Miracle-dz/UniFAR-FTUs huggingface dataset:
Abstract We present a mixed-signal system for extracting hemodynamic parameters in real-time from noisy electrical bioimpedance (EBI) measurements in an energy-efficient manner. The proof-of-concept system consists of floating-gate- based analog signal processing (ASP) electronics implemented on a f

We present a mixed-signal system for extracting hemodynamic parameters in real-time from noisy electrical bioimpedance (EBI) measurements in an energy-efficient manner. The proof-of-concept system consists of floating-gatebased analog signal processing (ASP) electronics implemented on a field programmable analog array (FPAA) chip interfaced with an on-chip low-power microcontroller. Physiological features important for calculating hemodynamic parameters (e.g., heart rate, blood volume, and blood flow) are extracted using the custom signal processing circuitry, which consumes a total power of 209 nW. Testing of the signal processing circuitry has been performed using ~580 sec of an impedance plethysmography dataset collected from the knee of a subject using a custom analog EBI front-end. Results show the similarities of variations in heart rate, blood volume, and blood flow calculated using features extracted by the ASP circuitry implemented on an FPAA and a MATLAB digital signal processing algorithm.
Working Memory Load Modulates Neuronal Coupling

There is a severe limitation in the number of items that can be held in working memory. However, the neurophysiological limits remain unknown. We asked whether the capacity limit might be explained by differences in neuronal coupling. We developed a theoretical model based on Predictive Coding and used it to analyze Cross Spectral Density data from the prefrontal cortex (PFC), frontal eye fields (FEF) and lateral intraparietal area (LIP). Monkeys performed a change detection task (Buschman et al., 2011). The number of objects that had to be remembered (memory load) was varied (1-3 objects in the same visual hemifield). Changes in memory load changed the connectivity in the PFC-FEF-LIP network. Feedback (top-down) coupling broke down when the number of objects exceeded cognitive capacity. This provides new insights into the neuronal underpinnings of cognitive capacity and how coupling in a distributed working memory network is affected by memory load.
Machine learning microserver for neuromodulation device training

Determining a treatment for those with refractory epilepsy often requires an observation period in an Epilepsy Monitoring Unit (EMU) where neural recordings are analyzed to localize a seizure onset zone. This region can be targeted by an implanted neuromodulation device to detect and inhibit ictal activity. Due to the patient-specific nature of epilepsy, on-device machine learning has been demonstrated to improve seizure detection accuracy. However, chronic implants experience considerable recording signal variability over time, leading to a degradation in treatment efficacy. This suggests the need for post-implantation learning which is impractical to perform on a power-constrained device. Presented here is a patient-localized microserver which enables continuous model adaptation aided by unsupervised machine learning. The system employs a one-class support vector machine (OC-SVM) to identify irregular neural activity for remote clinical assessment and device retraining. The system performance is demonstrated using 500 hours of human intracranial EEG (iEEG) where a clinical seizure detection rate of 97.05% is achieved.
Telomere and Telomerase in Cancer

The linear ends of chromosome are protected by specialized ribonucleoprotein (RNP) termed as telomere. These specialized terminal elements with tandem repeated sequence are the protective cap that alleviate end replication problem and cell senescence. The telomere length maintenance is essential to avoid cell death and apoptosis. Telomere shortening has been related to chronic stress due to several factors, which include not only psychological stress but also diseases such as cardiovascular diseases and cancer. Telomerase enzyme which maintains telomere length is the major factor responsible for evading cell death. Telomere length maintenance and telomerase expression put together are the prerequisite for immortality, an essential character for cancer cells. Understanding the mechanism of telomere and telomerase functions paves way for eradicating the diseases such as cancer.
Application of 3-D Printing for Tissue Regeneration in Oral and Maxillofacial Surgery: What is Upcoming?

The ultimate goal of any surgical procedure is to improve perioperative form and function and to minimize operative and postoperative morbidity. In recent years, many exciting and novel technological advances have been introduced in the field of oral and maxillofacial surgery. One example of such technology that is continuing to increase in prevalence is the use of 3-dimensional (3-D) printing techniques with special properties, which seems hopeful for practitioners in the field of regenerative medicine. Tissue engineering is a critical and important area in biomedical engineering for creating biological alternatives for grafts, implants, and prostheses. One of the main triad bases for tissue engineering is scaffolds, which play a great role for determining growth directions of stem cells in a 3-dimensional aspect. Mechanical strength of these scaffolds is critical as well as interconnected channels and controlled porosity or pores distribution. However, existing 3-D scaffolds proved less than ideal for actual clinical applications. In this chapter, we review the application and advancement of rapid prototyping (RP) techniques in the design and creation of synthetic scaffolds for use in tissue engineering. Also, we survey through new and novel merging era of “bioprinting. ”
Empathy Modulates the Evaluation Processing of Altruistic Outcomes

Empathy plays a central role in social decisions involving psychological conflict, such as whether to help another person at the cost of one’s own interests. Using the event-related potential (ERP) technique, the current study explored the neural mechanisms underlying the empathic effect on the evaluation processing of outcomes in conflict-of-interest situations, in which the gain of others resulted in the performer’s loss. In the high-empathy condition, the beneficiaries were underprivileged students who were living in distress (stranger in need). In the low-empathy condition, the beneficiaries were general students without miserable information (stranger not in need). ERP results showed that the FRN was more negative-going for self no-gain than self gain, but showed reversed pattern for other’s outcome (i.e., more negative for gain than no-gain) in the low-empathy condition, indicating that participants interpreted the gain of others as the loss of themselves. However, the reversed FRN pattern was not observed in the high-empathy condition, suggesting that the neural responses to one’s own loss are buffered by empathy. In addition, the P3 valence effect was observed only in the self condition, but not in the two stranger conditions, indicating that the P3 is more sensitive to self-relevant information. Moreover, the results of subjective rating showed that more empathic concern and altruistic motivation were elicited in the high-empathy condition than in the low-empathy condition, and these scores had negative linear correlations only with the FRN, but not with the P3. These findings suggest that when outcomes following altruistic decisions involve conflict of interest, the early stage of the processing of outcome evaluation could be modulated by the empathic level.
Helminth Infections: Recognition and Modulation of the Immune Response by Innate Immune Cells

The survival of helminths in the host over long periods of time is the result of a process of adaptation or dynamic co-evolution between the host and the parasite. However, infection with helminth parasites causes damage to the host tissues producing the release of danger signals that induce the recruitment of various cells, including innate immune cells such as macrophages (Mo), dendritic cells (DCs), eosinophils, basophils, and mast cells. In this scenario, these cells are able to secrete soluble factors, which orchestrate immune effector mechanisms that depend on the different niches these parasites inhabit. Here, we focus on recent advances in the knowledge of excretory-secretory products (ESP), resulting from helminth recognition by DCs and Mo. Phagocytes and other cells types such as innate lymphocyte T cells 2 (ILC2), when activated by ESP, participate in an intricate cytokine network to generate innate and adaptive Th2 responses. In this review, we also discuss the mechanisms of innate immune cell-induced parasite killing and the tissue repair necessary to assure helminth survival over long periods of time.
Long-term sequelae of acute respiratory distress syndrome caused by severe community-acquired pneumonia: Delirium-associated cognitive impairment and post-traumatic stress disorder

Objective Delirium in critically ill patients is considered a risk factor for various long-term consequences. We evaluated delirium and associated long-term outcomes in patients with acute respiratory distress syndrome with non-H1N1 and H1N1- associated severe community-acquired pneumonia (sCAP) who had been recommended to take antiviral drugs associated with delirious symptoms as adverse effects. Methods Of 64 patients, 42 survivors (H1N1, 15; non-H1N1, 27) were analyzed regarding the relationship between medication and the duration of delirium in the intensive care unit. During follow-up (n = 23), we assessed cognitive abilities, post-traumatic stress disorder (PTSD), physical capacity, and health-related quality of life (HRQoL). Results The incidence of delirium was 88%. There was no difference in the incidence and duration of delirium between patients with H1N1 and non-H1N1 infection. The haloperidol and opioid doses were associated with a longer delirium duration. The delirium duration was correlated with reduced cognitive performance in motor skills, memory function, and learning efficiency. Patients with PTSD (16%) had a significantly longer delirium duration and low mental HRQoL. Conclusions H1N1 infection and corresponding antiviral medication had no impact on delirium. The duration of delirium in these patients was associated with impairments in various outcome parameters, illustrating the burden of sCAP.
Graphene: A possible low-cost eco-friendly solution for antenna applications

This paper demonstrates the graphene as a competitive alternative to metals for antenna application. A conductive layer is developed by printing the cotton fabric by a commercially available graphene nanoparticle based ink and utilized to fabricate a rectangular patch antenna. It is shown that the patch antenna performance enhancement methods are likely applicable for graphene based conductive sheets over metal microstrip. The −6 dB impedance bandwidth of the antenna (24.2%) is enhanced by exciting the higher order TM02 mode and radiation efficiency (above 74% in the operating band) is improved using a low dielectric constant foam substrate. The prototype of the proposed design is fabricated showing excellent agreement between simulated and measured results.
Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data

We present a generic framework for spatio-temporal (ST) data modeling, analysis, and forecasting, with a special focus on data that is sparse in both space and time. Our multi-scaled framework is a seamless coupling of two major components: a self-exciting point process that models the macroscale statistical behaviors of the ST data and a graph structured recurrent neural network (GSRNN) to discover the microscale patterns of the ST data on the inferred graph. This novel deep neural network (DNN) incorporates the real time interactions of the graph nodes to enable more accurate real time forecasting. The effectiveness of our method is demonstrated on both crime and traffic forecasting.
Mining the Statistical Information of Confidential Data from Noise-Multiplied Data

Protecting data privacy and mining statistical information from protected data are the essential issues in big data. Protecting data privacy through noise-multiplied data is one of approaches studied in the literature. This paper introduces the B-M L2014 Approach for estimating the density function of the original data based on micro noise-multiplied data.We show an application of the B-M L2014 Approach and demonstrates that the statistical information of the original data can be retrieved from their noise-multiplied data reasonably. The approach provides a new data mining technique for big data when data privacy is concerned.
Optimizing MapReduce Partitioner Using Naive Bayes Classifier

Data locality and data skew on the reduce side are two essential issues in MapReduce. Improving data locality can decrease network traffic by moving reduce tasks to the nodes where the input data of reduce tasks is located. Data skew will lead to load imbalance among reducer nodes. Partitioning is an important operation of MapReduce because it determines the destinations of map output and could significantly affect the data amount of shuffle. Therefore, an effective partitioner can improve MapReduce performance by increasing data locality and decreasing data skew on the reduce side. Previous studies considering the two essential issues have ignored the fact that for different types of jobs, the priority of data locality and data skew on the reduce side may produce different effects on the execution time. In this paper, we propose a novel partitioner based on naive Bayes classifier, namely, BAPM, which achieves better performance through optimizing data locality and data skew by leveraging the naive Bayes classifier, i.e., considering job type and bandwidth as classification attributes. Our experiments are performed in a Hadoop cluster with 31 nodes and the results show that BAPM speeds up the computing performance of MapReduce by up to 19.26% compared to the native Hadoop.
Robust Control of Boost Converter

In recent years, high-performance DC-DC converter is a key research direction in the fields of power design. This paper takes the Boost-converter as an example to construct the mathematical model. Besides, it also applies several control strategies which includes PID control based on genetic algorithm, sliding mode control algorithm and so on to the design of DC-DC converter. Finally, we analyzed the simulation results.
PSCC: Parallel Self-Collision Culling with Spatial Hashing on GPUs

We present a GPU-based self-collision culling method (PSCC) based on a combination of normal cone culling and spatial hashing techniques. We first describe a normal cone test front (NCTF) based parallel algorithm that maps well to GPU architectures. We use sprouting and shrinking operators to maintain compact NCTFs. Moreover, we use the NCTF nodes to efficient build an enhanced spatial hashing for triangles meshes and use that for inter-object and intra-object collisions. Compared with conventional spatial hashing, our approach provides higher culling efficiency and reduces the cost of narrow phrase culling. As compared to prior GPU-based parallel collision detection algorithm, our approach demonstrates 6-8X speedup. We also present an efficient approach for GPU-based cloth simulation based on PSCC. In practice, our GPU-based cloth simulation takes about one second per frame on complex scenes with tens or hundreds of thousands of triangles, and is about 4-6X faster than prior GPU-based simulation algorithms.
Behavior of Piezoelectric Wafer Active Sensors Under Large Strain and Fatigue Loading Conditions

ii List of Figures v List of Symbols and Abbreviations viii Chapter 1 – Introduction 1 Motivation for this Research 1 Damage Detection Technology 2 Methods of Damage Detection 2 State of the Art in Structural Health Monitoring Technology 3 Research Goals and Objectives 8 Organization of the Thesis 9 Chapter 2 – Piezoelectric Wafer Active Sensors 11 Principle of Piezoelectricity 11 Behavior of Free One-Dimensional PWAS 12 Mechanical Response 16 Electrical Response 18 Behavior of Constrained One-Dimensional PWAS 21 Mechanical Response 23 Electrical Response 24 Chapter 3 – Electro-Mechanical Impedance Method 26 Impedance Techniques 26 E/M Impedance Methodology 26 Vibration Theory 28 Axial Vibrations of Bars 28 Flexural Vibrations of Strings 30 Flexural Vibrations of Beams 33 Orthogonality of Modes 38 Frequency Response 42 Frequency Response of Beam Excited by PWAS 47 Axial Vibrations 49 Flexural Vibrations 50 Chapter 4 – High Strain Effects on PWAS Performance 55 Geometry of the Test Specimen 55 Testing Procedure 55 Material Property Test 56 PWAS Strain Test 60
E valuation of Dry Distillers Grains Plus Solubles Inclusion on Performance and Economics of Finishing Beef Steers 1

A 167-d feedlot study was conducted to evaluate feeding increasing levels of dry distillers grains plus solubles (DDGS) to finishing cattle and the impact on performance and profitability. Crossbred steer calves (n = 240, BW = 306 ± 24.5 kg) were used in 30 pens with dietary treatments of 0, 10, 20, 30, and 40% DDGS dietary inclusion (DM basis). Quadratic relationships (P < 0.05) were observed for final BW and ADG as dietary DDGS increased, with the greatest ADG observed at 20% inclusion. The DMI was not affected (P > 0.15) by DDGS level, but G:F tended to be quadratic (P = 0.10) as 20% DM inclusion had the greatest value, although steers fed all levels of DDGS had numerically greater G:F compared with steers fed no DDGS. Carcass characteristics, other than hot carcass weight, were not affected by DDGS treatment. Energy value of DDGS at 10 to 40% dietary inclusion resulted in a quadratic trend (P = 0.10) and remained above corn, with the highest values at 10 and 20% inclusion averaging 127% of corn. When DDGS was priced equally to corn, all levels of DDGS from 10 to 40% inclusion resulted in higher profits compared with a dry-rolled corn based diet regardless of corn price. The greatest returns were observed when cattle were fed 20% DDGS. These data indicate that DDGS can be fed up to 40% DM to improve cattle performance and result in economic profits, with optimum levels at
Correction of megavoltage cone‐beam CT images of the pelvic region based on phantom measurements for dose calculation purposes

Megavoltage cone‐beam CT (MVCBCT) is an imaging technology that provides a 3D representation of the patient in treatment position. Because it is a form of x‐ray tomography, MVCBCT images give information about the attenuation coefficients of the imaged tissues, and thus could be used for dose calculation. However, the cupping and missing data artifacts seen on MVCBCT images can cause inaccuracies in dose calculations. To eliminate these inaccuracies, a correction method specific to pelvis imaging and based on phantom measurements has been devised. Pelvis‐shaped water phantoms of three different sizes were designed and imaged with MVCBCT. Three sets of correction factors were created from the artifacts observed in these MVCBCT images by dividing the measured CT number by the predefined CT number for water. Linear interpolation is performed between the sets of correction factors to take into account the varying size of different patients. To compensate for the missing anatomy due to the limited field of view of the MVCBCT system, the MVCBCT image is complemented with the kilovoltage CT (kVCT) image acquired for treatment planning. When the correction method is applied to an anthropomorphic pelvis phantom, the standard deviation between dose calculations performed with kVCT and MVCBCT images is 0.6%, with 98% of the dose points agreeing within ±3%. With uncorrected MVCBCT images this percentage falls to 75%. An example of dose calculation performed with a corrected clinical MVCBCT image of a prostate cancer patient shows that changes in anatomy of normal tissues result in variation of the dose distribution received by these tissues. This correction method enables MVCBCT images to be used for the verification of the daily dose distribution for patients treated in the pelvis region. PACS numbers: 87.57. Q‐ Computed tomography, 87.57. cp Artifacts and distortion
Comparison of two workflows for Web-based 3D smart home visualizations

In the built environment, the emergence of Internet of Things and the Smart Building paradigm increase the amount of networked systems that produce data from their environment. 3D user interfaces can help users cope with these systems. A 3D representation of a building can operate as a starting point for creating these interfaces. We experimented with creating a 3DUI for sensor network data visualization in two cases, testing both a manually created game engine model and a BIM model as a basis. Solutions were compared in terms of performance. While BIM model captures both the 3D geometry of a building along with its structural properties, some limitations were encountered in using it for online 3D application development.
Front-line treatment of inoperable or metastatic pancreatic cancer with gemcitabine and capecitabine: an intergroup, multicenter, phase II study.

PURPOSE To evaluate the efficacy and toxicity of gemcitabine (GEM) combined with capecitabine (CAP) in untreated patients with inoperable or metastatic pancreatic cancer. PATIENTS AND METHODS Fifty-three patients with pancreatic cancer (85% stage IV) were enrolled. Patients were treated with GEM 1000 mg/m2 on days 1 and 8 and CAP 1300 mg/m2 per day PO (per os), divided into two equal doses on days 1-14, in 21-day cycles. RESULTS In an-intention-to-treat analysis, 10 (18.9%) objective partial responses were achieved (95% confidence interval 8.33% to 29.4%). Twenty-two (42%) patients had stable disease and 15 (28%) had progressive disease. The median response time was 3 months (range 1.5-7.0) and the median time to tumor progression was 6.5 months (range 3.5-15.5). Median overall survival time was 8 months (range 1.0-15.5) and 1-year survival was 34.8%. Pain improvement during treatment was observed in 23 of 43 (53%) patients, and eight of 18 (44%) patients who had been receiving opioids discontinued their use. Weight gain was observed in 12 of 33 (36%) patients. Grade 3 anemia occurred in five (9%) patients and grade 3-4 thrombocytopenia occurred in three (6%). Grade 3-4 neutropenia occurred in 13 (25%) and five (9%) patients, respectively, and two (4%) developed febrile neutropenia. Non-hematological toxicity was mild. CONCLUSION In patients with pancreatic cancer, the combination of GEM with CAP is an active and well tolerated regimen that merits further evaluation in prospective randomized studies.
ICA DESCRIPTION OF JET BREAKUP

In this article we review recent results on the breakup of cylindrical jets of a Newtonian fluid. Capillary forces provide the main driving mechanism and our interest is in the description of the flow as the jet pinches to form drops. The approach is to describe such topological singularities by constructing local (in time and space) similarity solutions from the governing equations. This is described for breakup according to the Euler, Stokes or Navier-Stokes equations. It is found that slender jet theories can be applied when viscosity is present, but for inviscid jets the local shape of the jet at breakup is most likely of a non-slender geometry. Systems of one-dimensional models of the governing equations are solved numerically in order to illustrate these differences. 1This work was supported by the Air Force Office for Scientific Research Grant (F49620-94-1-0242) and the National Science Foundation (Grant DMS 9-9-0070). Additional support was also provided by the National Aeronautics and Space Administration under NASA Contract No. NAS1-19480 while the author was in residence at the Institute for Computer Applications in Science and Engineering (ICASE), NASA Langley Research Center, Hampton, VA 23681-0001