Miracle-dz/UniFAR-FTUs huggingface dataset:
A bio-inspired, asynchronous, time-domain, multispectral imaging system for high dynamic range near-infrared fluorescence image-guided surgery

As surgery has become the standard-of-care for cancer, surgeons have been left underequipped to identify tumors in the operating room, causing many operations to end in positive margins and necessitating secondary treatments to remove remaining tumor tissue. Near-infrared fluorescence image-guided surgery utilizes near-infrared fluorescent markers and near-infrared sensitive cameras to highlight cancerous tissues. Unfortunately, state-of-the-art imaging systems are unable to handle the high dynamic range between strong surgical lighting and weak fluorescent emission and suffer from temperature-dependent co-registration error. To provide a cost-effective and space-efficient imaging system with sufficient dynamic range and no co-registration error, this work analyzes the required dynamic range for a single-sensor imaging system used for near-infrared fluorescence image-guided surgery and reports the development of a single-chip snapshot multispectral imaging system that meets this specification. By monolithically integrating an asynchronous time-domain image sensor and pixelated interference filters, this system achieves a dynamic range of 120 dB without co-registration error in four channels across the visible and near-infrared spectra. The imager can detect less than 100 nM of the FDA-approved fluorescent dye indocyanine green under surgical lighting conditions, making it a promising candidate for image-guided surgery clinical trials.
Towards a sensor for detecting human presence and activity

In this paper, we propose a vision-based system for human detection and tracking in indoor environment allowing to collect higher level information on people activity. The developed presence sensor based on video analysis, using a static camera is ¯rst of all presented. Composed of three main steps, the ¯rst one consists in change detection using a background model updated at di®erent levels to manage the most common variations of the environment. A moving objects tracking based on interest points tracking is then performed. The classi¯cation step ¯nally relies on the use of statistical tools and multiple classi¯ers for the whole body and for the upper-body. The validation protocol, de¯ned by the industrial partners involved in the CAPTHOM project focusing among other things on "Energy Management in Building", is then detailed. Three applications integrated into the CAPTHOM draft ¯nally illustrate how the developed system can also help in collecting useful information for the building management system: occupancy detection and people counting as well as activity characterization and 3D location extend to a wide variety of buildings technology research areas such as human-centered environmental control including heating adjustment and demand-controlled ventilation, but also security and energy e±cient buildings.
QoS Analysis Of Kinematic Effects For Bluetooth HC-05 And NRF24L01 Communication Modules On WBAN System

Wireless Body Area Network (WBAN) consists of a number of sensor nodes that are attached to the human body, and intended for monitor the human body condition. The WBAN system has several wireless communication modules that are used for sending or exchanging data between sensor nodes and gateway nodes or gateway nodes. There are some factors that are used to decide which communication modules should be implemented on WBAN system, including communication efficiency, distance range, power consumption, and the effect of mobility on QoS. In this study, we analyze the impact of the kinematic movement of sensor nodes on QoS parameter of HC-05 Bluetooth and NRF25L01 communication modules, during sending and receiving process among nodes. We assume that the sensor node and gateway node are attached on the limbs to catch the movement. We use Quality of Service (QoS) parameters such as delay, jitter, and packet loss, to analyze the impact of movement on communication modules. Based on the experimental result, it was found that the average value of delay and jitter for booth communication modules was slightly influenced by the speed of the sensor node movement. During the sensor node movement and data transmission, we found that the NRF24L01 module have a lower delay and jitter value than Bluetooth HC-05 module. The percentage of packet loss tends to be stable at 0% value, even though the speed value becomes higher.
Personalized News Recommendation：A Review and an Experimental Investigation

作为新闻报道的一种新格式，联机新闻文章出现在因特网上。 与它的便利和崭新，越来越多的人喜欢在网上读新闻而不是读纸格式新闻报道。 然而，新闻事件的巨大的数量可能以百的率被释放，甚至千每小时。 一个挑战性的问题是怎么 effciently 从最新出版的新闻报道的一个大语料库选择特定的新闻文章推荐给单个阅读器，在选择新闻项目应该匹配读者的读物偏爱像一样的地方可能。 这个问题指个性化的新闻建议。 最近，个性化新闻当因特网在全世界从多重来源提供快存取给即时信息，建议成为了一个有希望的研究指示。 存在个性化的新闻建议系统努力由用户和新闻内容的优点使他们的服务适应单个用户信息。 许多技术被建议了处理个性化的新闻建议，包括基于内容的、合作过滤系统和这二的混合版本。 在这份报纸，我们提供存在的全面调查个性化的新闻 recommenders。 我们讨论位于个性化的新闻建议的问题下面的几个必要问题，并且为性能改进探索可能的解决方案。 进一步，我们在从各种各样的新闻网站获得的许多新闻文章上提供实验研究，并且为个性化的新闻建议评估不同因素的效果。 我们希望我们的讨论和探索将为对个性化的新闻建议感兴趣的研究人员提供卓见。
"Memory work" and recovered memories of childhood sexual abuse: Scientific evidence and public, professional, and personal issues.

The authors review and critically evaluate scientific evidence regarding recovered memories of childhood sexual abuse and discuss the implications of this evidence for professional psychology, public policy, and the law. The discussion focuses primarily on abuse memories recovered through "memory work" by people who previously believed that they were not sexually abused as children. The authors argue that memory work can yield both veridical memories and illusory memories or false beliefs, and they discuss factors that could be used to weigh the credibility of allegations based on recovered memories. The article offers tentative recommendations regarding public education, training and certification of psychotherapists, guidelines for trauma-oriented psychotherapy, research initiatives, legislative actions, and legal proceedings.
Gene Therapy in Urology

Bladder cancer is the 7th most common cancer worldwide. It has a natural history of superficial recurrences and local progression. It is estimated that within 18 months of first diagnosis approximately 50% of patients will have a recurrence (Anderson & Naish 2008). Thus there is a need for frequent monitoring of these patients. In the US the estimated lifetime cost of therapy for bladder cancer patients with non-muscle invasive disease was US $21.03 million based on a Medicare database (Cooksley et al. 2008). The majority of this is spent on surveillance and the treatment of recurrences. Tumors occur on the luminal surface of the bladder and the architecture of the bladder permits topical intravesical therapies. The bladder is isolated from other organs and tissues and intravesical therapy permits contact with the entire internal surface of the bladder with minimal systemic side-effects. The present gold standard therapy for superficial bladder cancers is immunotherapy with Mycobacterium bovis, Bacillus Calmette Guerin (BCG) following local transurethral resection of the bladder tumor (TURBT). BCG induces a mononuclear and neutrophilic infiltrate in the bladder wall which results in an inflammatory response as measured by cytokine production that causes sloughing of both tumor and normal cells (Herr and Morales 2008). The presence of IL-2, IL-8 and IL-18 in the urine of patients has been reported to correlate with response to therapy (Thalmann et al. 1997; Thalmann et al. 2000; Saint et al. 2003). Unfortunately, BCG has several shortcomings: it is a live vaccine and commonly causes side effects and occasionally septicemia. In addition some patients (2042%) do not respond to therapy (Kamat and Lamm 2000). In place of BCG, recombinant cytokines such as IFN-γ, TNF-α, and IL-2 have been used in a number of clinical trials with encouraging results (Glazier et al. 1995; Den Otter et al. 1998; Stavropoulos et al. 2002). However, recombinant cytokines are costly, unstable in urine and have poor permeability
Air pollutant parameter forecasting using support vector machines

Forecasting of air quality parameters is an important topic of atmospheric and environmental research today due to the health impact caused by airborne pollutants existing in urban areas. The support vector machine (SVM), as a novel type of learning machine based on statistical learning theory, can be used for regression and time series prediction and has been reported to perform well with some promising results. The work presented examines the feasibility of applying SVM to predict pollutant concentrations. The functional characteristics of the SVM are also investigated. The experimental comparison between the SVM and the classical radial basis function (RBF) network demonstrates that the SVM is superior to conventional RBF in predicting air quality parameters with different time series.
SyNERGY: An energy measurement and prediction framework for Convolutional Neural Networks on Jetson TX1

There is a huge demand for on-device execution of deep learning algorithms on mobile and embedded platforms. These devices present constraints on the application due to limited hardware resources and power. However, current evaluation studies in existing deep learning frameworks (for example, Caffe, Tensorflow, Torch and others) are limited to performance measurements of these applications on high-end CPUs and GPUs. In this work, we propose "SyNERGY" a fine-grained energy measurement (that is, at specific layers) and prediction framework for deep neural networks on embedded platforms. We integrate ARM’s Streamline Performance Analyser with standard deep learning frameworks such as Caffe and CuDNNv5 to quantify the energy-use of deep convolutional neural networks on the Nvidia Jetson Tegra X1. Our measurement framework provides an accurate breakdown of actual energy consumption and performance across all layers in the neural network while our prediction framework models the energy-use in terms of target-specific performance counters such as SIMD and bus accesses and application specific parameters such as Multiply and Accumulate (MAC) counts. Our experimental results using 9 representative Deep Convolutional Neural Network shows that a multi-variable linear regression model based on hardware performance counters alone achieves an average prediction test error of 8.04 ± 5.96% compared to actual energy measurements. Surprisingly, we find that it is possible to refine the model to predict the number of SIMD instructions and main memory accesses solely from the application’s Multiply-Accumulate (MAC) counts with an average prediction test error of 0.81 ± 0.77% and 17.97 ± 15.29% respectively. This alleviates the need for actual measurements giving a final average prediction test error of 7.08 ± 5.05% using solely the application’s MAC counts as
Log My Dog: Perceived Impact of Dog Activity Tracking

The pet industry is catching up in the wearables market, and pet activity and location trackers are increasingly worn by our furry friends. We report on an empirical study investigating the user perceptions of a popular dog activity tracker. Results show that these trackers have a positive impact on owners' motivation to increase their physical activities with their dogs.
A digital current sensor for PWM inverters

A digital current sensor having the properties of high accuracy, high speed, and low cost for measuring the output current of a pulse-width-modulated (PWM) inverter is described. The digital current sensor forms a closed-loop current sensor with a tracking-type analog-to-digital converter. A prototype digital current sensor of 12 bits is developed and excellent experimental results are shown in the case when an input current of an induction motor (2.2 kW) driven by a PWM inverter is measured by the digital current sensor. <<ETX>>
Mind Bugs: The Origins of Procedural Misconceptions

From the Publisher: As children acquire arithmetic skills, they often develop "bugs" - small, local misconceptions that cause systematic errors. Mind Bugs combines a novel cognitive simulation process with careful hypothesis testing to explore how mathematics students acquire procedural skills in instructional settings, focusing in particular on these procedural misconceptions and what they reveal about the learning process. VanLehn develops a theory of learning that explains how students develop procedural misconceptions that cause systematic errors. He describes a computer program, "Sierra," that simulates learning processes and predicts exactly what types of procedural errors should occur. These predictions are tested with error data from several thousand subjects from schools all over the world. Moreover, each hypothesis of the theory is tested individually by determining how the predictions would change if it were removed from the theory. Integrating ideas from research in machine learning, artificial intelligence, cognitive psychology, and linguistics, Mind Bugs specifically addresses error patterns on subtraction tests, showing, for example, why some students have an imperfect understanding of the rules for borrowing. Alternative explanatory hypotheses are explored by incorporating them in Sierra in place of the primary hypotheses, and seeing if the program still explains all the subtraction bugs that it explained before. Kurt VanLehn is Assistant Professor in the Department of Psychology at Carnegie Mellon University. Mind Bugs is included in the series Learning, Development, and Conceptual Change, edited by Lila Gleitman, Susan Carey, ElissaNewport, and Elizabeth Spelke. A Bradford Book
Automatic content generation for Second Life

Virtual worlds have been performing a role of extreme relevance in storage and share of knowledge. Following that direction, this project aims to make the generation of content to the virtual world of Second Life an easier task. The work was divided in three distinct phases: i) analysis of related work; ii) development of the software; iii) validation of the work. In the first phase some forms of automatic content generation are reviewed and some information sources for the content to generate are identified. In the second and third phases, it is developed and validated with some performance tests, the software for automatic content generation in Second Life's virtual world. Developed software allows automatic creation of roads, buses‟ waypoints as well as some predefined objects.
Comparison of fragment weighting schemes for substructural analysis

Several methods have been described in the literature for the calculation of weights which represent the contribution of fragments to the overall activity or inactivity of molecules which contain them. These weighting schemes are based on fragment occurrence data in training sets of molecules for which the activity is known. This paper reports a comparison of several such schemes (fourteen fragment weights in all), using small datasets for which structural and activity data are available. The comparison reveals that the most effective weight seems to be one derived from research into document retrieval systems (where indexing terms are used to discriminate between relevant and non-relevant documents).
Evaluation of Oral Therapeuthical and Surgical Treatment Needs among Retirement Age Population in Different Countries

Evaluation of Oral Therapeuthical and Surgical Treatment Needs among Retirement Age Population in Different Countries Oral health in connection with quality of life is affected by such functional factors as dental decay and its complications, untreated tooth roots, oral mucosal diseases and inflammations, precancerous diseases, cancers, pain in temporomandibular joints, xerostomia and partially or fully edentulous jaws. It has been noted in literature that among retirement age population the number of remaining teeth has increased and the number of untreated decayed teeth in developed countries for the last 20 years has decreased. Despite this fact the need to improve measures of oral health remains actual in this age group due to increasing prevalence of diagnosed oral diseases and number of extracted teeth and roots. Oral health indicators among retirement age population living in nursing homes in such countries as Canada, USA, UK, Finland, Denmark, Germany, Turkey, Brazil, Australia and Lithuania differ from the same age group indicators among self-dependent old people able to take care of themself. Oral health indicators of nursing homes residents in many countries are significantly worse than oral health indicators of the corresponding age group population. The proposed evaluation data of oral hygiene, periodontal status, DMF-T index, quality of existing and needs of new prosthodontics as well as oral mucosal disorders among retirement age population provides an important insight into therapeutic and surgical treatment provision in different countries.
Invasive Aspergillosis in Allogeneic Stem Cell Transplant Recipients: Increasing Antigenemia Is Associated with Progressive Disease

The kinetics of serum Aspergillus galactomannan, as determined by enzyme-linked immunosorbent assay, was examined in 37 allogeneic stem cell transplant (SCT) recipients treated for invasive aspergillosis (IA). Fifty-eight periods of response ("response episodes") were evaluated. There were 42 response episodes that were considered "treatment failures" and 16 that were considered "good" (that is, complete or partial) responses. At baseline (the first day of each new response episode), the patients who experienced treatment failure and those who had good responses did not differ significantly with regard to median galactomannan index (GMI) value. Thereafter, GMI values significantly increased in the treatment failure group, whereas no significant changes were observed in the good response group (P=.002). An increase in the GMI value of 1.0 over the baseline value during the first week of observation was predictive of treatment failure with a sensitivity of 44%, a specificity of 87%, and a positive predictive value of 94%. We conclude that serial determination of serum GMI values is a useful tool for assessing prognosis of IA in allogeneic SCT recipients during treatment.
A Web-Based Peer Interaction Framework for Improved Assessment and Supervision of Students

: One of the challenges of both traditional and contemporary instructional media in higher education is creating a sustainable teaching-learning environment that ensures continuous engagement of students and provides efficient means of assessing their performance. We present a peer-based framework designed to increase active participation of students in courses administered in both traditional and blended learning settings. Students are continuously engaged in attention-eliciting tasks and are assessed by their peers. The framework allows semi-automated assignment of tasks to students. In completing these tasks, students ask questions, answer questions from other students, evaluate the quality of question-answer pairs and rate answers provided by their peers. We have implemented this framework in several courses and run extensive experiments to assess the effectiveness of our approach. We discuss the results of students’ surveys of this approach, which, in general, has been perceived as useful in achieving better learning outcomes.
Drawing on the archive: using Actor-Network Theory to study historical scenography

ABSTRACT Scholarship on historical scenography has traditionally been limited to studies of extant designs and descriptions, and though wider artistic contexts are often considered, even these broader views tend to overlook connections to seemingly unrelated artistic works or ostensibly non-theatrical issues. In this article, I propose that adding Actor-Network Theory to the range of methodologies deployed in the study of scenography will provide a way to connect it to a larger context and suggest new ways of looking at historical material. Using a drawing by Florentine scenographer Baccio del Bianco for a production at the court of King Philip IV of Spain as a small-scale case study, this article demonstrates the application of the methodology of Actor-Network Theory to a specific work of scenography. In so doing, it suggests a range of possible connections for the drawing beyond its immediate production circumstances and obvious artistic antecedents that bring the work into contact with other social, political, and cultural actors.
Real-Time Sign Predictions of Exchange Rates - A Binary Dynamic Model Averaging Approach

We address the issue of sign predictability in foreign exchange markets for a real-time data set comprising 4 currencies. While most previous studies evaluate point forecast accuracy, we focus on sign predictability. We extend the real-time data set of Sarno and Valente (2009) and analyze whether information embedded in fundamentals contain useful information for direction forecasts of exchange rates. Our Bayesian method accommodates both model uncertainty with respect to included predictive variables and time-variation of model coe¢ cients. Our techniques involves dynamically combining probabilistic forecasts of individual dynamic logistic regression models, allowing for diminishing relevance of older data.
Identification in silico d’éléments de réponse de récepteurs nucléaires impliqués dans le cancer du sein

Two thirds of breast tumours depend on estrogens for their growth. The network of genes mediating the proliferative effect of estrogens is not fully characterized. Putative primary and secondary estrogen target genes were identified with microarray analysis of MCF7 breast cancer cells treated with estradiol (E2) in presence or absence of the protein synthesis inhibitor cycloheximide (CHX). The promoters of the target genes were screened for transcription factor binding sites with a collection of 300 matrix based DNA-binding profiles. Estrogen response elements (EREs) were enriched in the promoters of primary target genes. E2F binding sites were enriched in the promoters of secondary target genes. Similar enrichment was also observed in regions bounds by ERα and E2F1 in ChIP-on-chip experiments for each set of target genes. Retinoic acid (RA) treatment of mammary carcinoma cells inhibits their growth. Putative target genes were identified through microarray analysis of MCF7 cells treated with RA. Enrichment of retinoic acid response elements (RARE) was observed in their promoters after removing the elements found within transposable elements. Although transposable elements mask the enrichment, RARE within primate specific transposable elements are bound in vivo by retinoic acid receptors in the promoters of known target genes BTG2, CASP9 and GPRC5A. Some of the RA target genes in MCF7 cells are also target genes of E2 suggesting that these two molecules exert their effects on cell proliferation in part by opposite action on a common set of genes.