Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-interference cancellation with optimal feedback path selection on full-duplex relay systems

Full-duplex relay systems in wireless communication utilize the same time and frequency resources for transmission and reception at the relay node to improve spectral efficiency. This paper proposes a scheme that reduces residual self-interference significantly in the analog-circuit domain on full-duplex relay systems. The proposed scheme measures multiple responses of the feedback path by changing the direction of the main beam of the transmitter at the relay, and then selects the optimal direction that minimizes the residual self-interference. Analytical residual self-interference is derived as the criterion to select the optimal direction. In addition, analytical probability that the residual interference exceeds the target is derived, that helps determine the number of measured responses of the feedback path. Computer simulations show the superiority of the proposed scheme, and validate the analytical results.
Wnt Pathway, Angiogenetic and Hormonal Markers in Sporadic and Familial Adenomatous Polyposis-associated Juvenile Nasopharyngeal Angiofibromas (JNA)

Juvenile nasopharyngeal angiofibroma (JNA) is a rare, invasive, and locally destructive tumor of the nasopharynx. The Wnt pathway, angiogenetic and hormonal factors are involved in the pathophysiology of JNA; it can result in an extracolonic manifestation of familial adenomatous polyposis (FAP) or in a sporadic tumor. All patients who underwent resection of JNA between 1991 and 2006 at the University of Modena and Reggio Emilia were studied to identify immunohistochemical markers of associated FAP syndrome. Paraffin-embedded JNA samples were analyzed immunohistochemically for the expression of adenomatous polyposis coli (APC), β-catenin, E-cadherin, androgen receptor, and vascular endothelial growth factors receptor (VEGFR2). In one out of the 4 (25%) young patients affected by JNA the diagnosis of FAP syndrome linked to APC mutation was made. All of the sporadic and familial JNA tumors showed nuclear staining of β-catenin, whereas altered APC expression was seen only in FAP-associated JNA. All cases were stained with VEGFR2. A combined clinical, immunohistochemical, and biomolecular screening may be useful for the identification of FAP among patients with a diagnosis of JNA. The Wnt pathway can be involved in the JNA pathogenesis either by somatic mutations of β-catenin or by germline APC mutations. As the VEGFR has an important impact on the pathogenesis of JNA, we suggest that a targeted therapy with monoclonal antibodies against VEGFR might lead to a specific chemoprevention and treatment of these tumors and their recurrences.
Estimating structural equation models within a bayesian framework: a concrete example of a markov chain monte carlo method

Submit Manuscript | http://medcraveonline.com Structural equation modeling (SEM; Bollen, [1]) is a key latent-variable modeling framework in the social and behavioral sciences. It is generally used for understanding how observable indicators relate to latent variables that are postulated to represent unobservable constructs and how these latent variables influence each other. SEM can accommodate a variety of research questions including those that lead to multi-group estimation, multi-level estimation, missing data estimation, and longitudinal estimation, both in isolation and in combination.
Modelling of the Thermal Behaviour of Free Form Extrusion

The performance of parts produced by Free Form Extrusion (FFE) may be limited by poor mechanical properties, due to poor bonding between the individual extruded filaments. In this work, an analytical solution is proposed for the transient heat transfer during filament deposition, taking into account contacts between filaments. The developed code using Matlab® allows to study the influence of the main process variables during filament deposition and may assist the process optimization.
Constrained networked control systems stabilization: A λ-D-contractive set based approach

The paper embraces the stabilization problem of Networked Control Systems ‘NCSs’ with a specific attention to linear dynamical systems affected by uncertain, possibly time-varying, network-induced delays in the presence of input and state constraints. Two main theoretical results are presented. First, we address the computation of a polyhedral control Lyapunov-Razumikhin Function ‘pcLRF’ using 1-step controllability sets. Furthermore, we show that adopting ‘pcLRF’ instead of quadratic control Lyapunov-Razumikhin Function ‘qcLRF’ reduces the conservativeness of ‘LRF’ based control design. Second, based on the first result, we show that polyhedral λ-D-contractive sets can be used as a target set in a Set Induced Lyapunov Function ‘SILF’ control fashion where a simple Linear Programming ‘LP’ problem is required to be solved at each sampling instance. We prove that the proposed controller, under mild assumptions, is able to handle state/input constraints, and ensures asymptotic stability for all initial states belonging to a predefined set.
Targeted Therapeutic Nanoparticles: An Immense Promise to Fight against Cancer

In nanomedicine, targeted therapeutic nanoparticle (NP) is a virtual outcome of nanotechnology taking the advantage of cancer propagation pattern. Tying up all elements such as therapeutic or imaging agent, targeting ligand, and cross-linking agent with the NPs is the key concept to deliver the payload selectively where it intends to reach. The microenvironment of tumor tissues in lymphatic vessels can also help targeted NPs to achieve their anticipated accumulation depending on the formulation objectives. This review accumulates the application of poly(lactic-co-glycolic acid) (PLGA) and polyethylene glycol (PEG) based NP systems, with a specific perspective in cancer. Nowadays, PLGA, PEG, or their combinations are the mostly used polymers to serve the purpose of targeted therapeutic NPs. Their unique physicochemical properties along with their biological activities are also discussed. Depending on the biological effects from parameters associated with existing NPs, several advantages and limitations have been explored in teaming up all the essential facts to give birth to targeted therapeutic NPs. Therefore, the current article will provide a comprehensive review of various approaches to fabricate a targeted system to achieve appropriate physicochemical properties. Based on such findings, researchers can realize the benefits and challenges for the next generation of delivery systems.
Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework

Objective: In most continuous glucose monitoring (CGM) devices used for diabetes management, the electrical signal measured by the sensor is transformed to glucose concentration by a calibration function whose parameters are estimated using self-monitoring of blood glucose (SMBG) samples. The calibration function is usually a linear model approximating the nonlinear relationship between electrical signal and glucose concentration in certain time intervals. Thus, CGM devices require frequent calibrations, usually twice a day. The aim here is to develop a new method able to reduce the frequency of calibrations. Methods: The algorithm is based on a multiple-day model of sensor time-variability with second-order statistical priors on its unknown parameters. In an online setting, these parameters are numerically determined by the Bayesian estimation exploiting SMBG sparsely collected by the patient. The method is assessed retrospectively on 108 CGM signals acquired for 7 days by the Dexcom G4 Platinum sensor, testing progressively less-calibration scenarios. Results: Despite the reduction of calibration frequency (on average from 2/day to 0.25/day), the method shows a statistically significant accuracy improvement compared to manufacturer calibration, e.g., mean absolute relative difference when compared to a laboratory reference decreases from 12.83% to 11.62% (p-value of 0.006). Conclusion: The methodology maintains (sometimes improves) CGM sensor accuracy compared to that of the original manufacturer, while reducing the frequency of calibrations. Significance: Reducing the need of calibrations facilitates the adoption of CGM technology both in terms of ease of use and cost, an obvious prerequisite for its use as replacement of traditional SMBG devices.
Tree-Pattern Queries on a Lightweight XML Processor

Popular XML languages, like XPath, use "tree-pattern" queries to select nodes based on their structural characteristics. While many processing methods have already been proposed for such queries, none of them has found its way to any of the existing "lightweight" XML engines (i.e. engines without optimization modules). The main reason is the lack of a systematic comparison of query methods under a common storage model. In this work, we aim to fill this gap and answer two important questions: what the relative similarities and important differences among the tree-pattern query methods are, and if there is a prominent method among them in terms of effectiveness and robustness that an XML processor should support. For the first question, we propose a novel classification of the methods according to their matching process. We then describe a common storage model and demonstrate that the access pattern of each class conforms or can be adapted to conform to this model. Finally, we perform an experimental evaluation to compare their relative performance. Based on the evaluation results, we conclude that the family of holistic processing methods, which provides performance guarantees, is the most robust alternative for such an environment.
CHOBS: Color Histogram of Block Statistics for Automatic Bleeding Detection in Wireless Capsule Endoscopy Video

Wireless capsule endoscopy (WCE) is the most advanced technology to visualize whole gastrointestinal (GI) tract in a non-invasive way. But the major disadvantage here, it takes long reviewing time, which is very laborious as continuous manual intervention is necessary. In order to reduce the burden of the clinician, in this paper, an automatic bleeding detection method for WCE video is proposed based on the color histogram of block statistics, namely CHOBS. A single pixel in WCE image may be distorted due to the capsule motion in the GI tract. Instead of considering individual pixel values, a block surrounding to that individual pixel is chosen for extracting local statistical features. By combining local block features of three different color planes of RGB color space, an index value is defined. A color histogram, which is extracted from those index values, provides distinguishable color texture feature. A feature reduction technique utilizing color histogram pattern and principal component analysis is proposed, which can drastically reduce the feature dimension. For bleeding zone detection, blocks are classified using extracted local features that do not incorporate any computational burden for feature extraction. From extensive experimentation on several WCE videos and 2300 images, which are collected from a publicly available database, a very satisfactory bleeding frame and zone detection performance is achieved in comparison to that obtained by some of the existing methods. In the case of bleeding frame detection, the accuracy, sensitivity, and specificity obtained from proposed method are 97.85%, 99.47%, and 99.15%, respectively, and in the case of bleeding zone detection, 95.75% of precision is achieved. The proposed method offers not only low feature dimension but also highly satisfactory bleeding detection performance, which even can effectively detect bleeding frame and zone in a continuous WCE video data.
Effect of transtympanic low-pressure therapy in patients with unilateral Menière's disease unresponsive to betahistine: a randomised, placebo-controlled, double-blinded, clinical trial

Abstract Objective: To determine the effect of the Meniett® low-pressure generator on the subjective symptoms and audiovestibular disease markers of patients with unilateral Menière's disease unresponsive to betahistine treatment. Methods: Randomised, placebo-controlled, double-blinded, clinical trial at a tertiary referral centre. After ventilation tube placement, patients were randomised to the active treatment or placebo group. Monitoring comprised audiometry and air caloric testing and a vertigo diary (enabling calculation of vertigo and activity scores, and the number of vertigo days, vertigo-free days and sick days). Results: Sixty-eight patients completed the study. For the active treatment versus placebo group, the following pre- and post-treatment values, and significances for treatment effect comparisons, were respectively seen: cumulative vertigo scores, 22.47 and 15.97 vs 20.42 and 19.23 (p = 0.048); vertigo days, 6.5 and 4.08 vs 5.94 and 5.52 (p = 0.102); sick days, 3.08 and 0.78 vs 2.87 and 3.45 (p = 0.041); vertigo-free days, 14.47 and 17.61 vs 15.48 and 17.58 (p = 0.362); activity score, 23.61 and 13.42 vs 24.68 and 20.23 (p = 0.078); low-tone hearing threshold, 49.15 and 53.18 dB nHL vs 41.66 and 46.10 dB nHL (p > 0.05); and slow phase velocity in response to caloric stimulation, 18.86 and 18.72 °/second vs 14.97 and 15.95 °/second, (p > 0.05). Conclusion: Use of the Meniett® low-pressure generator improved patients' vertigo but not their hearing or vestibular function. This safe, minimally invasive treatment is recommended as second-line treatment for unilateral Menière's disease.
Role of Electrospun Nanofibers in Stem Cell Technologies and Tissue Engineering

Tissue engineering is a promising tool to manage structural and functional defects in bone and cartilage. To provide optimal conditions for three-dimensional cell growth the use of a scaffold is necessary. The aim of the study was to prove osteogenic differentiation of human mesenchymal stem cells (hMSC) onto a three-dimensional, nanostructured scaffold of electrospun poly (l-lactide)-nanofibers. HMSC were seeded onto this matrix and differentiated for 21 days. Cells clearly preferred a guided growth along the nanofibers and revealed no signs of cell-death. Osteogenic differentiation of hMSC onto the matrix has been demonstrated. Due to the fine structure, electrospun nanofibers promises to be an ideal scaffold for tissue engineering. They can be enriched with additives and are equally biocompatible and biodegradable.
Chipmunk: A systolically scalable 0.9 mm2, 3.08Gop/s/mW @ 1.2 mW accelerator for near-sensor recurrent neural network inference

Recurrent neural networks (RNNs) are state-of-the-art in voice awareness/understanding and speech recognition. On-device computation of RNNs on low-power mobile and wearable devices would be key to applications such as zero-latency voice-based human-machine interfaces. Here we present CHIPMUNK, a small (<1mm2) hardware accelerator for Long-Short Term Memory RNNs in UMC 65 nm technology capable to operate at a measured peak efficiency up to 3.08Gop/s/mW at 1.24 mW peak power. To implement big RNN models without incurring in huge memory transfer overhead, multiple CHIPMUNK engines can cooperate to form a single systolic array. In this way, the Chipmunk architecture in a 75 tiles configuration can achieve real-time phoneme extraction on a demanding RNN topology proposed in [1], consuming less than 13 mW of average power.
Label propagation through neuronal synchrony

Semi-Supervised Learning (SSL) is a machine learning research area aiming the development of techniques which are able to take advantage from both labeled and unlabeled samples. Additionally, most of the times where SSL techniques can be deployed, only a small portion of samples in the data set is labeled. To deal with such situations in a straightforward fashion, in this paper we introduce a semi-supervised learning approach based on neuronal synchrony in a network of coupled integrate-and-fire neurons. For that, we represent the input data set as a graph and model each of its nodes by an integrate-and-fire neuron. Thereafter, we propagate the class labels from the seed samples to unlabeled samples through the graph by means of the emerging synchronization dynamics. Experimentations on synthetic and real data show that the introduced technique achieves good classification results regardless the feature space distribution or geometrical shape.
Leakage Reduction in DT8T SRAM Cell Using Body Biasing Technique

During recent years SRAM has become the topic of crucial research due to increased demand in mobile applications. For low power applications, leakage reduction is very important. This brings the incentive to design low leakage SRAM cells. In this work, a Dynamic Threshold 8T (DT8T) SRAM cell is proposed to elevate the performance in terms of maintaining stability and leakage reduction by using variable threshold voltage transistors. During write and hold mode, drivability of transistors is improved with forward body biasing. For reducing the leakage current, reverse body biasing is used during read mode of operation. The proposed circuit is designed in 45 nm CMOS technology and is simulated using Cadence Virtuoso platform. At supply voltage of 0.5 V, read leakage currents through feedback transistors are observed as 0.261 pA and 0.198 pA when body is reverse biased at 0.6 V and these are reduced by approximately 84% compared to D8T SRAM cell. This proposed SRAM cell draws 7.31 nA leakage current in standby mode which is 24% lesser compared to conventional 6T SRAM cell.
Barrier-Enabled IO Stack for Flash Storage

This work is dedicated to eliminating the overhead of guaranteeing the storage order in modern IO stack. The existing block device adopts prohibitively expensive resort in ensuring the storage order among write requests: interleaving successive write requests with transfer and flush. Exploiting the cache barrier command for the Flash storage, we overhaul the IO scheduler, the dispatch module and the filesystem so that these layers are orchestrated to preserve the ordering condition imposed by the application can be delivered to the storage. Key ingredients of Barrier Enabled IO stack are Epoch based IO scheduling, Order Preserving Dispatch, and Dual Mode Journaling. Barrier enabled IO stack successfully eliminates the root cause of excessive overhead in enforcing the storage order. Dual Mode Journaling in BarrierFS dedicates the separate threads to effectively decouple the control plane and data plane of the journal commit. We implement Barrier Enabled IO Stack in server as well as in mobile platform. SQLite performance increases by 270% and 75%, in server and in smartphone, respectively. Relaxing the durability of a transaction, SQLite performance and MySQL performance increases as much as by 73X and by 43X, respectively, in server storage.
Size-miniaturized bandpass filter made of folded stepped-impedance resonators with adjacent and nonadjacent coupling for selectivity enhancement

In this paper, a size-miniaturized microstrip bandpass filter with quasi-elliptic function responses is presented. The proposed filter consists of four A/2 folded stepped-impedance resonators (FSIRs), which can save nearly 50% circuit size compared with its corresponding conventional SIR counterpart. By utilizing the adjacent and nonadjacent coupling topology, three different cross-coupling path-pairs are built up, so that three different transmission zeros (TZs) can be generated, which will contribute to high sideband selectivity and wide stopband range for the proposed filter. In order to verify the aforementioned concept, a prototype of the proposed filter is implemented, with its measured results are in good agreement with the simulated ones. Meanwhile, the sideband roll-off rejection of the proposed filter is better than 50 dB within 500 MHz away from the edge of passband, indicating a high selectivity. Moreover, with a stopband rejection better than 34 dB, its upper stopband can be as high as 12 GHz, i.e., over the third harmonic of the passband. As compared to some reported similar works, the proposed filter exhibits a size-reduction over 23%, which illustrates its suitability for the microwave system integration and packaging application.
Effect of a Rapid Test Algorithm on Linkage to Medical Care and Viral Suppression Among New Jersey Residents, 2007 to 2015

Background Efforts to identify and link human immunodeficiency virus-infected persons to medical care are the first steps to achieving viral suppression. In the United States, the goals are to link 85% of newly diagnosed persons to medical care in 30 days or less and for 80% to become virally suppressed by 2020. Among newly diagnosed residents from 2007 to 2015, in New Jersey, we evaluated the impact of a rapid testing algorithm (RTA) on linkage to medical care and viral suppression. Methods This is a retrospective review of data from New Jersey’s Enhanced HIV/AIDS Reporting System for residents, newly diagnosed at 13 years or older, from 2007 to 2015. We used survival analysis methods to estimate the proportion of residents and time to linkage to medical care and viral suppression. Results Of 8508 newly diagnosed residents, 60.3% and 72.3% were linked to medical care in 30 days or less and 90 days or less, respectively; 45.7% achieved viral suppression in 365 days or less. Linkage to medical care in 90 days or less and viral suppression in 365 days or less were more likely among those tested by RTA than laboratory testing. The adjusted hazard ratios for linkage to medical care, in clinical sites were 1.41, (95% confidence interval [CI], 1.22–1.63 and 1.08, 95% CI, 0.97–1.2 in community sites. The adjusted hazard ratios for viral suppression in clinical sites were 1.25 (95% CI, 1.05–1.47 and 1.16, 95% CI, 1.01–1.32, in community sites. Conclusions Implementation of a RTA may eliminate barriers to linkage to medical care and viral suppression leading to decreased morbidity, mortality, and transmission.
Visual Analysis of Brain Networks Using Sparse Regression Models

Studies of the human brain network are becoming increasingly popular in the fields of neuroscience, computer science, and neurology. Despite this rapidly growing line of research, gaps remain on the intersection of data analytics, interactive visual representation, and the human intelligence—all needed to advance our understanding of human brain networks. This article tackles this challenge by exploring the design space of visual analytics. We propose an integrated framework to orchestrate computational models with comprehensive data visualizations on the human brain network. The framework targets two fundamental tasks: the visual exploration of multi-label brain networks and the visual comparison among brain networks across different subject groups. During the first task, we propose a novel interactive user interface to visualize sets of labeled brain networks; in our second task, we introduce sparse regression models to select discriminative features from the brain network to facilitate the comparison. Through user studies and quantitative experiments, both methods are shown to greatly improve the visual comparison performance. Finally, real-world case studies with domain experts demonstrate the utility and effectiveness of our framework to analyze reconstructions of human brain connectivity maps. The perceptually optimized visualization design and the feature selection model calibration are shown to be the key to our significant findings.
Study and evaluation of different topologies in wireless sensor network

The network technologies development made wireless sensor network (WSN) to have many ways in reducing the complexity, cost and in improving reliability. The objective of this paper is to provide an effective topology modeling to conserve the energy of individual nodes in wireless sensor network and preserving its coverage maintenance and graph connectivity. This paper presents the types of topologies: Bus, ring, star and its evaluation in terms of Receiving energy, Residual energy, Idle-state energy, number of packets sent or received in the network.