Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of a PSoC-based flexible and low-power processor

A flexible and low-power PSoC-basecd platform has been implemented for discrete wavelet transform (DWT) and Fast Fourier transform (FFT) applications. Our designs comprise 1024-point FFT and 5-stage parametric DWT and digital filter processing units. High accuracy, low power consumption, flexibility and minimal hardware resource usage are characteristics of this design. This portable processor has been implemented on CY8C5868AXI-LP035 from PSoC5LP (ARM Cortex M3) Cypress family. Total power consumption of the design for DWT and FFT is 90 mW and 38.35mW respectively in 67MHZ frequency which is an appropriate value when compared with ASIC, FPGA and DSP based structures. The designed structure has high accuracy in computation, so that the maximum error is about 0.04 compared with the actual results.
Microcirculation and left-ventricular hypertrophy.

L eft-ventricular hypertrophy is an abnormal increase in the mass of the left-ventricular myocardium that can reflect a maladaptive response to chronic pressure overload [1]. Left-ventricular hypertrophy may be detected in about one-third of people with hypertension. When present, the risk of adverse cardiovascular events almost doubles [2,3]. In long-term epidemiological studies, left-ventricular hypertrophy increased the risk for diastolic heart failure, systolic heart failure, atrial fibrillation, and sudden death in patients with hypertension [2,3]. More than 20 years ago, the Framingham Heart Study proved that 35% of men and 20% of women died within 5 years of the appearance of left-ventricular hypertrophy at electrocardiography (ECG) [4]. Further analyses [5–7] have repeatedly confirmed that the prognostic impact of left-ventricular hypertrophy is independent of increased arterial pressure. In a coronary angiography study, left-ventricular hypertrophy increased the risk of death by two and four-fold, respectively, in the absence and presence of coronary artery stenoses [8]. Several mechanisms have been proposed to explain the risk associated with left-ventricular hypertrophy. At present, left-ventricular hypertrophy can be considered a bio-marker integrating the long-term exposure to both pressure overload and several nonhemodynamic factors which may promote progression and destabilization of atherosclerotic lesions ultimately leading to adverse clinical events. Indeed, a number of factors can increase leftventricular mass and promote progression of atherosclerotic lesions. They include insulin and insulin-like growth factors, angiotensin II, cathecholamines, endothelin and altered plasma viscosity [2]. A basic mechanism of the cardiac risk associated with left-ventricular hypertrophy may also reflect a network whose functional and structural elements are impaired coronary hemodynamics with reduced coronary blood
Adjuvant solution for pandemic influenza vaccine production

Extensive preparation is underway to mitigate the next pandemic influenza outbreak. New vaccine technologies intended to supplant egg-based production methods are being developed, with recombinant hemagglutinin (rHA) as the most advanced program for preventing seasonal and avian H5N1 Influenza. Increased efforts are being focused on adjuvants that can broaden vaccine immunogenicity against emerging viruses and maximize vaccine supply on a worldwide scale. Here, we test protection against avian flu by using H5N1-derived rHA and GLA-SE, a two-part adjuvant system containing glucopyranosyl lipid adjuvant (GLA), a formulated synthetic Toll-like receptor 4 agonist, and a stable emulsion (SE) of oil in water, which is similar to the best-in-class adjuvants being developed for pandemic flu. Notably, a single submicrogram dose of rH5 adjuvanted with GLA-SE protects mice and ferrets against a high titer challenge with H5N1 virus. GLA-SE, relative to emulsion alone, accelerated induction of the primary immune response and broadened its durability against heterosubtypic H5N1 virus challenge. Mechanistically, GLA-SE augments protection via induction of a Th1-mediated antibody response. Innate signaling pathways that amplify priming of Th1 CD4 T cells will likely improve vaccine performance against future outbreaks of lethal pandemic flu.
Side-informed watermarking using nth-order polynomial detectors

Most recent watermarking schemes differ from symmetric schemes in that the detection process does not require the use of the same private key in both the embedder and the detector. An advantage of such schemes is that estimation of the watermark by collusion attack is rendered impossible, so that the overall system is more secure. Almost all second generation schemes to date are also second-order; that is, they are based on the computation of a quadratic form in the detector. In this work, the authors propose a new class of watermarking schemes which employ an nth-order detection process. The scheme is based on a generalised differential modulation scheme. We address the question of how to choose the watermark signal in order to optimise the output of the detection and examine the efficiency and security of this new class of schemes.
Genealogical data and the biodemography of human longevity

Abstract Biodemography of human longevity is an emerging interdisciplinary field of sociobiological research with deep historical roots. Two research questions are examined in this article: (1) What evidence is there for the familial transmission of human longevity? , and (2) what are the effects of parental age at reproduction on offspring longevity, and in particular, are there long‐term adverse health consequences associated with the trend toward delayed reproduction? The ability of scientists to conduct biodemographic studies depends not only on merging theoretical and methodological elements from the biological and demographic/actuarial sciences, but unique sources of data and statistical methods must also be developed. In this article we describe how genealogical data have been used for over a century to explore basic questions about human longevity, and how similar kinds of data now being developed are driving the formation of new testable research hypotheses in the field of biodemography.
Documentation and diagnosis of overweight and obesity in electronic health records of adult primary care patients.

Inconclusion,manyprimarycarepatientslackdocumen-tation of BMI in the EHR, and most overweight and obese patients do not have a diagnosis on the problem list. Further research should focus on interventions to improve documentationofBMIanddiagnosisandmanagementofover-weight and obesity in the primary care setting.
Early Experiences in Using Blood Cells Biomembranes as Markers for Diabetes Diagnosis

Investigation of membrane fluidity by two photon fluorescence microscopy opens up a new and important area of translational research, being a useful and sensitive method for disease monitoring and treatment. In this paper we investigate if biomembranes in human red blood cells (RBC) and peripheral mononuclear cells (PMC) could be used as markers for type 1 diabetes mellitus (T1DM) diagnosis, leading to the development of a method for monitoring T1DM progression that nowadays is lacking, as clinical exams cannot pursue this task with enough reliability. To this aim, we present a set of features computed from PMC and RBC images that are given to a multi-experts system leveraging on multi-spectral information for positive/negative classifications. The experiments are carried out on a dataset of 800 blood cell images belonging to 18 subjects adopting the leave-one-person-out approach.
Discharge Morphology and spectral diagnostic of a serrated BDB plasma actuator dedicated to aerodynamic flow control applications

The serrated DBD plasma actuator configuration, with the exposed electrode having a sawtooth edge, was compared to the standard one (i.e. with strip electrodes) in order to highlight plasma channels induced by the serration. The differences in the plasma morphology and properties between these configurations were investigated by using optical diagnostics, in quiescent air. Images of the discharge were recorded by an ICCD camera, with and without narrow-band filters and an optical emission spectrometer was used to measure the spectral bands of N2 and N2 , allowing the rotational temperatures to be estimated.
Novel blood-based microRNA biomarker panel for early diagnosis of pancreatic cancer.

AIM To develop a panel of blood-based diagnostic biomarkers consisting of circulating microRNAs for the detection of pancreatic cancer at an early stage. METHODS Blood-based circulating microRNAs were profiled by high throughput screening using microarray analysis, comparing differential expression between early stage pancreatic cancer patients (n = 8) and healthy controls (n = 11). A panel of candidate microRNAs was generated based on the microarray signature profiling, including unsupervised clustering and statistical analysis of differential expression levels, and findings from the published literature. The selected candidate microRNAs were then confirmed using TaqMan real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) to further narrow down to a three-microRNA diagnostic panel. The three-microRNA diagnostic panel was validated with independent experimental procedures and instrumentation of RT-qPCR at an independent venue with a new cohort of cancer patients (n = 11), healthy controls (n = 11), and a group of high risk controls (n = 11). Receiver operating characteristic curve analysis was performed to assess the diagnostic capability of the three-microRNA panel. RESULTS In the initial high throughput screening, 1220 known human microRNAs were screened for differential expression in pancreatic cancer patients versus controls. A subset of 42 microRNAs was then generated based on this data analysis and current published literature. Eight microRNAs were selected from the list of 42 targets for confirmation study, and three-microRNAs, miR-642b, miR-885-5p, and miR-22, were confirmed to show consistent expression between microarray and RT-qPCR. These three microRNAs were then validated and evaluated as a diagnostic panel with a new cohort of patients and controls and found to yield high sensitivity (91%) and specificity (91%) with an area under the curve of 0.97 (P < 0.001). Compared to the CA19-9 marker at 73%, the three-microRNA panel has higher sensitivity although CA19-9 has higher specificity of 100%. CONCLUSION The identified panel of three microRNA biomarkers can potentially be used as a diagnostic tool for early stage pancreatic cancer.
Constitutive and LPS-induced expression of MCP-1 and IL-8 by human uveal melanocytes in vitro and relevant signal pathways.

PURPOSE Melanocytes are one of the major cellular components in the uvea. Interleukin-8/CXCL8 and monocyte chemoattractant protein-1 (MCP-1/CCL2) are the two most important proinflammatory chemokines. We studied the constitutive and lipopolysaccharide (LPS)-induced expression of IL-8 and MCP-1 in cultured human uveal melanocytes (UM) and explored the relevant signal pathways. METHODS Conditioned media and cells were collected from UM cultured in medium with and without stimulation of LPS. Interleukin-8 and MCP-1 proteins and mRNAs were measured using an ELISA kit and RT-PCR, respectively. Nuclear factor (NF)-κB in nuclear extracts and phosphorylated p38 mitogen-activated protein kinase (MAPK), extracellular signal-regulated kinases1/2 (ERK1/2), and c-Jun N-terminal kinase1/2 (JNK1/2) in cells cultured with and without LPS were measured by ELISA kits. Inhibitors of p38 (SB203580), ERK1/2 (UO1026), JNK1/2 (SP600125), and NF-κB (BAY11-7082) were added to the cultures to evaluate their effects. RESULTS Low levels of IL-8 and MCP-1 proteins were detected in the conditioned media in UM cultured without serum. Lipopolysaccharide (0.01-1 μg/mL) increased IL-8 and MCP-1 mRNAs and proteins levels in a dose- and time-dependent manner, accompanied by a significant increase of phosphorylated JNK1/2 in cell lysates and NF-κB in nuclear extracts. Nuclear factor-κB and JNK1/2 inhibitors significantly blocked LPS-induced expression of IL-8 and MCP-1. CONCLUSIONS This is the first report on the expression and secretion of chemokines by UM. The data suggest that UM may play a role in the pathogenesis of ocular inflammatory diseases.
Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi-fidelity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. From simulation results and a real example using finite element analysis, our method outperforms the expected improvement (EI) criterion that works for single-accuracy experiments. Supplementary materials for this article are available online.
Novel stretch-sensor technology allows quantification of adherence and quality of home-exercises: a validation study

Objective To investigate if a new stretch sensor attached to an elastic exercise band can assist health professionals in evaluating adherence to home exercises. More specifically, the study investigated whether health professionals can differentiate elastic band exercises performed as prescribed, from exercises not performed as prescribed. Methods 10 participants performed four different shoulder-abduction exercises in two rounds (80 exercise scenarios in total). The scenarios were (1) low contraction speed, full range of motion (0–90°), (2) high contraction speed, full range of motion (0–90°), (3) low contraction speed, diminished range of motion (0–45°) and (4) unsystematic pull of the elastic exercise band. Stretch-sensor readings from each participant were recorded and presented randomly to the raters. Two raters were asked to differentiate between unsystematic pull (scenario 4), from shoulder abduction strength exercises (scenarios 1–3). The next two raters were asked to identify the four different exercise scenarios (scenarios 1–4). Results The first two raters were able to differentiate between unsystematic pull (scenario 4) from shoulder abduction strength exercises (scenarios 1–3). They made no errors (100% success rate). The second two raters were both able to identify each of the 80 scenarios (scenarios 1–4). They too made no errors (100% success rate). Conclusions The stretch-sensor readings from the elastic exercise band allow health professionals to quantify whether strength-exercises have been performed as prescribed. These findings have great implications for future clinical practice and research where home exercises are the drugs-of-choice, as they enable clinicians and researchers to measure the exact adherence and quality of the prescribed exercises.
Building emotional resilience over 14 sessions of emotion focused therapy: Micro-longitudinal analyses of productive emotional patterns

Abstract Objective: Pascual-Leone and Greenberg’s sequential model of emotional processing has been used to explore process in over 24 studies. This line of research shows emotional processing in good psychotherapy often follows a sequential order, supporting a saw-toothed pattern of change within individual sessions (progressing “2-steps-forward, 1-step-back”). However, one cannot assume that local in-session patterns are scalable across an entire course of therapy. Thus, the primary objective of this exploratory study was to consider how the sequential patterns identified by Pascual-Leone, may apply across entire courses of treatment. Method: Intensive emotion coding in two separate single-case designs were submitted for quantitative analyses of longitudinal patterns. Comprehensive coding in these cases involved recording observations for every emotional event in an entire course of treatment (using the Classification of Affective-Meaning States), which were then treated as a 9-point ordinal scale. Results: Applying multilevel modeling to each of the two cases showed significant patterns of change over a large number of sessions, and those patterns were either nested at the within-session level or observed at the broader session-by-session level of change. Discussion: Examining successful treatment cases showed several theoretically coherent kinds of temporal patterns, although not always in the same case. Clinical or methodological significance of this article: This is the first paper to demonstrate systematic temporal patterns of emotion over the course of an entire treatment. (1) The study offers a proof of concept that longitudinal patterns in the micro-processes of emotion can be objectively derived and quantified. (2) It also shows that patterns in emotion may be identified on the within-session level, as well as the session-by-session level of analysis. (3) Finally, observed processes over time support the ordered pattern of emotional states hypothesized in Pascual-Leone and Greenberg’s (2007) model of emotional processing.
Microarray and Serial Analysis of Gene Expression Analyses Identify Known and Novel Transcripts Overexpressed in Hematopoietic Stem Cells

The human CD34+/CD38−/Lin− cell subset, comprising ∼1–10% of the CD34+ cell population, contains few of the less primitive hematopoietic (lineage-committed) progenitor cells (HPCs) but most of the primitive in vivo engrafting (lympho-)hematopoietic stem cells (HSCs). We analyzed gene expression in CD34+/CD38−/Lin− cell populations isolated from normal human adult donor bone marrow, neonatal placental/umbilical cord blood, and mobilized adult donor peripheral blood stem-progenitor cells. As measured by Affymetrix microarrays, 4746 genes were expressed in CD34+/CD38−/Lin− cells from all three tissues. We also determined the transcriptomes of the stem cell-depleted, HPC-enriched CD34+/[CD38/Lin]++ cell population from each tissue. Comparison of CD34+/CD38−/Lin− (HSC-enriched) versus CD34+/[CD38/Lin]++ (HPC-enriched, HSC-depleted) cells from each tissue yielded 81 genes overrepresented and 90 genes underrepresented, common to all three of the CD34+/CD38−/Lin− cell populations. These transcripts, which are selectively expressed in HSCs from all three tissues, include a number of known genes (e.g., transcription factors, receptors, and signaling molecules) that might play roles in key functions (e.g., survival, self-renewal, differentiation, and/or migration/adhesion) of human HSCs. Many genes/transcripts of unknown function were also detected by microarray analysis. Serial analysis of gene expression of the bone marrow HSC and HPC populations confirmed expression of most of the overrepresented transcripts for which reliable serial analysis of gene expression tags were detected and additionally suggested that current microarrays do not detect as many as 30% of the transcripts expressed in HSCs, including a number of previously unknown transcripts. This work is a step toward full definition of the transcriptome of normal human HSCs and may identify new genes involved in leukemogenesis and cancer stem cells.
Linearization of RF power amplifiers using an enhanced memory polynomial predistorter

Radio frequency power amplifiers (PAs) play a key-role in transceivers for mobile communications and their linearity is a crucial aspect. In order to meet the linearity requirements dictated by the standard at a reasonable efficiency, the usage of a linearization technique is required. In this paper we propose a linearization by means of a new type of digital predistorter, defined directly in the I-Q domain. The architecture of the proposed predistorter can be understood as an enhancement of the memory polynomial model (MPM) by means of additional I-Q terms. The usage of the proposed predistorter allows a more robust linearization of the whole RF transmitter because the enhancement of the model with additional I-Q terms can guarantee a more versatile compensation which is beneficial when the distortion comes from the joint contribution of the PA and the quadrature modulator. The proof of concept is achieved by measurements on a commercial PA in GaN technology and the performance of the proposed predistorter is illustrated.
Callous–unemotional traits affect adolescents' perception of collaboration

Background How is the perception of collaboration influenced by individual characteristics, in particular high levels of callous–unemotional (CU) traits? CU traits are associated with low empathy and endorsement of negative social goals such as dominance and forced respect. Thus, it is possible that they could relate to difficulties in interpreting that others are collaborating based on a shared goal. Methods In the current study, a community sample of 15‐ to 16‐year olds participated in an eye tracking task measuring whether they expect that others engaged in an action sequence are collaborating, depending on the emotion they display toward each other. Positive emotion would indicate that they share a goal, while negative emotion would indicate that they hold individual goals. Results When the actors showed positive emotion toward each other, expectations of collaboration varied with CU traits. The higher adolescents were on CU traits, the less likely they were to expect collaboration. When the actors showed negative emotion toward each other, CU traits did not influence expectations of collaboration. Conclusions The findings suggest that CU traits are associated with difficulty in perceiving positive social interactions, which could further contribute to the behavioral and emotional problems common to those with high CU traits.
Using Fuzzy Technology in Ambient Intelligence Environments

Ambient intelligence (AmI, shortly) gathers best results from three key technologies, ubiquitous computing, ubiquitous communication, and intelligent user friendly interfaces. The functional and spatial distribution of tasks is a natural thrust to employ multi-agent paradigm to design and implement AmI environments. Two critical issues, common in most of applications, are (1) how to detect in a general and efficient way "context" from sensors and (2) how to process contextual information in order to improve the functionality of services. In this work we experiment a framework where hybrid techniques (distributed fuzzy control, mobile agents, fuzzy rules induction algorithms) are mixed to gain flexibility and uniformity
Exploiting Local Class Information in Extreme Learning Machine

In this paper we propose an algorithm for Single-hidden Layer Feedforward Neural networks training. Based on the observation that the learning process of such networks can be considered to be a non-linear mapping of the training data to a high-dimensional feature space, followed by a data projection process to a lowdimensional space where classification is performed by a linear classifier, we extend the Extreme Learning Machine (ELM) algorithm in order to exploit the local class information in its optimization process. The proposed Local Class Variance Extreme Learning Machine classifier is evaluated in facial image classification problems, where we compare its performance with that of other ELM-based classifiers. Experimental results show that the incorporation of local class information in the ELMoptimization process enhances classification performance.