Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal physiology-aware scheduling of clinical states in rural ambulance transport

Remote monitoring in a continuous manner is a key component of ambulance transports for patients with severe diseases. The measurements of the patients, e.g. their heart rate, temperature, level of glucose and many more, should constantly be reported to the hospital with expert doctors to give instructions to people in ambulance so that the patient survives on the way to hospital where more instruments and expert doctors are available in hand. In rural areas, the coverage of communication services are not sufficient for transmission of such signals, so the available bandwidth should be used in an efficient manner, or severe irreparable damages can be caused for the patient. The available bandwidth can come from different sources like satellite communication, 2G/3G/4G communication from different carriers, or other wireless communications available for ambulances specifically. Given that the physiological states of a patient are of different priorities and that the different sources of communications have different bandwidths (and so different round trip time), an important issue is to schedule the right physiological state of the patient to the right communication channel, so that the cost incurred to the patient minimizes. In this paper, we investigate the performance of different scheduling algorithms on our system model, and propose an adaptive communication scheme for remote monitoring of critically ill patients who are receiving ambulance transport in rural areas with poor communication coverage to minimize the instantaneous incurred damage to these patients.
Analysis-synthesis model learning with shared features: A new framework for histopathological image classification

Automated histopathological image analysis offers exciting opportunities for the early diagnosis of several medical conditions including cancer. There are however stiff practical challenges: 1. ) discriminative features from such images for separating diseased vs. healthy classes are not readily apparent, and 2. ) distinct classes, e.g. healthy vs. stages of disease continue to share several geometric features. We propose a novel Analysis-synthesis model Learning with Shared Features algorithm (ALSF) for classifying such images more effectively. In ALSF, a joint analysis and synthesis learning model is introduced to learn the classifier and the feature extractor at the same time. In this way, the computation load in patch-level based image classification can be much reduced. Crucially, we integrate into this framework the learning of a low rank shared dictionary and a shared analysis operator, which more accurately represents both similarities and differences in histopathological images from distinct classes. ALSF is evaluated on two challenging databases: (1) kidney tissue images provided by the Animal Diagnosis Lab (ADL) at the Pennsylvania State University and (2) brain tumor images from The Cancer Genome Atlas (TCGA) database. Experimental results confirm that ALSF can offer benefits over state of the art alternatives.
Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization

Most of the current abstractive text summarization models are based on the sequence-to-sequence model (Seq2Seq). The source content of social media is long and noisy, so it is difficult for Seq2Seq to learn an accurate semantic representation. Compared with the source content, the annotated summary is short and well written. Moreover, it shares the same meaning as the source content. In this work, we supervise the learning of the representation of the source content with that of the summary. In implementation, we regard a summary autoencoder as an assistant supervisor of Seq2Seq. Following previous work, we evaluate our model on a popular Chinese social media dataset. Experimental results show that our model achieves the state-of-the-art performances on the benchmark dataset.
Poster Abstract: Who's Watching Your Child? Exploring Home Security Risks with Smart Toy Bears

The Internet of Things (IoT) can affect the physical safety of a child in addition to their digital safety. Digital safety concerns include what is being recorded and who is monitoring them. IoT devices, like the Fisher Price Smart Toys are designed to play with children of ages 3-8 and entertain them with various activities. This has expanded digital exposure into children's spaces. These toys contain a variety of communication technologies that users are ill-prepared to understand, a myriad of sensors collecting private data, including video, and often rely on inadequate security tools and methodology. This intersection of poor security, invasive sensor data, and proximity to children may put children at risks both online and in-person. In examining the Fisher Price Bear, our researchers were able to both verify that security tools have been implemented to fix network security failures previously found in the toy, but also discovered a security flaw which allows root access to the smart toy, allowing full access to the nose camera and other sensors. Preliminary results are presented in how the operating system can be modified in order to install software so that a modified bear can be controlled remotely. Mitigation education is presented as a critical instrument for self-protection of parents and children in a smart toy environment.
Modifying Spearman’s Attenuation Equation to Yield Partial Corrections for Measurement Error—With Application to Sample Size Calculations

Spearman’s correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman’s equation removes all measurement error from a correlation coefficient which translates into “increasing the reliability of either-or-both of two variables to 1.0. ” In this inquiry, Spearman’s correction is modified to allow partial removal of measurement error from either-or-both of two variables being correlated. The practical utility of this partial correction is demonstrated in its use to explore increasing the power of statistical tests by increasing sample size versus increasing the reliability of the dependent variable for an experiment. Other applied uses are mentioned.
Optimizing Directional Reader Antennas Deployment in UHF RFID Localization System by Using a MPCSO Algorithm

Network planning plays a critical role in the performance of ultra-high frequency radio-frequency identification (UHF RFID) system. Existing works mainly focus on the impact of reader antennas’ location with regard to coverage, quality of service, and cost, rather than localization accuracy. Moreover, since the link budget of stated solutions was investigated based on omnidirectional antennas, most research findings cannot be directly applied to practical directional localization scene. Hence, a novel deployment optimization approach for the directional reader antennas is proposed in this paper. By investigating the gain characteristic of patch antenna and dipole antenna, a propagation model is established in the first place. Then, we build a new network planning model for identifying the placement of a fixed number of reader antennas, which maximizes coverage and minimizes location error as well as interference. Finally, an improved chicken swarm optimization algorithm, termed as MPCSO, is developed for this problem. Simulation results show that the proposed approach achieves much better performance than other classic algorithms.
Forward and Inverse Displacement Analysis of an Actuated Spoke Wheel Robot With Two Spokes and a Tail Contact With the Ground

Intelligent Mobility Platform with Active Spoke System (IMPASS) is a unique wheel-leg hybrid robot that can walk in unstructured environments by stretching in or out three independently actuated spokes of each wheel. The latest prototype of IMPASS has two actuated spoke wheels and one passive tail. In order to maintain its stability, the tail of the robot is designed as a rigid shell with a geometrically convex surface touching the ground. IMPASS is considered as a mechanism with variable topologies (MVTs) due to its metamorphic configurations. Its motions on the ground, such as steering, straight-line walking and other combinations, can be uniformly interpreted as a series of configuration transformations. Among all cases of its topologies, the cases with two spokes and the tail in contact with the ground possess two d.o. f and contribute the most to its ground motion. To fully understand the characteristics of such topologies, the forward and inverse displacement analysis is developed for these cases, with the polynomial equations derived. Numerical solutions from simulation are present to validate their formulation. These results lay the kinematics foundation for the motion monitoring and planning of IMPASS. It also contributes to the design optimization of the tail’s surface geometry to improve its adaptability on uneven terrains.Copyright © 2010 by ASME
Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites

With the rapid growth of networking, cyber–physical–social systems (CPSSs) provide vast amounts of information. Aimed at the huge and complex data provided by networking, obtaining valuable information to meet precise search needs when capturing user intention has become a major challenge, especially in personalized websites. General search engines face difficulties in addressing the challenges brought by this exploding amount of information. In this paper, we use real-time location and relevant feedback technology to design and implement an efficient, configurable, and intelligent retrieval framework for personalized websites in CPSSs. To improve the retrieval results, this paper also proposes a strategy of implicit relevant feedback based on click-through data analysis, which can obtain the relationship between the user query conditions and retrieval results. Finally, this paper designs a personalized PageRank algorithm including modified parameters to improve the ranking quality of the retrieval results using the relevant feedback from other users in the interest group. Experiments illustrate that the proposed accurate and intelligent retrieval framework improves the user experience.
Capacity Bounds for Bandlimited Gaussian Channels With Peak-to-Average-Power-Ratio Constraint

We revisit Shannon’S problem of bounding the capacity of bandlimited Gaussian channel (BLGC) with peak power constraint, and extend the problem to the peak-to-average-power-ratio (PAPR) constrained case. By lower bounding the achievable information rate of pulse amplitude modulation with independent and identically distributed input under a PAPR constraint, we obtain a general capacity lower bound with respect to the shaping pulse. We then evaluate and optimize the lower bound by employing some parametric pulses, thereby improving the best existing result. Following Shannon’S approach, capacity upper bound for PAPR constrained BLGC is also obtained. By combining our upper and lower bounds, the capacity of PAPR constrained BLGC is bounded to within a finite gap which tends to zero as the PAPR constraint tends to infinity. Using the same approach, we also improve existing capacity lower bounds for bandlimited optical intensity channel at high SNR.
Application of perfusion-weighted magnetic resonance imaging as an imaging biomarker in clinical practice: A review from bench to bedside

Despite substantial advances in disease management in the previous years, survival from many common cancers remains poor. It is expected that decision and cost-effectiveness analyses will become an integral component in assessing the indications for initial brain imaging, including the evaluation for metastatic disease, and the efficiency of follow-up of known primary Attention to the mentioned issues and applying PW-MRI provides suitable situation in which one can calculate certain vascular parameters. In our opinion revolutionary progress in the medical imaging techniques provides situations in which brain surgery could be replaced by techniques such as PW-MRI in near future. A tissue and this reduction is due to T2z.ast; as well as presence of the contrast media in the tissue. At the beginning signal intensity will extremely dropped, then it increases to its basic state.
Inference comprehension in text reading: Performance of individuals with right- versus left-hemisphere lesions and the influence of cognitive functions

Background Right-hemisphere lesions (RHL) may impair inference comprehension. However, comparative studies between left-hemisphere lesions (LHL) and RHL are rare, especially regarding reading comprehension. Moreover, further knowledge of the influence of cognition on inferential processing in this task is needed. Objectives To compare the performance of patients with RHL and LHL on an inference reading comprehension task. We also aimed to analyze the effects of lesion site and to verify correlations between cognitive functions and performance on the task. Methods Seventy-five subjects were equally divided into the groups RHL, LHL, and control group (CG). The Implicit Management Test was used to evaluate inference comprehension. In this test, subjects read short written passages and subsequently answer five types of questions (explicit, logical, distractor, pragmatic, and other), which require different types of inferential reasoning. The cognitive functional domains of attention, memory, executive functions, language, and visuospatial abilities were assessed using the Cognitive Linguistic Quick Test (CLQT). Results The LHL and RHL groups presented difficulties in inferential comprehension in comparison with the CG. However, the RHL group presented lower scores than the LHL group on logical, pragmatic and other questions. A covariance analysis did not show any effect of lesion site within the hemispheres. Overall, all cognitive domains were correlated with all the types of questions from the inference test (especially logical, pragmatic, and other). Attention and visuospatial abilities affected the scores of both the RHL and LHL groups, and only memory influenced the performance of the RHL group. Conclusions Lesions in either hemisphere may cause difficulties in making inferences during reading. However, processing more complex inferences was more difficult for patients with RHL than for those with LHL, which suggests that the right hemisphere plays an important role in tasks with higher comprehension demands. Cognition influences inferential processing during reading in brain-injured subjects.
The UTokyo speech synthesis system for Blizzard Challenge 2017

This paper presents a speech synthesis system developed at the University of Tokyo (UTokyo) for the Blizzard Challenge 2017. The task of this year’s challenge is the British English children’s audiobook. We have developed the Deep Neural Network (DNN)-based speech synthesis system including two functions: automated bell-sound removal and an audio code. The developed system has been submitted, and the results of the large-scale subjective evaluation demonstrated the performance of our system.
Thrombotic Regulation From the Endothelial Cell Perspectives.

Thrombosis, the localized clotting of blood that affects arterial or venous circulation, is one of the leading causes of death worldwide.1 Currently used antithrombotic drugs have increased bleeding risk.2,3 Exploring new antithrombotic strategies that preserve physiological hemostasis is under intensive investigation. Classical triad of causative factors leading to thrombosis includes alterations in blood content, alterations in blood flow, and alterations in the vessel wall. Endothelium, the inner most single layer of cells lining the blood vessels, provides a surface for thrombosis formation and critically regulates blood fluidity and homeostasis. As barrier, endothelium separates blood clotting factors from exposure to subendothelial prothrombotic extracellular matrix components. Endothelium also secretes or expresses vasoactive factors that modulate platelet reactivity, coagulation, fibrinolysis, and vascular contractility, all of which contribute to thrombotic formation. Such factors include nitric oxide, prostacyclin, Von Willebrand factor (VWF), thrombomodulin, endothelin, etc. Accumulating evidences show that endothelial cells (ECs) play a pivotal role in modulating thrombosis, highlighting ECs as a potential target for thrombosis control. In this Recent Highlights, we reviewed recent publications in Arteriosclerosis, Thrombosis, and Vascular Biology and other leading journals that are focused on the mechanisms of endothelial regulation of thrombosis and discussed their merits in therapeutic discovery. Arterial thrombosis is commonly initiated by vascular endothelial erosions and ruptures of an atherosclerotic plaque3,4 while venous thrombosis mainly stems from blood stasis.5 Despite these differences, platelet adhesion/activation, and fibrin deposition as the result of coagulation constitute the fundamental processes of thrombus formation.6,7 Platelet activation occurs when they interact with activated ECs (with increased VWF release and selectin expression) via glycoprotein Ib-V-IX complex binding to VWF, or when they expose to subendothelial extracellular matrix components, such as collagen (via glycoprotein VI receptor), in the cases of endothelial injury or plaques …
ICUS, IDUS, CHIP and CCUS: Diagnostic Criteria, Separation from MDS and Clinical Implications

Various myeloid neoplasms, including the myelodysplastic syndromes (MDS), bear a certain risk of progression to secondary acute myeloid leukemia (sAML). The evolution from low-risk to high-risk MDS and finally to sAML suggests that leukemogenesis is a multistep process. However, even before an overt neoplasm, such as an MDS, develops, “prediagnostic” clonal conditions may be identified. With the advent of large-scale genomic screens, such conditions may be detected quite frequently and early in apparently healthy individuals. Recent data suggest that these conditions increase with age and are indeed associated with an increased risk of the occurrence of MDS or another myeloid neoplasm. In other patients, unexplained cytopenia may be detected and may precede MDS. More recently, diagnostic criteria for potential pre-MDS conditions, including idiopathic cytopenia of uncertain significance and clonal hematopoiesis with indeterminate potential, have been proposed. The current article provides an overview of pre-MDS states and related criteria through which these conditions can be discriminated from each other and from MDS. In addition, the clinical implications and management of pre-MDS states are discussed.
Effects of addition of flaxseed to diets of laying hens on some production characteristics , levels of yolk and serum cholesterol , and fatty acid composition of yolk Einfluss des

Foods of animal origin such as meat, milk, and egg take a very important place in human diets due to their nutritional qualities. However, these types of foods containing different amounts of unsaturated/saturated fatty acids and cholesterol are sometimes associated with health problems. The past suggestion that egg cholesterol caused atherosclerosis which in turn results in health complications such as heart attacks and paralyses is arguable at the present (Hansen and Thorling, 1994; Marshall et al., 1994; Cherian and Sim, 1996; Farell, 1997). Cholesterol and fatty acids contents of yolks vary depending especially on dietary manipulations, the genetics of chickens, age, and egg production rate (Beyer and Jensen, 1989; Hargis and Van Elswyk, 1993; Ahn et al., 1995; Meluzzi et al., 1995; Van Elswyk et al., 1997; Scharf and Elmadfa, 1998). In the past, studies have been conducted to reduce the cholesterol level of eggs. One idea to reduce egg cholesterol is to change the fatty acid (FA) composition of the diet and by this of the egg yolk reducing the cholesterolaemic effect. The hypocholesterolaemic effects of mono unsaturated fatty acids, e.g. oleic acid (OA), and poly unsaturated fatty acids, e.g. linoleic acid (LA), have been discussed for a long time (Grundy, 1986). In recent years researches have been focused on W-3 polyunsaturated fatty acids (PUFA) such as a-linolenic acid (LnA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (Dha) (Watkins, 1992; Farrell, 1993, 1997; Hansen and Thorling, 1994; Blanch and Grashorn, 1996; Cherian and Sim, 1996). In literature it was shown that diets rich in W-3 PUFA reduced blood cholesterol levels in rats (Caston and Leeson, 1990; Jiang et al., 1991; Watkins, 1992; Ferrier et al., 1995; Scheideler and Froning, 1996). Comparable data on layers are lacking. Therefore, this experiment was carried out to determine the effects of addition of flaxseed (FS) to laying hens’ diets on some performance characteristics, yolk and blood cholesterol levels, and fatty acid compositions of egg yolks.
A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003

In this paper, we develop an ecological, multi-level model that can be used to study the evolution of emerging technology. More specifically, by defining technology as a system composed of a set of interacting components, we can build upon the argument of multi-level density dependence from organizational ecology to develop a distribution-independent model of technological evolution. This allows us to distinguish between different stages of component development, which provides more insight into the emergence of stable component configurations, or dominant designs. We validate our hypotheses in the biotechnology industry by using patent data from the USPTO from 1976 to 2003.
Yeasts in floral nectar: a quantitative survey.

BACKGROUND AND AIMS One peculiarity of floral nectar that remains relatively unexplored from an ecological perspective is its role as a natural habitat for micro-organisms. This study assesses the frequency of occurrence and abundance of yeast cells in floral nectar of insect-pollinated plants from three contrasting plant communities on two continents. Possible correlations between interspecific differences in yeast incidence and pollinator composition are also explored. METHODS The study was conducted at three widely separated areas, two in the Iberian Peninsula (Spain) and one in the Yucatán Peninsula (Mexico). Floral nectar samples from 130 species (37-63 species per region) in 44 families were examined microscopically for the presence of yeast cells. For one of the Spanish sites, the relationship across species between incidence of yeasts in nectar and the proportion of flowers visited by each of five major pollinator categories was also investigated. KEY RESULTS Yeasts occurred regularly in the floral nectar of many species, where they sometimes reached extraordinary densities (up to 4 x 10(5) cells mm(-3)). Depending on the region, between 32 and 44 % of all nectar samples contained yeasts. Yeast cell densities in the order of 10(4) cells mm(-3) were commonplace, and densities >10(5) cells mm(-3) were not rare. About one-fifth of species at each site had mean yeast cell densities >10(4) cells mm(-3). Across species, yeast frequency and abundance were directly correlated with the proportion of floral visits by bumble-bees, and inversely with the proportion of visits by solitary bees. CONCLUSIONS Incorporating nectar yeasts into the scenario of plant-pollinator interactions opens up a number of intriguing avenues for research. In addition, with yeasts being as ubiquitous and abundant in floral nectars as revealed by this study, and given their astounding metabolic versatility, studies focusing on nectar chemical features should carefully control for the presence of yeasts in nectar samples.