Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Driven Modeling of Signal Strength Distributions for Localization in Cellular Radio Networks (Datengetriebene Modellierung von Feldstärkeverteilungen für die Ortung in zellulären Funknetzen)

Abstract In this article, we propose a novel approach to solving the localization problem in cellular networks, with a focus on indoor environments. The goal is to estimate a mobile user's position, based on measurements of signals received from different base stations. Our solution uses the Progressive Bayes estimation framework to model the distribution of signal measurements, as obtained in a series of calibration measurements. In the localization step, we compute the full probability density over the user position. We also show that user motion models can be easily integrated in our solution.
Complement Component 3 Regulates IFN-α Production by Plasmacytoid Dendritic Cells following TLR7 Activation by a Plant Virus–like Nanoparticle

The increasing use of plant viruses for the development of new vaccines and immunotherapy approaches poses questions regarding the mechanism by which the mammalian immune system recognizes these viruses. For example, although natural Abs (NA) and complement are key components of the innate immune system involved in the opsonization, phagocytosis, and destruction of microorganisms infecting mammals, their implication in plant virus recognition and immunogenicity is not well defined. In this study, we address the involvement of NA and the complement system in the activation of innate immunity through engagement of TLR7 with papaya mosaic virus (PapMV)-like nanoparticles. We demonstrate that NA, although binding to PapMV, are not involved in its recognition by the immune system. On the other hand, C3 strongly binds to PapMV nanoparticles and its depletion significantly reduces PapMV’s interaction with immune cells. Unexpectedly, however, we observed increased immune cell activation following administration of PapMV to complement-depleted mice. TLR7 activation by PapMV in the absence of C3 induced higher IFN-α production, resulting in superior immune cell activation and increased immunotherapeutic properties. In conclusion, in this study we established the involvement of the complement system in the recognition and the phagocytosis of PapMV nanoparticles and identified an unsuspected role for C3 in regulating the production of IFN-α following TLR7 activation.
Cooperative Detection-Assisted Localization in Wireless Networks in the Presence of Ranging Outliers

Location-aware wireless networks can provide precise location information in harsh environments, however, which is only possible when all nodes are well-functioning. In this paper, we propose algorithms and analyze the performance limits for both non-cooperative and cooperative localization networks in the presence of ranging outliers. Especially, we show that the localization performance can be boosted by using the cooperative outlier detection scheme. An algorithm based on expectation-maximization is proposed for non-cooperative localization networks, while a variational message passing-based algorithm is proposed for the cooperative counterparts. Performance limits are investigated using Cramér–Rao lower bound. Further inspection on the performance limits confirms the performance gain from the cooperative detection scheme. Stochastic geometric analysis is also carried out to account for the stochastic nature of wireless networks, as well as to provide simpler expressions and additional insights. Simulation results corroborate the analytical results, and show that both of the proposed algorithms are capable of attaining the corresponding performance limits at a significantly reduced computational cost compared with existing algorithms.
Cognitive Skills Underlying Driving in Patients Discharged Following Self-Poisoning With Central Nervous System Depressant Drugs

Background: Central nervous system–depressant (CNS-Ds) drugs can impair cognitive functions and driving. They are also the most common drugs taken in overdose in hospital-treated episodes of self-poisoning. In Australia most of these patients are discharged within 48 h, while they still have possible subclinical drug effects. We aimed to determine whether patients treated for self-poisoning with CNS-Ds are impaired in the Trail-Making Test (TMT, parts A and B), a neuropsychological test that is known to correlate with driving performance. Methods: This study was a conducted from November 2008 to April 2011 in a referral center for poisonings in New South Wales, Australia. One hundred seven patients discharged from the clinical toxicology unit following treatment for self-poisoning of CNS-Ds (benzodiazepines, atypical antipsychotics, or opioids) and a control group of 68 discharged following self-poisoning of non-CNS-depressant drugs (acetaminophen or nonsedating antidepressants) were tested with the TMT (parts A and B). Due to the known association of impaired TMT with driving impairment and increased risk of traffic accidents, performance less than the 10th percentile for age was defined as significant impairment in each part of the TMT. The odds ratio (OR) for impairment in each part was calculated in multivariate logistic regression (MLR) models adjusted for gender, education, IQ, and the presence of a major psychiatric illness. A secondary MLR analysis was conducted only for those patients (78 CNS-D and 54 control group participants) who were directly discharged home, after excluding those who were transferred for further psychiatric care. Results: The odds of impairment in the CNS-D group was 2.8 times that of the control group on the TMT-A (38 [35.5%] vs. 11 [16.2%]: adjusted OR = 2.76, 95% confidence interval [CI]: 1.28–5.97), and 4.6 times on the TMT-B (67 [62.6%] vs. 22 [32.4%]: adjusted OR = 4.63, 95% CI: 2.06–10.42). The results were similar in the subgroup of patients discharged home, and the odds of impairment in the CNS-D group was 3.3 times that of the control group on the TMT-A (25 [32.1%] vs. 7 [13.0%]: adjusted OR = 3.30, 95% CI: 1.28–8.52), and 3.6 times on the TMT-B (46 [59.0%] vs. 17 [31.5%]: adjusted OR = 3.64, 95% CI: 1.44–9.20). TMT-B impairment in the CNS-D group remained significant even after adjusting for TMT-A performance. Conclusions: Patients with CNS-D overdose may have significant impairment in cognitive skills underlying driving at the time of discharge from hospitals. Clinicians should warn these patients that their driving skills might still be impaired, even if they are considered clinically recovered and advise them not to drive during the first 1 to 2 days following discharge.
About Face 3: the essentials of interaction design

From the Publisher: Dear Reader, In the eight years since this book was first published, the ideas that seemed do radical at first have become standard models across the industry. Many practicioners have adopted them and seen dramatic improvements in their products. This book would not have been possible without the commitment of the many organizations over the past decade that hired Cooper, my design consulting company. They demonstrated a great measure of self-confidence to break from the pack. By the same token, the many brilliant and talented people who have worked at Cooper have pushed the limits of my original thinking far beyond where I started. They have put their professional reputations on the line to prove that there is a higher standard and better ways to achieve it. In this significantly revised and expanded edition of the book, Robert Reimann and I have rewritten and reorganized every page. Together we have: Updated examples to reflect the current state of the art, and included more examples from Cooper design solutions Included references to recent technology and industry developments Added an entirely new section covering Cooper's Goal-Directed Design methods such as personas, goals, and scenarios in detail Added new chapters on visual design, as well as interaction design issues for embedded systems and the Web Added a bibliography of design reference sources Thanks for joining me in the pursuit of better software, happier programmers and designers, more successful businesses, and extremely satisfied users. Sincerely, Alan Cooper Founder & Chairman of the Board Cooper Author Biography: Alan Cooper is a pioneering software inventor, programmer, designer, and theorist. He is credited with creating what many regard as the first serious business software for microcomputers, and is widely known as the "Father of Visual Basic. " For the last decade, Alan's interaction design consulting firm, Cooper, has helped companies invent powerful, usable, desirable software and improve digital product behavior through the use of Alan's unique methodology  the Goal-Directed process. A cornerstone of this method, the use of personas, has been widely adopted since it was first described in Alan's second book, The Inmates are Running the Asylum. A best-selling author and popular speaker, Alan is a tireless advocate for integrating design into business practice and for humanizing technology. Robert Reimann has spent the past 15 years pushing the boundaries of digital products as a designer, writer, lecturer, and consultant. He has led dozens of design consulting projects for startups and Fortune 500 clients alike. Upon joining Cooper in 1996, Robert led the development and refinement of many Goal-Directed Design methods described in About Face 2.0. He has lectured at major universities and to international industry audiences, and he is a member of the industry advisory board for the Institute of Design at the University of California, Berkeley.
Towards Context-aware Adjective Learning

Context, which can be defined as the interrelated conditions in which something exists or occurs, is important for interpreting the environment, especially in determining which concept an object belongs to. In this paper, we are interested in how such context information can be used by a robot for constructing concepts that correspond to adjectives in language (i.e., adjective concepts). This is not only important for robot’s “cognition” but also critical for natural human-robot communication which requires the robot to understand what an object means for us in the environment. For this reason, we are using adjective labels that eight participants assigned for objects in isolation and for objects in a context. In the first phase of the trainings, the robot iCub interacts with a set of objects and learns affordances by applying the behaviors in its behavior repertoire. After that, we evaluate appearance and affordance information of objects in isolation as well as in relation to other objects’ attributes for adjective concepts using the adjective labels from humans. The results show that iCub can predict the adjectives of an object in a twoobject environment with a confidence comparable to humans.
Intensity of Anticoagulation and Clinical Outcomes in Acute Cardioembolic Stroke: The Fukuoka Stroke Registry

Background and Purpose— The relationship between the intensity of anticoagulation at the onset of acute cardioembolic stroke and clinical outcome after stroke is unclear. Here, we elucidated the relationship between prothrombin time–international normalized ratio (PT-INR) values on admission and clinical outcomes in patients with acute cardioembolic stroke. Methods— A total of 602 patients from the Fukuoka Stroke Registry in Japan who had been treated with warfarin but developed cardioembolic stroke were enrolled. The patients were classified into 3 groups according to their PT-INR values on admission: PT-INR <1.50, 411 patients; PT-INR 1.50 to 1.99, 146 patients; and PT-INR ≥2.00, 45 patients. The associations between PT-INR categories and severe neurological deficits (National Institutes of Health Stroke Scale ≥10) on admission and poor functional outcome (modified Rankin scale 4–6) at discharge were investigated using a logistic regression analysis. Results— Neurological deficits on admission were less severe, and functional outcome at discharge was more favorable as the PT-INR level on admission increased. The multivariate analysis revealed that severe neurological deficits were inversely associated with PT-INR on admission (PT-INR 1.50–1.99: odds ratio, 0.66; 95% confidence interval, 0.43–1.00; PT-INR ≥2.00: odds ratio, 0.41; 95% confidence interval, 0.20–0.83; compared with a reference group of PT-INR <1.50). Poor functional outcome was less likely in patients with PT-INR ≥2.00 (odds ratio, 0.20; 95% confidence interval, 0.06–0.55) after adjustment for confounders. Conclusions— Prestroke PT-INR ≥2.0 is associated with favorable clinical outcomes after acute cardioembolic stroke.
A NEED-AWARING MULTI-AGENT APPROACH FOR AD HOC NEED IDENTIFICATION AND GROUP FORMATION IN NOMADIC COMMUNITY COMPUTING

Researchers have proposed community computing for facilitating both group formation and group decision making. However, legacy community computing systems do not support group needs identification for ad hoc group formation, which is a key feature of ubiquitous decision support systems and services. In this article, we describe a multi-agent-based methodology that both enables nomadic community computing and supports ad hoc needs identification and group formation. Our approach uses needs awareness through a Rescorla-Wagner model of association theories and need reasoning by rough set theory. With a focus on supporting decision making within a relatively small-sized group of multiple individuals in a community, the methodology addresses the following three characteristics: (1) ad hoc group formation; (2) context-aware group needs identification; and (3) implementation of mobile devices working indoors and outdoors. We develop a prototype system, NAMA-US, to show the feasibility of the ideas proposed in this article.
Motivations, Expectations, and Experiences of Labiaplasty: A Qualitative Study.

BACKGROUND The demand for labiaplasty has increased rapidly over recent years; however, very little is known about the experiences women have undergoing this surgery or the subsequent effects it has on their well-being. OBJECTIVES To explore women's reasons for undergoing labiaplasty, their expectations, and preoperative and postoperative experiences. METHODS One-on-one semi-structured interviews were conducted with 14 adult women who had undergone a labiaplasty procedure. The women were asked about their reasons for having labiaplasty, the processes of accessing and undergoing surgery, and how various aspects of their lives were influenced after having surgery. The interviews were audio recorded then transcribed verbatim. The interview transcripts were analyzed using thematic analysis owing to the exploratory nature of the study. RESULTS Themes reflecting "media influence," "negative commentary," "physical vs appearance reasons," "satisfaction with surgery," and "sexual well-being" emerged from the analyses. Online media representations of labial appearance, and negative past experiences, primarily sexual in nature, contributed to women's concerns about their labial appearance. Issues of physical discomfort were also common and were sometimes emphasized to potentially legitimize women's requests for surgery. Most women were generally very satisfied with their surgical results, although some noted that their labia were not as small and/or symmetrical as they had expected. Most women reported significant improvements in their sexual well-being after surgery, however, some noted that their emotional discomfort around sexual intercourse had not improved. CONCLUSIONS These new insights into why women seek labiaplasty, their experiences and outcomes may assist clinicians in enhancing their communication with prospective patients. LEVEL OF EVIDENCE 4 Therapeutic.
Effect of Music on Anxiety of Women Awaiting Breast Biopsy

Abstract The authors investigated the effect of music on the state anxiety of a sample of 20 patients awaiting breast biopsy at a suburban medical facility. The patients were assigned alternately to either the control or experimental group. The individuals in the experimental group were given a 20-minute music-based intervention in a preoperative holding area, whereas the patients in the control group received the customary preoperative care. Clinicians measured blood pressure, heart rate, and respiration in both groups of patients, and the participants completed the State portion of the self-administered State-Trait Anxiety Inventory (STAI). After the patients completed the 20 minutes of music or of preoperative care without music, clinicians again measured the participants' vital signs and the patients completed the STAI. The authors' findings indicated that the posttest state anxiety and respiratory rates of the patients in the experimental group were significantly lower than those of the patients in the control group.
Social volunteer computing

While both volunteer computing and social networks have proved successful, the merging of these two models is a new field: Social Volunteer Computing. A Social Volunteer Computing system utilizes the relationships within a social network to determine how computational resources flow towards tasks that need to be completed, and the results of these computations are added back into the social network as content. Such a system will provide scientists and artists a new facility to obtain computational resources and disseminate their work. RenderWeb 2.0, a prototype Social Volunteer Computing system, is introduced that allows animations created in Blender to be distributed and rendered within Facebook.
3D-2D ultrasound feature-based registration for navigated prostate biopsy: A feasibility study

The aim of this paper is to describe a 3D-2D ultrasound feature-based registration method for navigated prostate biopsy and its first results obtained on patient data. A system combining a low-cost tracking system and a 3D-2D registration algorithm was designed. The proposed 3D-2D registration method combines geometric and image-based distances. After extracting features from ultrasound images, 3D and 2D features within a defined distance are matched using an intensity-based function. The results are encouraging and show acceptable errors with simulated transforms applied on ultrasound volumes from real patients.
Towards a modular, robust, and portable sensing platform for biological and point of care diagnostics

The ability to conveniently and immediately test and diagnose in a diverse and rapidly changing environment is critical for field diagnostics. Smart biomedical sensors employ many different diagnostic/therapeutic methodologies; however, an ideal system would include the ability for results to be shared instantaneously with all members of the team through a software interface. We discuss our efforts towards the development and use of a robust, mobile platform (Android-based smart phone) that incorporates stable molecular recognition elements in sensor development. The inexpensive, compact, robust, archival, and portable design is ideal for rapid field diagnostics.
Combined model-based sliding-mode controller for a three-phase voltage source inverter fed induction motor drive

The chattering phenomenon associated with the use of Sliding Mode Controllers (SMC) is considered a major drawback of the robust controllers. Ideally, SMCs are to exhibit infinite switching frequency but this is always compromised by the existence of parasitic dynamics which add to the input relative degree of the system and leads to high but finite switching frequency. The performance and robustness of the controller can be closely linked to the resulting switching frequency. Often, when controlling the speed of induction motors, SMCs are applied and used to generate what is assumed to be smooth control signals. These control signals are used as modulation inputs for various carrier based modulation schemes. In doing so, the sliding action of the controller is disrupted as the SMC's switching frequency is limited by the finite carrier frequency of the modulation process. This effect is carefully analysed in this paper. An alternative is considered in this paper where SMCs are applied to the inner most control loop without the use of any carrier based modulation schemes.
Complexity Science and Leadership in Healthcare

The emerging field of complexity science offers an alternative leadership strategy for the chaotic, complex healthcare environment. A survey revealed that healthcare leaders intuitively support principles of complexity science. Leadership that uses complexity principles offers opportunities in the chaotic healthcare environment to focus less on prediction and control and more on fostering relationships and creating conditions in which complex adaptive systems can evolve to produce creative outcomes.
A Position-Based QoS Routing Scheme for UWB Ad-Hoc Networks

Ultra-wideband (UWB) wireless communication is a promising spread spectrum technology that supports very high data rates and provides precise position information of mobile users. In this paper, we present a position-based quality-of-service (QoS) routing scheme for UWB ad-hoc networks. The scheme applies call admission control and temporary bandwidth reservation for discovered routes, taking into consideration the medium access control (MAC) interactions. Via cross-layer design, it exploits UWB advantages by using the position information in routing and bandwidth reservation. Simulation results demonstrate that the proposed routing scheme is effective in end-to-end QoS support.
A Markov Chain Monte Carlo based rigid image registration method

We propose a Monte Carlo Markov Chain (MCMC) based method for image registration. We formulate the image registration problem within a Bayesian framework and generate samples from the resulting posterior density of the registration parameters using MCMC. Thus, posterior density is characterized through the samples that are drawn with the MCMC principle. When the posterior density is multimodal, samples from different modes of the posterior lead to different and meaningful solutions for the image registration problem. We perform experiments on pairs of test images which may admit multiple registration solutions. Preliminary results demonstrate the potential of the proposed approach.
An efficient heuristic algorithm for channel assignment problem in cellular radio networks

This paper presents an efficient heuristic algorithm for the channel assignment problem in cellular radio networks. The task is to find channel assignment with minimum frequency bandwidth necessary to satisfy given demands from different nodes in a cellular network. At the same time the interference among calls within the same cell and from different neighboring cells are to be avoided, where interference is specified as the minimum frequency distance to be maintained between channels assigned to a pair of nodes. The simplest version of this problem, where only cochannel interferences are considered, is NP-complete. The proposed algorithm could generate a population of random valid solutions of the problem very fast. The best among them is the optimum or very near to optimum solution. For all problems with known optimal solutions, the algorithm could find them. A statistical estimation of the performance of the proposed algorithm is done. Comparison with other methods show that our algorithm works better than the algorithms that we have investigated.