Miracle-dz/UniFAR-FTUs huggingface dataset:
Cager: a framework for cross-page search

Existing search engines have page as the unit of information of retrieval. They typically return a ranked list of pages, each being a search result containing the query keywords. This within-one-page constraint disallows utilization of relationship information that is often available and greatly beneficial. To utilize relationship information and improve search precision, we explore cross-page search, where each answer is a logical page consisting of multiple closely related pages that collectively contain the query keywords. We have implemented a prototype Cager, providing cross-page search and visualization over real dataset.
Pain management in day-case surgery

### Key points Day-case surgery is defined as a planned surgical procedure for which selected patients are admitted to hospital and discharged home the same calendar day. The Department of Health in 2000 set a target that 75% of all elective surgery should be undertaken as day-case procedures and subsequently the British Association of Day Surgery now lists >200 different surgical procedures suitable for day-case and short-stay units. Additionally, there is an increasing political, managerial, and clinical drive to also admit patients presenting with acute conditions requiring urgent surgery as day cases. Indeed, the National Health Service (NHS) Modernisation Agency states inpatient care should be the exception rather than the rule.1 Planned changes to admission policies are expected to release nearly half a million in-patient bed days each year, generating large savings for the NHS, while at the same time responding to patients’ expectations of a modern, flexible healthcare service. Hence, day-case surgery is continually evolving with more extensive surgical procedures being offered to patients with an increased number of co-morbidities. Assisting in achieving those targets it is the role of the anaesthetist to plan anaesthetic techniques and pain relief suitable for day-case surgery patients. As postoperative pain is a common cause for extended hospital stay, unanticipated admission, and re-admission, the responsibilities of the anaesthetist encompass not only the immediate patient care but also the implementation and planning of day surgical lists. This paper will, in the context of day-case surgery, discuss the currently available options …
The MARS Adaptive Social Network for Information Access : Architecture and Experimental Results

Conventional techniques for finding information on the web are time-con suming and often yield unreliable results. This has led to renewed interest in referral systems, which support the interactions of people with others by directing users tow ard others who might have the answers they seek. We consider a social networkof agents who assist each other in helping their users find information. Unlike in most previous ap proaches, our architecture is fully distributed and includes agents who preserve the privacy and autonomy of their users. These agents learn models of each other in terms of expertise(ability to produce correct domain answers), and sociability (ability to produce accurate referrals). We study this framework experimentally to see the effects that the different variables ha ve on each other. Specifically, we find that under our multiagent learning heuristic, the qual ity of the network improves with time; the quality is maximized when both expertise and so ciability are considered during learning and querying; pivot agents (who relate different subcommunities) further improve the quality of the network and have a catalytic effect on i s quality even if they are ultimately removed. Recall that conventional approaches to collaborati on emphasize clustering the agents. By contrast, we find that the quality of the n etwork improves when clustering decreases, reflecting the intuition that you need to talk to peo ple outside your close circle to get the best information. Topics: Intelligent personal assistants; Resource discovery; Information retrieval and filtering. This research was supported by Ericsson and by the National S cience Foundation under grant IIS-9624425 (Career Award).
The D-Type Cyclin CYCD3;1 Is Limiting for the G1-to-S-Phase Transition in Arabidopsis[W]

The G1-to-S-phase transition is a key regulatory point in the cell cycle, but the rate-limiting component in plants is unknown. Overexpression of CYCLIN D3;1 (CYCD3;1) in transgenic plants increases mitotic cycles and reduces endocycles, but its effects on cell cycle progression cannot be unambiguously determined. To analyze the cell cycle roles of plant D-type cyclins, we overexpressed CYCD3;1 in Arabidopsis thaliana cell suspension cultures. Changes in cell number and doubling time were insignificant, but cultures exhibited an increased proportion of G2- over G1-phase cells, as well as increased G2 arrest in response to stationary phase and sucrose starvation. Synchronized cultures confirm that CYCD3;1-expressing (but not CYCD2;1-expressing) cells show increased G2-phase length and delayed activation of mitotic genes such as B-type cyclins, suggesting that CYCD3;1 has a specific G1/S role. Analysis of putative cyclin-dependent kinase phosphorylation sites within CYCD3;1 shows that mutating Ser-343 to Ala enhances CYCD3;1 potency without affecting its rate of turnover and results in a fivefold increase in the level of cell death in response to sucrose removal. We conclude that CYCD3;1 dominantly drives the G1/S transition, and in sucrose-depleted cells the decline in CYCD3;1 levels leads to G1 arrest, which is overcome by ectopic CYCD3;1 expression. Ser-343 is likely a key residue in modulating CYCD3;1 activity in response to sucrose depletion.
Racial group, socioeconomic status, and the development of persistent proteinuria in systemic lupus erythematosus

OBJECTIVES Systemic lupus erythematosus (SLE) patients of Afro-Caribbean and Asian origin living in the United Kingdom have a more severe spectrum of disease compared with the white population but whether this is attributable to genetic host factors or environmental factors is unclear. This study examines time from first symptom to onset of persistent proteinuria, as a marker of renal disease, to assess which factors are important. METHODS The 189 patients studied were ascertained using multiple methods and included 161 white, 22 Afro-Caribbean and six Asian patients. Time of first observation of persistent proteinuria (⩾0.5 g/day) was taken as onset of renal SLE. Initial univariate analysis to determine which factors are associated with onset of renal disease was followed by using a Cox's proportional hazards regression model enabling analysis of several prognostic factors at the same time. Variables included three measures of socioeconomic status, ethnic group and the presence or absence of different autoantibodies. RESULTS There was no effect from any socioeconomic variable. Using forwards stepwise selection, the following had independent effects (p<0.05) on the development of renal SLE: Afro-Caribbean race (hazard rate ratio 4.4 (1.9–10.2), compared with white population); and the presence of IgG anti-cardiolipin antibodies (hazard rate ratio 2.6 (1.2–5.7)). CONCLUSION Differing socioeconomic factors do not explain the increased frequency of lupus nephritis in Afro-Caribbean patients with SLE, but rather there are important genetic or other host differences. The independent effect of IgG anti-cardiolipin antibodies warrants further investigation.
Automatic whole mouse segmentation for cryo-imaging data using DRLSE model

Cryo-imaging is a novel and powerful imaging technique that enables 3D visualization of an entire mouse with single cell resolution. However, the current methods to segment a whole animal from the cryo-imaging data is not yet optimal. In this paper, we developed a fully-automatic software for segmenting a whole mouse in fluorescent cryo-images using Distance Regularized Level Set Evolution (DRLSE) model. In our experiment, we used masks that were manually created by experts as the gold standard to evaluate segmentation performance (sensitivity and specificity). We also tested the algorithm against a thresholding-based algorithm which was developed based on our previous work. The results suggest that DRLSE-based segmentation algorithm was more robust to noises and weak boundaries than the thresholding-based algorithm. The mean specificity of the DRLSE-based algorithm in the long exposure data (500 ms) and the short exposure data (250 ms) were 98.32% and 98.46%, respectively. The mean sensitivity in the long exposure data and the short exposure data were 97.08% and 93.93%, respectively. The drop in sensitivity was mostly due to the increased numbers of weak boundaries in the low contrast images. The 3D visualization results show similar results between the body masks generated by the DRLSE-based algorithm and the gold standard. This work is significant as it can increase through-put of cryo-imaging analysis and visualization workflow. Hopefully, it will have a significant impact on the advancement of biomedical image processing and analysis.
Micro disasters: Expanding the social work conceptualization of disasters

Environmental problems, like environmental disasters, mirror oppressive structural forces in society, as the primary victims of environmental degradation are also the main victims of other injustices. However, scholarship is lacking on the impacts of environmental disasters in these populations. Using a participatory phenomenological approach from a social work standpoint, this study uses the concept of slow violence to explore disasters in several poor communities in Kenya. Findings include the development and operationalization of a new term, micro disasters. Micro disasters are everyday problems that are linked to development and have no formal aid support for survivors, which deepens poverty.
Why Do Small Firms Choose Quasi-Integration? The Case Of The Homebuilding Industry

This article explores the variables that drive small firms to choose quasi- integration as an alternative to vertical integration in situations of high asset frequency. Our study provides new insights by focusing on (1) the preferences of small, vulnerable firms, and (2) an institutionalized form of quasi- integration. The findings indicate that the preference for quasi- integration is driven by asset specificity, bargaining power, and opportunistic expectations. The implications are that preferences for quasi- integration go beyond simple efficiency considerations.
Hierarchical clustering-based navigation of image search results

Usually, the image search results contain multiple topics on semantic level and even semantically consistent images have diverse appearances on visual level. How to organize the results into semantically and visually consistent clusters becomes a necessary task to facilitate users' navigation. To attack this, HiCluster, an effective method to organize image search results is designed in this paper, which employs both textual and visual analysis. First, we extract some query-related key phrases to enumerate specific semantics of the given query and cluster them into some semantic clusters using K-lines-based clustering algorithm. Second, the resulting images corresponding to each key phrase are clustered with Bregman Bubble Clustering (BBC) algorithm, which partially groups images in the whole set while discarding some scattered noisy ones. At last, a novel user interface (UI) is designed to provide users with the diverse and helpful information based on the hierarchical clustering structure. Experiments on web images demonstrate the effectiveness and potential of the system.
Heterogeneous Cellular Networks with Flexible Cell Association: A Comprehensive Downlink SINR Analysis

In this paper we develop a tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association policies. The HCN is modeled as a multi-tier cellular network where each tier's base stations (BSs) are randomly located and have a particular transmit power, path loss exponent, spatial density, and bias towards admitting mobile users. For example, as compared to macrocells, picocells would usually have lower transmit power, higher path loss exponent (lower antennas), higher spatial density (many picocells per macrocell), and a positive bias so that macrocell users are actively encouraged to use the more lightly loaded picocells. In the present paper we implicitly assume all base stations have full queues; future work should relax this. For this model, we derive the outage probability of a typical user in the whole network or a certain tier, which is equivalently the downlink SINR cumulative distribution function. The results are accurate for all SINRs, and their expressions admit quite simple closed-forms in some plausible special cases. We also derive the average ergodic rate of the typical user, and the minimum average user throughput - the smallest value among the average user throughputs supported by one cell in each tier. We observe that neither the number of BSs or tiers changes the outage probability or average ergodic rate in an interference-limited full-loaded HCN with unbiased cell association (no biasing), and observe how biasing alters the various metrics.
Metaphors and Auditor Professional Judgment: Can Non-Conscious Primes Activate Professionally Skeptical Mindsets?

Results of an experiment with 99 senior auditors from two Big 4 audit firms indicate that reading simple metaphors promotes professional skepticism and influences auditors’ skeptical judgments. Relative to auditor participants who did not read a metaphor, participants who read a metaphor related to concerns about the honesty of sources of information (client-skeptical metaphor) or concerns about one’s own ability to detect problems (self-skeptical metaphor) assessed higher levels of fraud risk, assessed greater needs for a risk management partner, and perceived that fraud-based explanations were more likely to cause fluctuations in client ratios. Further, the client-skeptical metaphor caused auditors to increase audit hours and increase audit testing for accounts likely to be influence by fraud. Metaphors are a form of non-conscious prime, and our results suggest that non-conscious priming represents a powerful and efficient tool for promoting professional skepticism.
Pursuing the double affine Grassmannian I: transversal slices via instantons on A_k-singularities

This paper is the first in a series that describe a conjectural analog of the geometric Satake isomorphism for an affine Kac-Moody group. In this paper we construct a model for the singularities of some would-be Schubert varieties in the affine Grassmannian for an affine Kac-Moody group. We formulate a conjecture describing the (local) intersection cohomology of these varieties in terms of integrable representations of the Langlands dual affine Kac-Moody group and check this conjecture in a number of cases. Roughly speaking the above singularities are constructed by looking at the Uhlenbeck space of instantons on the quotient of the affine plane by a finite cyclic subgroup of SL(2).
Hardware Architecture Design of CABAC Codec for H.264/AVC

This paper presents a hardware architecture for Context-Based Adaptive Binary Arithmetic Coding (CABAC) codec in H.264/AVC main profile. The similarities between encoding algorithm and decoding algorithm are explored to fulfill hardware reuse. Meanwhile, dynamic pipeline scheme is adopted to speedup the throughput. The characteristics of CABAC algorithm are utilized to reduce pipeline latency. Proposed codec design is implemented under TSMC 0.18 mum technology. Results show that the equivalent gate counts is 33.2 k when the maximum frequency is 230 MHz. It is estimated that the proposed CABAC codec can process the input binary symbol at 135 Mb/s for encoding and 90 Mb/s for decoding.
Athletes connected: Results from a pilot project to address knowledge and attitudes about mental health among college student-athletes

Student-athletes experience mental health problems, but they often encounter barriers to seeking help. This study reports findings from the pilot phase of Athletes Connected (AC), a new research and practice program at the University of Michigan addressing mental health and help-seeking behaviors among collegiate student-athletes. Members of the AC team gave presentations consisting of contact- and education-based interventions to every varsity athletic team at a large Division I Midwestern university, along with pre- and postsurvey questionnaires to measure their efficacy. The presentations included an educational overview of mental health, two videos highlighting former student-athletes’ struggles with mental illnesses, and a discussion at the end with the former athletes portrayed in the videos. A total of 626 student-athletes completed the pre- and postsurveys. Results indicated significant increases in knowledge and positive attitudes toward mental health and help-seeking. These results suggest that .
MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource for plant genomics

Arabidopsis thaliana is the most widely studied model plant. Functional genomics is intensively underway in many laboratories worldwide. Beyond the basic annotation of the primary sequence data, the annotated genetic elements of Arabidopsis must be linked to diverse biological data and higher order information such as metabolic or regulatory pathways. The MIPS Arabidopsis thaliana database MAtDB aims to provide a comprehensive resource for Arabidopsis as a genome model that serves as a primary reference for research in plants and is suitable for transfer of knowledge to other plants, especially crops. The genome sequence as a common backbone serves as a scaffold for the integration of data, while, in a complementary effort, these data are enhanced through the application of state-of-the-art bioinformatics tools. This information is visualized on a genome-wide and a gene-by-gene basis with access both for web users and applications. This report updates the information given in a previous report and provides an outlook on further developments. The MAtDB web interface can be accessed at http://mips.gsf. de/proj/thal/db.
Regular Article: Modeling Melt Convection in Phase-Field Simulations of Solidification

A novel diffuse interface model is presented for the direct numerical simulation of microstructure evolution in solidification processes involving convection in the liquid phase. The solidification front is treated as a moving interface in the diffuse approximation as known from phase-field theories. The no-slip condition between the melt and the solid is realized via a drag resistivity in the diffuse interface region. The model is shown to accurately reproduce the usual sharp interface conditions in the limit of a thin diffuse interface region. A first test of the model is provided for flow through regular arrays of cylinders with a stationary interface. Then, two examples are presented that involve solid/liquid phase-change: (i) coarsening of a mush of a binary alloy, where both the interface curvature and the flow permeability evolve with time, and (ii) dendritic growth in the presence of melt convection with particular emphasis on the operating point of the tip.
A Layered Fabric 3D Printer for Soft Interactive Objects

We present a new type of 3D printer that can form precise, but soft and deformable 3D objects from layers of off-the-shelf fabric. Our printer employs an approach where a sheet of fabric forms each layer of a 3D object. The printer cuts this sheet along the 2D contour of the layer using a laser cutter and then bonds it to previously printed layers using a heat sensitive adhesive. Surrounding fabric in each layer is temporarily retained to provide a removable support structure for layers printed above it. This process is repeated to build up a 3D object layer by layer. Our printer is capable of automatically feeding two separate fabric types into a single print. This allows specially cut layers of conductive fabric to be embedded in our soft prints. Using this capability we demonstrate 3D models with touch sensing capability built into a soft print in one complete printing process, and a simple LED display making use of a conductive fabric coil for wireless power reception.
Towards force sensing from vision: Observing hand-object interactions to infer manipulation forces

We present a novel, non-intrusive approach for estimating contact forces during hand-object interactions relying solely on visual input provided by a single RGB-D camera. We consider a manipulated object with known geometrical and physical properties. First, we rely on model-based visual tracking to estimate the object's pose together with that of the hand manipulating it throughout the motion. Following this, we compute the object's first and second order kinematics using a new class of numerical differentiation operators. The estimated kinematics is then instantly fed into a second-order cone program that returns a minimal force distribution explaining the observed motion. However, humans typically apply more forces than mechanically required when manipulating objects. Thus, we complete our estimation method by learning these excessive forces and their distribution among the fingers in contact. We provide a full validity analysis of the proposed method by evaluating it based on ground truth data from additional sensors such as accelerometers, gyroscopes and pressure sensors. Experimental results show that force sensing from vision (FSV) is indeed feasible.
Ubiquitous community driven traffic analysis

The availability data sources is increasing thanks to the rise of interconnected devices with sensory capabilities. Their use, has also become predominant in tasks that are not directly related with the devices' primary function or for which they may not even be designed for. Taking in consideration the act of driving, this research shows how through a composition of theories and services with these connected devices, it is possible to monitor and profile drivers performance and the generate community knowledge that can be used for the creation of user notification and warning systems. Thanks to the composition of theories from ubiquitous sensorization, machine learning, and communications it possible to design a general platform based on ubiquitous devices that generate information and models about each user behaviour individually and in communities around specific locations. This helps the improvement of not only performance but also security. Sensorization of large communities of users enrolled in driving activities can generate useful knowledge to the community. This article explores ubiquitous sensorization over the PHESS Driving platform to create reliable information that can be shared between users based on communication opportunity and location.
Sparse model fitting in nested families: Bayesian approach vs penalized likelihood

We study the problem of model fitting in the framework of nested probabilistic families. Our criteria are: (i) sparsity of the identified representation, (ii) its ability to fit the (finite length) data set available. As we show in this paper, current methodologies, often taking the form of penalized versions of the data likelihood, cannot simultaneously satisfy these requirements, as the examples presented clearly demonstrate. On the contrary, maximization of the Bayesian model posterior, even without assumption of a complexity penalizing prior, is able to select models with appropriate complexity, enabling sound determination of its parameters in a second step.