Miracle-dz/UniFAR-FTUs huggingface dataset:
A biopsychosocial-spiritual model for the care of patients at the end of life.

PURPOSE This article presents a model for research and practice that expands on the biopsychosocial model to include the spiritual concerns of patients. DESIGNS AND METHODS Literature review and philosophical inquiry were used. RESULTS The healing professions should serve the needs of patients as whole persons. Persons can be considered beings-in-relationship, and illness can be considered a disruption in biological relationships that in turn affects all the other relational aspects of a person. Spirituality concerns a person's relationship with transcendence. Therefore, genuinely holistic health care must address the totality of the patient's relational existence-physical, psychological, social, and spiritual. The literature suggests that many patients would like health professionals to attend to their spiritual needs, but health professionals must be morally cautious and eschew proselytizing in any form. Four general domains for measuring various aspects of spirituality are distinguished: religiosity, religious coping and support, spiritual well-being, and spiritual need. A framework for understanding the interactions between these domains is presented. Available instruments are reviewed and critiqued. An agenda for research in the spiritual aspects of illness and care at the end of life is proposed. IMPLICATIONS Spiritual concerns are important to many patients, particularly at the end of life. Much work remains to be done in understanding the spiritual aspects of patient care and how to address spirituality in research and practice.
Vision-Based Turning Movement Monitoring:Count, Speed & Waiting Time Estimation

This work presents a vision-based vehicle tracking system designed for improved intersection behavior analysis. Motion-based tracking is paired with trajectory analysis methods for accurate turning movement counts of all legs of an intersection using a single camera. Additional behavior analysis methods are implemented to estimate both speed and waiting time at intersections. Improved count accuracy is obtained through cooperation between complementary counting modules and a path reconstruction module is integrated to reconnect broken tracks of the same stationary vehicles at intersections. Experimental results show around 15% improvement in counting accuracy and different behavior of right turns were observed by speed profile and waiting time estimation. Right turns are taken more slowly than other turns and vehicle waiting times are shorter at signalized intersections since they do not always need permission from the signal. We finally show that the waiting time of right turns are directly affected by opposing flows regardless of signal phase.
A biologically-inspired model for dynamic saliency detection

This paper proposes a biologically inspired model for dynamic saliency detection. Our work simulates the visual processing procedure in primary visual cortex, which differs from previous work on spatio-temporal information extraction and feature integration. We compute the spatio-temporal features by a 3D Gabor filters to simulate the response of neurons to different stimulus of their relative receptive fields. To integrate meaningful features, perceptual grouping is introduced to eliminate distracting features. The facilitative and suppressive interactions among neurons are simulated by convolution and half-wave rectification. Effective spatial and motion features are outputs of the stable responses of neurons after the interaction. Dynamic saliency maps are computed from these features as previous work did. We compare our model with four state-of-the-art dynamic saliency detection models on the public available ASCMN database. Our model achieves higher score for AUC, CC and NSS metric.
Generalized Descriptions for the Procedural Modeling of Ancient East Asian Buildings

Many ancient East Asian buildings are noted for their immense beauty and intricate design. We introduce a graphics modeling library based on a generalized procedural description we formulated to describe East Asian architecture. By setting the desired parameters, a user can create a building in any of the many different styles, such as Chinese, Japanese or Korean. Different building types, such as palace halls, commoner houses, temples, pagodas, pavilions, ceremonial gates and fences, are described by our modeling system. This large range of traditional East Asian styles and structures is significantly more than those supported by existing systems.
A Review On Content Delivery Network

With the advent of services and applications such as media streaming over the Internet, speed and reliability have become critical issues for users. Content delivery networks (CDNs) are (overlay) networks that are designed to distribute files to a set of clients. Through approaches such as replication of content at multiple servers (proxies) and redirection of user requests to closer servers, content delivery networks (CDNs) attempt to minimize latency at the user-end while reducing bandwidth consumption and load at the origin server. By sharing the load among various locations closer to the user-end, CDNs can deliver content to users in a timely manner. Content replication enhances robustness so that CDNs can maintain reliable service in case of failures. As streaming media is already a multi-billion dollar industry and will probably be a dominant application in the future, the amount and nature of traffic it generates should be considered during the design of content-delivery networks. The delivery of streaming media causes new problems that did not apply to the distribution of HTTP objects: streaming objects are much larger than web objects and hence create much more traffic [1]. Furthermore, it is no longer possible to assume infinite storage size at the replica locations which makes calculations less trivial [2]. If implemented over existing network architectures, CDNs are a form of overlay network; their design consists of resource allocation decisions and the development of a combination of intelligent routing, performance monitoring and careful caching strategies. It is questionable whether even the best such design is scalable to scenarios where millions of geographically-distributed users are requesting on-demand video. When it is possible to augment or replace the existing underlying network, new challenges present themselves; ideally, the CDN traffic should be explicitly considered during topology design. We plan to address the two challenges of (i) designing a CDN that operates over an existing network with known architectural properties, and (ii) performing the dual design of a metro-area agile all-photonic network (AAPN) [3] and CDN. As a first step, it is valuable to review the solutions proposed in the literature regarding the delivery of multimedia objects. This technical report serves that purpose and is organized as follows. Section II presents the parameters, constraints and various algorithms to solve the replica location and content allocation problem. Section III surveys various traffic models and file popularity distributions. Section IV covers the techniques used for request routing and content delivery. Finally, section V discusses the implementation of content delivery in an AAPN. II. TOPOLOGYDESIGN
Personalized Intervention Program: Tobacco Treatment for Patients at Risk for Lung Cancer.

Background Lung cancer screening and tobacco treatment for patients at high-risk for lung cancer may greatly reduce mortality from smoking, and there is an urgent need to improve smoking cessation therapies for this population. Aims The purpose of this study is to test the efficacy of two separate, sequential interventions to promote tobacco cessation/reduction compared to standard care in smokers considered high-risk for lung cancer. Methods The study will recruit 276 current smokers attending a lung cancer screening clinic or considered high-risk for lung cancer based on age and smoking history across two sites. Patients first will be randomized to either standard tobacco treatment (8 weeks of nicotine patch and five individual counselling sessions) or standard tobacco treatment plus personalized gain-framed messaging. At the 8-week visit, all patients will be re-randomized to receive biomarker feedback or no biomarker feedback. Repeated assessments during treatment will be used to evaluate changes in novel biomarkers: skin carotenoids, lung function, and plasma bilirubin that will be used for biomarker feedback. We hypothesize that personalized gain-framed messages and receiving biomarker feedback related to tobacco cessation/reduction will improve quit rates and prevent relapse compared to standard care. Primary outcomes include 7-day point-prevalence abstinence verified with expired carbon monoxide at 8 weeks and mean cigarettes per day in the past week at 6 months. Conclusions Study findings will inform the development of novel interventions for patients at risk for lung cancer to improve smoking cessation rates.
Trajectory Data Warehouses: Design and Implementation Issues

In this paper we investigate some issues and solutions related to the design of a Data Warehouse (DW), storing several aggregate measures about trajectories of moving objects. First we discuss the loading phase of our DW which has to deal with overwhelming streams of trajectory observations, possibly produced at dierent rates, and arriving in an unpredictable and unbounded way. Then, we focus on the measure presence, the most complex measure stored in our DW. Such a measure returns the number of distinct trajectories that lie in a spatial region during a given temporal interval. We devise a novel way to compute an approximate, but very accurate, presence aggregate function, which algebraically combines a bounded amount of measures stored in the base cells of the data cube. We conducted many experiments to show the eectiveness of our method to compute such an aggregate function. In addition, the feasibility of our innovative trajectory DW was validated with an implementation based on Oracle. We investigated the most challenging issues in realizing our trajectory DW using standard DW technologies: namely, the preprocessing and loading phase, and the aggregation functions to support OLAP operations.
UBIGIouS: a ubiquitous, mixed-reality geographic information system

Moving in virtual environments has become very common. On the one hand there are e.g. non-interactive route guidance systems which are not adequate for pedestrians. On the other hand interactive applications like Second Life fascinate a broad community. This work presents the information system UBIGIouS that combines reality with virtuality in an interactive mixed reality scenario. It is intended to link Virtual Reality Geographic Information Systems with purely virtual interactive applications. For ubiquitous access, users can participate from their homes by standard, stationary PCs or on site using mobile devices like smartphones. By means of visual building recognition capabilities UBIGIouS offers location-based services with or without positioning via the Global Positioning System GPS.
Statistical rate analysis for multi-pair two-way full-duplex relaying with massive antennas

This paper considers a multi-pair two-way relaying network, where multiple pairs of full-duplex users are served via a full-duplex relay with large-scale antennas under the amplify-and-forward protocol. Based on maximum-ratio combining/maximum-ratio transmission (MRC/MRT) processing, an exact achievable rate expression is derived by utilizing the statistical distribution of the channels to detect the desired signals, with the case of a finite number of relay antennas. We show that the exact expression is a tight lower bound of the ergodic rate. Then we obtain its approximate closed-form, which keeps very close to the exact one, especially in large number of antennas. The proposed approximate expression indicates that increasing the relay antenna number can greatly improve the sum rate. In addition, the optimal transmit powers of the users and the relay are obtained in order to maximize the achievable rate. Moreover, we demonstrate that with very large antenna arrays, the two-way full-duplex relaying scheme outperforms both the one-way full-duplex relaying scheme and the two-way half-duplex relaying scheme. Finally, numerical results are presented to verify the accuracy of the analysis.
Encoding extraction as inferences

The analysis of natural-language text involves many different kinds of processes that might be described in multiple ways. One way to describe these processes is in terms of the semantics of their requirements and results. Such a description makes it possible to view these processes as analogous to inference rules in a theorem-proving system. This analogy is useful for metacognition because there is existing theory and infrastructure for manipulating inference rules. This paper presents a representational framework for text analysis processes. We describe a taxonomy of text extraction tasks that we have represented as inference rules. We also describe a working system that encodes the behavior of text analysis components as a graph of inferences. This representation is used to present browsable explanations of text extraction; in future work, we expect to perform additional automated reasoning over this encoding of text analysis processes.
Alpha shape and Delaunay triangulation in studies of protein-related interactions

In recent years, more 3D protein structures have become available, which has made the analysis of large molecular structures much easier. There is a strong demand for geometric models for the study of protein-related interactions. Alpha shape and Delaunay triangulation are powerful tools to represent protein structures and have advantages in characterizing the surface curvature and atom contacts. This review presents state-of-the-art applications of alpha shape and Delaunay triangulation in the studies on protein-DNA, protein-protein, protein-ligand interactions and protein structure analysis.
On the properties of young multiple stars

We present numerical results on the properties of young binary and multiple stellar systems. Our analysis is based on a series of smoothed particle hydrodynamics (SPH) +N-body simulations of the fragmentation of small molecular clouds, which fully resolve the opacity limit for fragmentation. These simulations demonstrate that multiple star formation is a major channel for star formation in turbulent flows. We have produced a statistically significant number of stable multiple systems, with component separations in the range ∼1–103 au. At the end of the hydrodynamic stage (0.5 Myr), we find that ≈60 per cent of stars and brown dwarfs are members of multiples systems, with about a third of these being low-mass, weakly bound outliers in wide eccentric orbits. Our results imply that in the stellar regime most stars are in multiples (≈80 per cent) and that this fraction is an increasing function of primary mass. After N-body integration to 10.5 Myr, the percentage of bound objects has dropped to about 40 per cent, this decrease arising mostly from very low-mass stars and brown dwarfs that have been released into the field. Brown dwarfs are never found to be very close companions to stars (the brown dwarf desert at very small separations), but one case exists of a brown dwarf companion at intermediate separations (10 au). Our simulations can accommodate the existence of brown dwarf companions at large separations, but only if the primaries of these systems are themselves multiples. We have compared the outcome of our simulations with the properties of real stellar systems as deduced from the infrared colour–magnitude diagram of the Praesepe cluster and from spectroscopic and high-resolution imaging surveys of young clusters and the field. We find that the spread of the observed main sequence of Praesepe in the 0.4–1 M⊙ range appears to require that stars are indeed commonly assembled into high-order multiple systems. Similarly, observational results from Taurus and ρ Ophiuchus, or moving groups such as TW Hydrae and MBM 12, suggest that companion frequencies in young systems can indeed be as high as we predict. The comparison with observational data also illustrates two problems with the simulation results. First, low mass ratio (q < 0.2) binaries are not produced by our models, in conflict with both the Praesepe colour–magnitude diagram and independent evidence from field binary surveys. Secondly, very low-mass stars and brown dwarf binaries appear to be considerably underproduced by our simulations.
Glucocorticoids protect against suppression of T cell responses in a murine model of acute ethanol exposure and thermal injury by regulating IL‐6

Previous reports by this laboratory demonstrated that acute alcohol exposure combined with a 15% body surface area dorsal scald injury results in significant reductions in delayed‐type hypersensitivity (DTH) and splenocyte proliferative responses compared to either insult alone. Previous studies by this lab have also shown that these defects are mediated, in part, by increased production of interleukin‐6 (IL‐6). Because both alcohol exposure and thermal injury are known to modulate glucocorticoid (CORT) levels, and CORT regulates IL‐6 gene expression, the relationship between circulating CORT and IL‐6 production in burn + ethanol mice was examined . At 24 and 48 h post‐burn, a positive correlation existed between circulating CORT levels and measurements of cellular immune function. Administration of exogenous CORT to burn + ethanol‐treated mice resulted in significant restoration (to 60% of control) of DTH and splenocyte proliferative responses. This restoration was concomitant with a down‐regulation of circulating and macrophage‐derived IL‐6. The specificity of CORT in modulating these responses was tested by assessing cellular immune function and IL‐6 levels after glucocorticoid receptor blockade with RU486. Taken together, these data strongly suggest that under normal circumstances CORT protects burned mice from severe immune dysfunction, a protection that is not afforded to burn + ethanol‐treated mice. Furthermore, the immune dysfunction observed in burn + ethanol mice may be due to a lack of glucocorticoid attenuation of IL‐6. J. Leukoc. Biol. 64: 724–732; 1998.
Multi-target tracking by discriminative analysis on Riemannian manifold

This paper addresses the problem of multi-target tracking in crowded scenes from a single camera. We propose an algorithm for learning discriminative appearance models for different targets. These appearance models are based on covariance descriptor extracted from tracklets given by a short-term tracking algorithm. Short-term tracking relies on object descriptors tuned by a controller which copes with context variation over time. We link tracklets by using discriminative analysis on a Riemannian manifold. Our evaluation shows that by applying this discriminative analysis, we can reduce false alarms and identity switches, not only for tracking in a single camera but also for matching object appearances between non-overlapping cameras.
A method for watermarking on facial images

Most digital images that are photographed by using smartphones are a facial image that widely published in a social network. These images may be used by using cropping a face that is without permission. This paper proposes a digital image watermarking method in the spatial domain for protection a copyright on the facial image. The face in an image will be evaluated by using phase correlation technique for embedding the watermark. A binary watermark logo is defined to embed in a facial region. Pixels for embedding the watermark are predicted and altered based on the Weber ratio to control the strength of the watermark. Our method does not require an original image to extract the watermark logo. An extracted watermark is computed by subtracting the watermarked pixel with its predicted pixel. The experimental results showed that our method yielded high similarity of the watermark logo when a watermarked image was attacked by the cropping attack and the JPEG compression.
Additive and Multiplicative Notions of Leakage, and Their Capacities

Protecting sensitive information from improper disclosure is a fundamental security goal. It is complicated, and difficult to achieve, often because of unavoidable or even unpredictable operating conditions that can lead to breaches in planned security defences. An attractive approach is to frame the goal as a quantitative problem, and then to design methods that measure system vulnerabilities in terms of the amount of information they leak. A consequence is that the precise operating conditions, and assumptions about prior knowledge, can play a crucial role in assessing the severity of any measured vunerability. We develop this theme by concentrating on vulnerability measures that are robust in the sense of allowing general leakage bounds to be placed on a program, bounds that apply whatever its operating conditions and whatever the prior knowledge might be. In particular we propose a theory of channel capacity, generalising the Shannon capacity of information theory, that can apply both to additive- and to multiplicative forms of a recently-proposed measure known as g-leakage. Further, we explore the computational aspects of calculating these (new) capacities: one of these scenarios can be solved efficiently by expressing it as a Kantorovich distance, but another turns out to be NP-complete. We also find capacity bounds for arbitrary correlations with data not directly accessed by the channel, as in the scenario of Dalenius's Desideratum.
A Smart Surface Simulation Environment

A versatile simulation system is presented, for observing the effects of different algorithmic and mechanical approaches to physical object manipulation via "smart" surfaces -physical machines which use a distributed array of actuators algorithmically controlled to manipulate objects placed upon them. The system presented is a graphical 3D physics sandbox simulator that allows the modeller to include real-world and hardware related constraints such as inter-object collisions and trajectories, mechanical properties, friction, and sensor/actuator reliability, while conducting experiments in an interactive, repeatable and controlled environment.
Progress and Challenges in Research on Cognitive Architectures

Research on cognitive architectures attempts to develop unified theories of the mind. This paradigm incorporates many ideas from other parts of AI, but it differs enough in its aims and methods that it merits separate treatment. In this paper, we review the notion of cognitive architectures and some recurring themes in their study. Next we examine the substantial progress made by the subfield over the past 40 years, after which we turn to some topics that have received little attention and that pose challenges for the research community.