assistance in text checking, based on usage relationships between words structuralized on the Web. For a given sentence, the method builds a connectionist structure of relationships between word n-grams. Such structure is then parameterized by means of an unsupervised and language agnostic optimization process. Finally, the method provides a representation of the sentence that allows emerging the least prominent usage-based relational patterns, helping to easily find badly-written and unpopular text. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and some experimental use.
Group selection and social evolution in domesticated animals

Social interactions, especially those involving competition among individuals, are important in domesticated livestock and in natural populations. The heritability of traits affected by such interactions has two components, one originating in the individual like that of classical traits (direct effects) and the other originating in other group members (indirect effects). The latter type of trait represents a significant source of ‘hidden heritability’ and it requires population structure and knowledge from relatives in order to access it for selective breeding. When ignored, competitive interactions may increase as an indirect response to direct selection, resulting in diminished yields. We illustrate how population genetic structure affects the response to selection of traits with indirect genetic effects using population genetic and quantitative genetic theory. Population genetic theory permits us to connect our results to the existing body of theory on kin and group selection in natural populations. The quantitative genetic perspective allows us to see how breeders have used knowledge from relatives and family selection in the domestication of plants and animals to improve the welfare and production of livestock by incorporating social genetic effects in the breeding program. We illustrate the central features of these models by reviewing empirical studies from domesticated chickens.
‘‘Blacks Deserve Bodies Too!’’: Design and Discussion About Diversity and Race in a Tween Virtual World

In this paper, we investigate racial diversity in avatar design and public discussions about race within a large-scale tween virtual world called Whyville.net, with more than 1.5 million registered players of ages 8—16. One unique feature of Whyville is the player’s ability to customize their avatars with various face parts and accessories, all designed and sold by other players in Whyville. Our findings report on the racial diversity of available resources for avatar construction and online postings about the role of race in avatar design and social interactions in the community. With the growing interest in player-generated content for online worlds such as Teen Second Life, our discussion addresses the role of avatars in teen/tween identity development and self-representation, and the role of virtual entrepreneurs and community activists in increasing the diversity of avatar parts available.
Towards auditable cloud-assisted access of encrypted health data

Motivated by the privacy issues curbing the adoption of electronic healthcare systems and the wild success of cloud service models, we propose to build privacy into electronic healthcare systems with the help of private cloud. Our system offers salient features including privacy-preserving data access, especially during emergencies, and auditability for misusing health data. Specifically, we propose to integrate the concept of attribute-based encryption with threshold signing for providing role-based access control with auditability to prevent potential misbehavior, in both normal and emergency cases.
Cost-effectiveness of relapse-prevention cognitive therapy for bipolar disorder: 30-month study.

BACKGROUND We have reported the advantageous clinical outcome of adding cognitive therapy to medication in the prevention of relapse of bipolar disorder. AIMS This 30-month study compares the cost-effectiveness of cognitive therapy with standard care. METHOD We randomly allocated 103 individuals with bipolar 1 disorder to standard treatment and cognitive therapy plus standard treatment. Service use and costs were measured at 3-month intervals and cost-effectiveness was assessed using the net-benefit approach. RESULTS The group receiving cognitive therapy had significantly better clinical outcomes. The extra costs were offset by reduced service use elsewhere. The probability of cognitive therapy being cost-effective was high and robust to different therapy prices. CONCLUSIONS Combination of cognitive therapy and mood stabilizers was superior to mood stabilizers alone in terms of clinical outcome and cost-effectiveness for those with frequent relapses of bipolar disorder.
Using feature scale change for robot localization along a route

An appearance-based similarity measure for localizing a robot along a route is presented. This measure assesses the likelihood that the robot lies between a pair of positions where snapshot images were captured during training. The change in the scale parameter of matched SIFT features is used to determined whether the robot lies ahead or behind each snapshot. Experimental results in two different indoor environments suggest that this similarity measure will improve localization accuracy in situations where there is a large distance between snapshot positions.
A new Bacillus subtilis gene, med, encodes a positive regulator of comK

Bacillus subtilis degR, a positive regulator of the production of degradative enzymes, is negatively regulated by the competence transcription factor ComK which is overproduced in mecA null mutants. We used transposon Tn10 to search for a mutation that reduced the repression level of degR caused by a mecA mutation. A new gene exerting positive regulation on comK was obtained and designated med (suppressor of mecA effect on degR). Sequence determination, Northern analysis, and primer extension analyses revealed that the med gene contained an open reading frame (ORF) composed of 317 codons and was transcribed into an approximately 1,250-nucleotide mRNA together with its short downstream gene. The expression of comK is positively regulated by factors such as ComK itself, ComS (SrfA)-MecA, DegU, SinR, and AbrB. Quantitative analyses using comK'-'lacZ, srfA-lacZ, degU'-'lacZ, and sinR'-'lacZ fusions showed that disruption of med caused a significant decrease in comK expression in both mecA+ and mecA strains, while expression of srfA, sinR, and degU was not affected by the mutation. An epistatic analysis revealed that overproduction of ComK resulted in alteration of med expression, suggesting a regulatory loop between comK and med. Several possible mechanisms for positive regulation of comK by Med are discussed.
Feature Integration across Multimodal Perception and Action: A Review

The human brain is facing a continuous stream of stimulus information delivered by multiple modalities and sensory channels and processed in distinct cortical regions. We discuss recent empirical and theoretical developments in addressing the question of how this distributed information is integrated into coherent representations (the so-called binding problem) with an emphasis on the principles and constraints underlying the integration of multiple (rather than redundant) features across different sensory modalities and across perception and action planning.
UC : A Fluid Interface for Personal Digital Libraries

An advanced visual interface system is presented for fluid interaction in a personal digital library system. The system employs a zoomable planar representation of a collection using hybrid continuous/quantum treemap visualizations to facilitate navigation while minimizing cognitive load. By providing both fluidity and a means of reading documents within the same visualization, the system obliterates the traditional boundary separating the acquisition of materials from their use. In addition, the system provides a means of streamlining and largely automating the addition of new documents into a collection. The system is particularly well suited to user tasks which, in the physical world, are normally carried out by laying out a set of related documents on a physical desk — namely, those tasks that require frequent and rapid transfer of attention from one document in the collection to another. Discussed are the design and implementation of the system as well as its relationship to previous work.
A Study of Bio-inspired Algorithm to Data Clustering using Different Distance Measures

Data mining is the process of extracting previously unknown and valid information from large databases. Clustering is an important data analysis and data mining method. It is the unsupervised classification of objects into clusters such that the objects from same cluster are similar and objects from different clusters are dissimilar. Data clustering is a difficult unsupervised learning problem because many factors such as distance measures, criterion functions, and initial conditions have come into play. Many algorithms have been proposed in literature. However, some traditional algorithms have drawbacks such as sensitive to initialization and easily trapped in local optima. Recently, bio-inspired algorithms such as ant colony algorithms (ACO) and particle swarm optimization algorithms (PSO) have found success in solving clustering problems. These algorithms have also been used in several other real-life applications. They are global optimization techniques. The distance based algorithms have been studied for the clustering problems. This paper provides a study of particle swarm optimization algorithm to data clustering using different distance measures including Euclidean, Manhattan and Chebyshev for well known real-life benchmark medical data sets and an artificially generated data set. The PSO-based clustering algorithm using Chebyshev distance measure is better fitness value than those of Euclidean and Manhattan distance measures.