Miracle-dz/UniFAR-FTUs huggingface dataset:
Toll-like Receptor 4 Antagonist (e5564) Prevents the Chronic Airway Response to Inhaled Lipopolysaccharide (lps)

Although chronic inhalation of endotoxin or lipopolysaccharide (LPS) causes all of the classic features of asthma, including airway hyperreactivity, airway inflammation, and airway remodeling, the mechanisms involved in this process are not clearly understood. The objective of this study was to determine whether intratracheal treatment with lipopolysaccharide antagonist (E5564, a lipid A analog) prevented the development of chronic endotoxin-induced airway disease in a mouse model of environmental airway disease. Pretreatment with 10 and 100 µg of E5564 was found to inhibit the airway response (hyperreactivity and inflammation) for up to 48 hours after the administration of the compound. Repeated dosing with 50 µg of E5564 intratracheally did not cause any measurable toxicity. Therefore, in a chronic experiment, mice were treated with either E5564 (50 µg) or vehicle 3 times weekly for 5 weeks and simultaneously daily exposed to either LPS (4.65 ± 0.30 µg/m 3) or saline aerosol. E5564 was effective in decreasing the airway hyperreactivity to methacholine, the airspace neutrophilia, the interleukin-6 in the lung lavage fluid, and the neutrophil infiltration of the airways 36 hours after five weeks of LPS inhalation. Less collagen deposition was observed in the airways of E5564-treated mice compared to vehicle-treated mice after a four-week recovery period. Our results indicate that E5564, a toll-like receptor 4 antagonist, minimizes the physiologic and biologic effects of chronic LPS inhalation, suggesting a therapeutic role for competitive LPS antagonists in preventing or reducing endotoxin-induced environmental airway disease. Abbreviations used in this paper:
Generalized Proportionally Fair Scheduling for Multi-User Amplify-and-Forward Relay Networks

Providing ubiquitous very high data rate coverage in next generation wireless networks is a formidable goal, requiring cost-effective radio access network (RAN) devices, such as multi-user enabled amplify- and-forward (AF) relays, and fair radio resource management (RRM). To further this goal, we investigate multi-user enabled AF relays which multiplex user's data in orthogonal frequency division multiple access (OFDMA). These relays are cost-effective, simpler to implement, and introduce less delay in comparison to other relay based routers. We devise a generalized proportionally fair (GPF) RRM framework for multi-user enabled AF relays. In GPF scheduling a single parameter is used to gradually change schedules from throughput optimal to proportionally fair. We formulate the GPF scheduling problem and due to its complexity devise a low complexity heuristic to solve it. We evaluate the performance of the heuristic with extensive simulations and show that the heuristic performs well.
On Clustered Statistical MIMO Millimeter Wave Channel Simulation

The use of mmWave frequencies is one of the key strategies to achieve the fascinating 1000x increase in the capacity of future 5G wireless systems. While for traditional sub-6 GHz cellular frequencies several well-developed statistical channel models are available for system simulation, similar tools are not available for mmWave frequencies, thus preventing a fair comparison of independently developed transmission and reception schemes. In this paper we provide a simple albeit accurate statistical procedure for the generation of a clustered MIMO channel model operating at mmWaves, for both the cases of slowly and rapidly time-varying channels. Matlab scripts for channel generation are also provided, along with an example of their use.
Performance of Single Carrier Cyclic Prefix Versus OFDM Over Wideband HF Ionospheric Channel

This paper presents a comparative study between orthogonal frequency division multiplexing (OFDM) and the single carrier with cyclic prefix (SCCP) communication systems over wideband high frequency (HF) ionospheric communication channel. HF communication has the advantages of long distance coverage, low cost, and simplified infrastructure. Meanwhile, the limited bandwidth (3KHz) of the standard HF channels restricts the operation of modern applications which requires relatively higher data rates. In an attempt to evaluate the utility of HF for high data rate applications, this paper considers a wideband HF communication channel with bandwidth of 24KHz modelled by a well-established channel model developed by Vogler and Hoffmeyer in 1993. Vogler and Hoffmeyer model parameters are driven from a practical experiment took place in Thailand with a 612Km HF link with a centre frequency of 6.6MHz. The model is shown to be valid for HF channels with bandwidth up to 1MHz. Traditional OFDM systems are bandwidth efficient and they can achieve high rates, meanwhile, they suffer from peak to average power ratio (PAPR) which becomes more significant in high power HF communication systems. On the other hand, SSCP is one communication approach suitable for wideband channels which does not suffer from PAPR problem. In addition, it is also less sensitive to carrier frequency offset.Simulation results show that OFDM offers 1-3dB improvement over SCCP for the same BER for uncoded data while coded data has the same result but with overall 3dB improvement. In addition, it offers 0.05 up to 0.5 bits per Hz per channel use in terms of the maximum achievable bit rate. Hence, our results show that for the considered channel parameters, OFDM outperforms SCCP in terms of both bit error rate (BER) performance and maximum achievable bit rate. These results open the door for further exploitation of OFDM communication over wideband HF communication channel.
Sensor Interoperability of Fingerprint Segmentation: An Empirical Study

Fingerprint segmentation is an important pre- processing step before feature extraction. Quality of fingerprint images acquired by various sensors of different types is distinctive. Fingerprint images from one data base have significantly distinct distribution from another in CMV feature space. The impact of sensor interoperability on fingerprint segmentation has received limited attention. This paper provides an empirical study on sensor interoperability of fingerprint segmentation. We find that a well trained fingerprint segmentation model on a single data set usually has higher accuracy on its homogenous testing data set, while lower accuracies on its heterogeneous testing data sets; and when a model trained on combined fingerprint data bases acquired from several sensors, the more training data sets to be combined, the more corresponding testing data sets achieve higher accuracies.
Misinformation and Mass Audiences

Ever since the 2016 U.S. presidential election, the term “fake news” has become seemingly inescapable. Because the term lacks a consensus definition, it increasingly operates as a stand-in for whatever someone finds most alarming within today’s news media environment. It’s been used on Twitter by politicians to denounce credible yet embarrassing news stories, and by wary journalists to refer to serial news fabricators. Complicating matters further is the fact that concern about fake news currently outweighs empirical research into both its production and impact. Consequently, it’s a term that provokes alarm and confusion, making it one in dire need of a comprehensive review. That is a long way of saying that Misinformation and Mass Audiences could not have come along at a better time. The book, edited by Brian G. Southwell, Emily A. Thorson, and Laura Sheble, offers a wide variety of perspectives on fake news from a thoughtfully assembled, interdisciplinary group of scholars. These disciplines include communication research, public health, psychology, political science, environmental studies, and information science. Considering the gulf between how little we know about the causes and effects of fake news and the seemingly universal panic over its influence on everything from journalism to democracy, it is enormously helpful to have these insights from a variety of backgrounds and methodologies collected into a single volume. There are a number of other smart decisions the editors of and authors within this collection have made: first, as is apparent by its title, the term “fake news” rarely appears at all. In its place is “misinformation. ” This may seem like an inconsequential distinction (and who knows, maybe it wasn’t even intentional), but it isn’t. Forgoing the more fashionable term for the more timeless “misinformation” allows
A Color Mask and Trained Image Set for the Creation of New Technique for Indoor Robotic Navigation

Among the different methods used in the indoor navigation of robotic systems image processing techniques are widely used. This research was focused to explore a new dimension of image capturing and matching in order to enhance the indoor navigation methods of moving robots. The color extraction were carried out by performing the logical operation between a color mask and the original image. The color mask would be created considering the bitwise range analysis. The real comparison has been received analyzing the histograms received from color extraction and the trained source image.
Radiological Errors: Implications and Causes with a Focus on Mammographic Misdiagnosis

Radiological diagnostic errors may have serious clinical and medico-legal implications. Previous work has reported that radiology has a reasonable incidence of error, a number of which are resulted from observer mistakes. The radiologists’ interaction with the image is critical, and studying the types of diagnostic errors to improve patient and radiologist wellbeing, reduce cost and improve the public perception of the health care system is well justified. Therefore, the aim of current review is to consider the primary types of diagnostic errors in radiology, as well as their causes and implications with a focus on mammographic misdiagnosis.
UVA–VU SFM SEMINAR STOCHASTICS FOR MASTER STUDENTS

Below is a description of the proposed topics for the seminar, including an outline of what should be covered and references to some literature. We have given a rating of how difficult we think each topic is, on a scale from ? (very easy) to ? (advanced). It is important to note that the given description is only a suggestion for what you could discuss. It is your task to make this into an attractive and coherent series of lectures. Feel free to change the order of the suggested topics, to add or omit some topics, to look for complementary literature, etc.
A Dynamic Window-Constrained Scheduling Algorithm for Multiprocessor Real-Time Systems

Advances in computing applications in recent years have prompted the demand for more flexible scheduling models and multiprocessor scheduling algorithm. The DWCS (dynamic window-constrained scheduling) is a flexible scheduling algorithm. In the scheduling algorithms on multiprocessor real time systems, the heuristic algorithm is an important algorithm and a known heuristic algorithm is myopic algorithm [1]. The performance of the myopic algorithm is greatly based on heuristic functions. In this paper, we present an improved heuristic algorithm, which has a new heuristic function for window-constrained real-time tasks. The improved algorithm considers not only the deadlines and the resource requirements of a task, but also the processing time of the task. The most important metric for real-time scheduling algorithms is scheduling success ratio. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the scheduling success ratio of the improved heuristic algorithm is superior to that of myopic algorithm.
On Regularization , Formulation and Initialization of theActive Contour Models ( Snakes )

In snake formulation, large regularization enhances the ro-bustness against noise and incomplete data, while small values increase the accuracy in capturing boundary variations. We present a local minimax criterion which automatically determines the optimal regularization at every locations along the boundary with no added computation cost. We also modify existing energy formulations to repair deeciencies in internal energy and improve performance in external energy. This yields snakes that contain Hough transform as a special case. We can therefore initialize the snake eeciently and reliably using Hough transform.
Time-Course of the Effects of QSYQ in Promoting Heart Function in Ameroid Constrictor-Induced Myocardial Ischemia Pigs

We aim to investigate the therapeutic effects of QSYQ on a pig myocardial ischemia (MI) model and to determine its mechanism of action. The MI model was induced by Ameroid constriction of the left anterior descending coronary (LAD) in Ba-Ma miniature pigs. Four groups were created: model group, digoxin group, QSYQ group, and sham-operated group. Heart function, Ang II, CGMP, TXB2, BNP, and cTnT were evaluated before (3 weeks after operation: 0 weeks) and at 2, 4, and 8 weeks after drug administration. After 8 weeks of administration, the pigs were sacrificed for cardiac injury measurements. Pigs with MI showed obvious histological changes, including BNP, cTnT, Ang II, CGRP, TXB2, and ET, deregulated heart function, and increased levels of apoptotic cells in myocardial tissue. Treatment with QSYQ improved cardiac remodeling by counteracting those events. The administration of QSYQ was accompanied by a restoration of heart function and of the levels of Ang II, CGRP, TXB2, ET BNP, and cTnT. In addition, QSYQ attenuated administration, reduced the apoptosis, and decreased the level of TNF-α and active caspase-3. In conclusion, administration of QSYQ could attenuate Ameroid constrictor induced myocardial ischemia, and TNF-α and active caspase-3 seemed to be the critical potential target of QSYQ.
Book Reviews Stochastic Integration and Differential equations (Second edition)

As anyone who has taught or attended a course on Stochastic calculus knows, one of the most difficult aspect of the theme is absence of exercises in the books on the topic. The second edition of this book comes to the rescue. Each chapter has exercises which should help instructors and students alike. The basic approach of the book is of course the same as in the first edition: Define a semimartingale to be a process with respect to which stochastic integration can be defined and then show that this is a liner space that includes martingales as well as processes with bounded variation paths. The topics included in the edition include a newer proof of Doob-Meyer decomposition theorem, Lenglart’s version of Girsanov Theorem, a treatment of Kazamaki-Novikov criterion for exponential local martingales to be martingales, representation of martingales, Emery topology, Fisk-Stratenovich integration and differential equations, Flows associated with stochastic differential equations. This book would serve as a good text book for a course on stochastic calculus. At the same time, the book is also a good reference book.
A Logic of Direct Evidence

In the proof-theoretic study of logic, the notion of normal proof has been understood and investigated as a metalogical property. Usually we formulate a system of logic, identify a class of proofs as normal proofs, and show that every proof in the system reduces to a corresponding normal proof. This paper presents a system of modal logic that is capable of expressing the notion of normal proof within the system itself. That is, the system has a means for both recognizing and manipulating its own normal proofs, thereby making normal proofs an inherent property of the logic. As an application, we present an authorization logic whose unique feature is to distinguish between “what a principal would affirm via inference” and “what a principal explicitly says. ”
Duloxetine: A Review of Its Safety and Efficacy in the Management of Fibromyalgia Syndrome

Fibromyalgia (FM) is a chronic disorder characterized by widespread pain and other associated symptoms including fatigue, insomnia, cognitive/memory problems, and even psychological distress. Duloxetine is one of three FDA approved medications (the other two being milnacipran and pregabalin) for the treatment of FM. It has been demonstrated that FM patients possess low central nervous system levels of serotonin and norepinephrine. Duloxetine, which is classified pharmacologically as a serotonin-norepinephrine reuptake inhibitor (SNRI), may be beneficial for FM patients by increasing these levels. This review will touch briefly upon the pathophysiology of FM, diagnostic tools, currently available therapeutic options (both pharmacologic and non-pharmacologic), as well as the pharmacokinetic/pharmacodynamic properties of duloxetine. In addition, the efficacy and safety/tolerability of duloxetine exclusively in FM will be assessed through examination of 5 randomized controlled trials, as well as pooled analyses of current data. Suggestions for a therapeutic niche for duloxetine in FM are discussed based on a presentation of the characteristics of duloxetine.
SDM-BSM: A fusing depth scheme for human action recognition

Depth map has shown promising capability in human action recognition, however it always be auxiliary of RGB features in previous work. As to sufficiently exploring depth map, we propose an innovative descriptor for human action recognition using solo depth data. First, Salient Depth Map (SDM) is calculated between two consecutive depth frames, which is superior for action description as it is located on salient moving objects. Moreover, Binary Shape Map (BSM) is proposed to depict the silhouettes induced by the lateral component of the scene action parallel to the image plane. Then, for implementation, a new framework as Bag-of-Map-Words is employed after concatenating SDM and BSM feature vectors. Experiments on NHA database demonstrate the superiority and high efficiency of the proposed method. We also give detailed comparisons with other features and analysis for parameters as a guidance of further applications.
Quasimap Floer Cohomology for Varying Symplectic Quotients

Abstract We show that quasimap Floer cohomology for varying symplectic quotients resolves several puzzles regarding displaceability of toric moment fibers. For example, we present a compact Hamiltonian torus action containing an open subset of non-displaceable orbits and a codimension four singular set, partly answering a question of McDuff, and we determine displaceability for most of the moment fibers of a symplectic ellipsoid.
Perceptions of the Influence of Hip-Hop Music and Media on Sexual Decision-Making and Behaviors of African American Adolescent Females

abstract:This study examined the role of hip-hop music, media and culture in sexual risk behaviors using focus groups and computerized surveys among 32 AA mid-adolescent girls in the southeastern U.S. The mean age was 17.8 years (SD=1.0) with a mean vaginal sexual debut of 15.7 years (SD=1.6). Sixty-six percent of girls were sexually active, 13% had at least one child and nearly 10% reported a history of sexually transmitted infections. Three themes emerged: (1) Hip-hop is the voice of the young people; (2) Media and music as first exposures to sex; (3) Artists and celebrities as role models for sex.
Do Wellness Tourists Get Well? An Observational Study of Multiple Dimensions of Health and Well-Being After a Week-Long Retreat

Abstract Background: Wellness retreats use many complementary and alternative therapies within a holistic residential setting, yet few studies have evaluated the effect of retreat experiences on multiple dimensions of health and well-being, and no published studies have reported health outcomes in wellness tourists. Objectives: To assess the effect of a week-long wellness-retreat experience in wellness tourists. Design: A longitudinal observational study with outcomes assessed upon arrival and departure and 6 weeks after the retreat. Setting: A rural health retreat in Queensland, Australia. Interventions: A holistic, 1-week, residential, retreat experience that included many educational, therapeutic, and leisure activities and an organic, mostly plant-based diet. Outcome measures: Multiple outcome measures were performed upon arrival and departure and 6 weeks after the retreat. These included anthropometric measures, urinary pesticide metabolites, a food and health symptom questionnaire, the Five Factor Wellness Inventory, the General Self Efficacy questionnaire, the Pittsburgh Insomnia Rating Scale, the Depression Anxiety Stress Scale, the Profile of Mood States, and the Cogstate cognitive function test battery. Results: Statistically significant improvements (p < 0.05) were seen in almost all measures (n = 37) after 1 week and were sustained at 6 weeks (n = 17). There were statistically significant improvements (p < 0.001) in all anthropometric measures after 1 week, with reductions in abdominal girth (2.7 cm), weight (1.6 kg), and average systolic and diastolic pressure (−16.1 mmHg and −9.3 mmHg, respectively). Statistically significant improvements (p < 0.05) were also seen in psychological and health symptom measures. Urinary pesticide metabolites were detected in pooled urine samples before the retreat and were undetectable after the retreat. Conclusion: Retreat experiences can lead to substantial improvements in multiple dimensions of health and well-being that are maintained for 6 weeks. Further research that includes objective biomarkers and economic measures in different populations is required to determine the mechanisms of these effects and assess the value and relevance of retreat experiences to clinicians and health insurers.
A Sub-1-V, 350- $\mu$ W, 6.5-dB Integrated NF Low-IF Receiver Front-End for IoT in 28-nm CMOS

This letter presents a highly efficient low-intermediate frequency receiver front-end for Internet-of-Things applications. The low-noise trans-impedance amplifier (LNTA) combines a transformer-based network for scaling up the source impedance together with passive <italic>gm</italic>-boosting and current-reuse techniques to achieve better noise and <inline-formula> <tex-math notation="LaTeX">$12\times $ </tex-math></inline-formula> current saving compared with a common-gate (CG) stage. A complex channel-selection filter with center frequency and passband of 2 and 1.4 MHz, respectively, is implemented after the passive mixer with a <italic>gm</italic>-boosted CG stage. Built in 28-nm CMOS, the proposed receiver occupies an active area of 0.1 mm<sup>2</sup>, it is supplied with 0.9 V and consumes only 350 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula>, while showing a minimum NF of 6.2 dB at the channel of interest. The RF performance of the proposed receiver is very competitive with the state-of-the-art ultralow-power receivers, while it consumes the lowest power.
Recycle deep features for better object detection

Aiming at improving the performance of existing detection algorithms developed for different applications, we propose a region regression-based multi-stage class-agnostic detection pipeline, whereby the existing algorithms are employed for providing the initial detection proposals. Better detection is obtained by exploiting the power of deep learning in the region regress scheme while avoiding the requirement on a huge amount of reference data for training deep neural networks. Additionally, a novel network architecture with recycled deep features is proposed, which provides superior regression results compared to the commonly used architectures. As demonstrated on a data set with ~1200 samples of different classes, it is feasible to successfully train a deep neural network in our proposed architecture and use it to obtain the desired detection performance. Since only slight modifications are required to common network architectures and since the deep neural network is trained using the standard hyperparameters, the proposed detection is well accessible and can be easily adopted to a broad variety of detection tasks.