Miracle-dz/UniFAR-FTUs huggingface dataset:
3D printed flexible substrate with pneumatic driven electrodes for health monitoring

Telemedical methods enable remote patient monitoring and healthcare at a distance. Besides, fitness tracker and sport watches are currently trending electronic products to generate awareness of health parameters in daily life. Especially, the long-term and continuous measurement of electrophysiological signals such as electrocardiogramm (ECG) becomes increasingly attractive for telemedical applications. Typically used disposable Ag/AgCl wet electrodes for good skin-electrode contact can potentially cause skin irritation and rashes. This paper presents a low cost, individual and flexible substrate for skin electrodes to be applied in future consumer electronic or professional applications. It enables an alternative contact method of the electrode to the skin by applying a pressure during the measurement and hence good contact. If no measurement is needed pressure can be released and the electrode loses skin contact. The 3D printed polymer module is 4 mm thick and comprises a pressure chamber, silver electrodes and insulation layer. The airtight printed membrane of flexible filament, which expands when inflating the chamber, may be printed in different thicknesses and shapes, much thinner than the present 4mm. This enables a high individuality for various applications. Pressure up to 150 kPa was applied and leads to dilatation of 1400 μm. First tests on skin when measuring electrodermal activity (EDA) show promising results for future applications.
Hardware-software collaboration for secure coexistence with kernel extensions

Our society is dependent upon computer systems that are the target of a never-ending siege against their resources. One powerful avenue for exploitation is the operating system kernel, which has complete control of a computer system's resources. The current methodology for kernel design, which involves loadable extensions from third parties, facilitates compromises. Most of these extensions are benign, but in general they pose a threat to system trustworthiness: they run as part of the kernel and some of them can be vulnerable or malicious. This situation is paradoxical from a security point of view: modern OSes depend, and must co-exist, with untrustworthy but needed extensions. Similarly, the immune system is continuously at war against various types of invaders and, through evolution, has developed highly successful defense mechanisms. Collaboration is one of these mechanisms, where many players throughout the body effectively communicate to share attack intelligence. Another mechanism is foreign body co-existence with its microbiota. Remarkably, these properties are not leveraged in kernel defense approaches. Security approaches at the OS and virtual machine layers do not cooperate with each other or with the hardware. This paper advocates a new paradigm for OS defense based on close collaboration between an OS and the hardware infrastructure, and describes a hardware-software architecture realizing this vision. It also discusses the architecture design at the OS and hardware levels, including experimental results from an emulator-based prototype, and aspects of an ongoing hardware implementation. The emulator-based proof-of-concept prototype, Ianus, uses Linux as the OS and the Bochs x86 emulator as the architecture layer. It successfully minimized kernel extensions interactions with the original kernel. Its security was evaluated with real rootkits and benign extensions. Ianus' performance was analyzed with system and CPU benchmarks and it caused a small overhead to the system (approximately 12%).
Human Pose Estimation for RGBD Imagery with Multi-Channel Mixture of Parts and Kinematic Constraints

In this paper, we present a approach that combines monocular and depth information with a multichannel mixture of parts model that is constrained by a structured linear quadratic estimator for more accurate estimation of joints in human pose estimation. Furthermore, in order to speed up our algorithm, we introduce an inverse kinematics optimization that allows us to infer additional joints that were not included in the original solution. This allows us to train in less time and with only a subset of the total number of joints in the final solution. Our results show a significant improvement over state of the art methods on the CAD60 and our own dataset. Also, our method can be trained in less time and with smaller fraction of training samples when compared to state of the art methods. Key–Words: DPM, Kalman Filter, Pose Estimation, Kinematic Constraints
The Codon Usage of Lowly Expressed Genes Is Subject to Natural Selection

Abstract Codon usage bias affects the genomes of organisms from all kingdoms of life and results from both background substitution biases and natural selection. Natural selection on codon usage to increase translation accuracy and efficiency has long been known to affect gene sequences. Such selection is stronger on highly, compared with lowly expressed genes, resulting in higher levels of codon bias within genes with higher expression levels. Additionally, selection on translation accuracy affects more strongly codons encoding conserved amino acids, since these will more often affect protein folding and/or function. By applying tests of selection on the gene sequences of the bacterium Escherichia coli, we demonstrate that both highly and lowly expressed genes display signals of selection on codon usage. Such signals are found for both conserved and less conserved amino acid positions, even within the 10% of E. coli genes expressed at the lowest levels. We further demonstrate experimentally that single synonymous codon replacements within a lowly expressed, essential gene can carry substantial effects on bacterial fitness. Combined, our results demonstrate that even within genes expressed at relatively low levels there is substantial selection on codon usage and that single synonymous codon replacements within such genes can have a marked effect on bacterial fitness.
The Correlation between Left Atrial Deformation Indices and the CHA2DS2 -VASc Risk Score in Patients with Atrial Fibrillation

Objectives: To assess the relation between left atrial systolic strain and CHA2DS2 -VASc score in patients with non valvular atrial fibrillation and to assess whether it can be used in guiding the decision for oral anticoagulation. Methods: The study included 100 patients with non- valvular persistent AF (group I) compared to 100 individuals with sinus rhythm of matching age and gender (group II). Standard two-dimensional echocardiography, PW Doppler and TDI derived velocity and strains were used to assess LA function then its correlation with CHA2DS2-VASc score in group I was evaluated. Results: The prevalence of DM (P<0.001), HTN (P=0.001), prior stroke (P<0.001), heart failure (P < 0.001) and peripheral vascular disease (P < 0.001) was increased in patients in group I. Group I showed significant increase in LA diameters (anterio-posterior, transverse and longitudinal) P EÂ‚ 0.001, LA volumes (maximal and minimal P < 0.001 and mitral E/e" ratio P EÂ‚ 0.05. The correlation between LA emptying fraction and CHA2DS2 - VASc score was negative and significant (P < 0.05). Systolic LA strain was significantly reduced in patients with AF (P < 0.001) and it was negatively correlated to CHA2DS2 - VASc score but without statistical significance. There was no significant difference of LA systolic strain between the CHA2DS2 - VASc score of < 2 points and ≥ 2 points (P = 0.52). Systolic LA strain ≤ 17.44 was shown to have the best diagnostic accuracy (sensitivity = 42.11 %; specificity = 62.07%) in predicting CHA2DS2 - VASc ≥ 2. Conclusion: LA systolic strain is significantly reduced in AF patients and negatively correlated to CHA2DS2- VASc score and no significant difference between LA systolic strain in patients with CHA2DS2 - VASc score of < 2 points and ≥ 2 points so LA strain may be a tool that helps in guiding the decision for oral anticoagulation.
How Does the Unconscious “Think”?

Recent research indicates that unconscious thought may circumvent many of the problems resulting from the limited processing capacity of conscious thought. Although some light has been shed on the limitations of these benefits, at present little empirical investigation offers insight into how the unconscious might improve certain tasks. This research investigates one possible source of the ability of the unconscious to consolidate information by replicating the results of a temporal construal experiment. The results provide evidence for the hypothesis that unconscious thought operates by processing information at an abstract level, which supports some recently proposed limitation of unconscious thought.
Active Structure From Motion: Application to Point, Sphere, and Cylinder

In this paper, we illustrate the application of a nonlinear active structure estimation from motion (SfM) strategy to three problems, namely 3-D structure estimation for 1) a point, 2) a sphere, and 3) a cylinder. In all three cases, an appropriate parameterization reduces the problem to the estimation of a single quantity. Knowledge of this estimated quantity and of the available measurements allows for then retrieving the full 3-D structure of the observed objects. Furthermore, in the point feature case, two different parameterizations based on either a planar or a spherical projection model are critically compared. Indeed, the two models yield, somehow unexpectedly, to different convergence properties for the SfM estimation task. The reported simulative and experimental results fully support the theoretical analysis and clearly show the benefits of the proposed active estimation strategy, which is in particular able to impose a desired transient response to the estimation error equivalent to that of a reference linear second-order system with assigned poles.
Quantitative divergence of the bacterial root microbiota in Arabidopsis thaliana relatives

Significance All plants carry distinctive bacterial communities on and inside organs such as roots and leaves, collectively called the plant microbiota. How this microbiota diversifies in related plant species is unknown. We investigated the diversity of the bacterial root microbiota in the Brassicaceae family, including three Arabidopsis thaliana ecotypes, its sister species Arabidopsis halleri and Arabidopsis lyrata, and Cardamine hirsuta. We show that differences in root microbiota profiles between these hosts are largely quantitative and that host phylogenetic distance alone cannot explain the observed microbiota diversification. Our work also reveals a largely conserved and taxonomically narrow root microbiota, which comprises stable community members belonging to the Actinomycetales, Burkholderiales, and Flavobacteriales. Plants host at the contact zone with soil a distinctive root-associated bacterial microbiota believed to function in plant nutrition and health. We investigated the diversity of the root microbiota within a phylogenetic framework of hosts: three Arabidopsis thaliana ecotypes along with its sister species Arabidopsis halleri and Arabidopsis lyrata, as well as Cardamine hirsuta, which diverged from the former ∼35 Mya. We surveyed their microbiota under controlled environmental conditions and of A. thaliana and C. hirsuta in two natural habitats. Deep 16S rRNA gene profiling of root and corresponding soil samples identified a total of 237 quantifiable bacterial ribotypes, of which an average of 73 community members were enriched in roots. The composition of this root microbiota depends more on interactions with the environment than with host species. Interhost species microbiota diversity is largely quantitative and is greater between the three Arabidopsis species than the three A. thaliana ecotypes. Host species-specific microbiota were identified at the levels of individual community members, taxonomic groups, and whole root communities. Most of these signatures were observed in the phylogenetically distant C. hirsuta. However, the branching order of host phylogeny is incongruent with interspecies root microbiota diversity, indicating that host phylogenetic distance alone cannot explain root microbiota diversification. Our work reveals within 35 My of host divergence a largely conserved and taxonomically narrow root microbiota, which comprises stable community members belonging to the Actinomycetales, Burkholderiales, and Flavobacteriales.
Identity Distancing and Targeted Advertisements: The Black Sheep Effect

ABSTRACT This research examines the effect of target marketing using the black sheep effect, which occurs when individuals judge likable ingroup members more positively than similar outgroup members, while judging unlikable ingroup members more negatively than similar outgroup members. The results of two experiments show that individuals feel more targeted by ads that feature members of their ingroup that are more prototypical and likeable, and feel less targeted by advertisements featuring models who violate the group's positive image on some trait, making them nonprototypical and unlikeable. Theoretical implications regarding the impact of intragroup processes in consumer persuasion effects and target marketing are discussed.
Optimization of Yield in Magnetic Cell Separations Using Nickel Nanowires of Different Lengths

Ferromagnetic nanowires are shown to perform both high yield and high purity single‐step cell separations on cultures of NIH‐3T3 mouse fibroblast cells. The nanowires are made by electrochemical deposition in nanoporous templates, permitting detailed control of their chemical and physical properties. When added to fibroblast cell cultures, the nanowires are internalized by the cells via the integrin‐mediated adhesion pathway. The effectiveness of magnetic cell separations using Ni nanowires 350 nm in diameter and 5–35 micrometers long in field gradients of 40 T/m was compared to commercially available superparamagnetic beads. The percent yield of the separated populations is found to be optimized when the length of the nanowire is matched to the diameter of the cells in the culture. Magnetic cell separations performed under these conditions achieve 80% purity and 85% yield, a 4‐fold increase over the beads. This effect is shown to be robust when the diameter of the cell is changed within the same cell line using mitomycin‐C.
Memorization Test and Resting State EEG Components in Mild and Subjective Cognitive Impairment.

BACKGROUND Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer's disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. OBJECTIVE The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. METHOD We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. RESULTS During cognitive task, α-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The α -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. CONCLUSION This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis.
Predicting Online Political Participation

Although we have a broad understanding of the factors that predict traditional forms of political participation, we know comparatively less about the determinants of online political participation. Among the limited research that explores the predictors of online political participation, news seeking is often found to be an important factor; however, many studies fail to consider selective exposure and the distinct influence of differing types of information. In this study, I ask, “What factors predict online participation, and what role does selective exposure play in this relationship? ” Using a nationally representative sample (N = 2,250) and a selection model to correct for biased estimates of online political participation, I find that online political participation is not well predicted by the same resource-related determinants that influence traditional participation; specifically, income and age are unrelated to online political participation among Internet users. Second, I find that exposure to political information that reinforces one’s point of view predicts higher levels of online political participation when compared with differing information or information with no point of view. Finally, I conduct a subset analysis of partisan identifiers to examine differences in these relationships among Republicans and Democrats.
Benefits of remote real-time side-effect monitoring systems for patients receiving cancer treatment

In Australia, the incidence of cancer diagnoses is rising along with an aging population. Cancer treatments, such as chemotherapy, are increasingly being provided in the ambulatory care setting. Cancer treatments are commonly associated with distressing and serious side-effects and patients often struggle to manage these themselves without specialized real-time support. Unlike chronic disease populations, few systems for the remote real-time monitoring of cancer patients have been reported. However, several prototype systems have been developed and have received favorable reports. This review aimed to identify and detail systems that reported statistical analyses of changes in patient clinical outcomes, health care system usage or health economic analyses. Five papers were identified that met these criteria. There was wide variation in the design of the monitoring systems in terms of data input method, clinician alerting and response, groups of patients targeted and clinical outcomes measured. The majority of studies had significant methodological weaknesses. These included no control group comparisons, small sample sizes, poor documentation of clinical interventions or measures of adherence to the monitoring systems. In spite of the limitations, promising results emerged in terms of improved clinical outcomes (e.g. pain, depression, fatigue). Health care system usage was assessed in two papers with inconsistent results. No studies included health economic analyses. The diversity in systems described, outcomes measured and methodological issues all limited between-study comparisons. Given the acceptability of remote monitoring and the promising outcomes from the few studies analyzing patient or health care system outcomes, future research is needed to rigorously trial these systems to enable greater patient support and safety in the ambulatory setting.
A Network Analysis of Leadership Theory

We investigated the status of leadership theory integration by reviewing 14 years of published research (2000 through 2013) in 10 top journals (864 articles). The authors of these articles examined 49 leadership approaches/theories, and in 293 articles, 3 or more of these leadership approaches were included in their investigations. Focusing on these articles that reflected relatively extensive integration, we applied an inductive approach and used graphic network analysis as a guide for drawing conclusions about the status of leadership theory integration. All 293 articles included in the analysis identified 1 focal theory that was integrated with 2 or more supporting leadership theories. The 6 leadership approaches most often appearing as the focal theory were transformational leadership, charismatic leadership, strategic leadership, leadership and diversity, participative/shared leadership, and the trait approach to leadership. On the basis of inductive reflections on our analysis, we make two key observations. First, the 49 focal leadership theories qualify as middle-range theories that are ripe for integration. Second, drawing from social network theory, we introduce the term “theoretical neighborhood” to describe the focal theoretical networks. Our graphical inductive analyses reveal potential connections among neighboring middle-range leadership theories that merit investigation and, hence, identify promising future directions for achieving greater theoretical integration. We provide an online supplement with 10 additional leadership theory graphs and analyses: leadership in teams and decision groups, ethical leadership, leader and follower cognitions, leadership emergence, leadership development, emotions and leadership, implicit leadership, leader-member exchange, authentic leadership, and identity and identification process theories of leadership.
Influence of temperature on dynamic fault behavior due to resistive defects in FinFET-based SRAMs

FinFET technology has emerged as the most promising alternative to continue the scaling-down of technological nodes due to its superior electric properties. In parallel, the need to store more information on chip led to Static Random Access Memories (SRAMs) occupying the greatest part of silicon area of Systems-on-Chips (SoCs). During manufacturing, SRAMs can be affected by resistive defects that may lead to dynamic faults, considered one of the most important causes of test escape in deep-submicron technologies. In this context, this paper proposes to analyze the impact of temperature on the dynamic faulty behavior during manufacturing tests of SRAM cells affected by weak resistive defects. In more detail, critical resistances and the number of operations necessary to sensitize faults are investigated. Additionally, the concept of Dynamic Behavior Window is presented and characterized. The proposed analysis has been performed using SPICE simulations adopting a 20nm FinFET compact model.
Prevalence, Cognitive and Socio-Demographic Determinants of Prostate Cancer Screening

Screening may be effective for reducing deaths due to prostate cancer. The aim of this study was determine the prevalence and determinants influencing prostate cancer early detection behaviors based on the theory planned behavior (TPB). In this cross-sectional study, conducted in the west of Iran, a total of 250 men aged 50 to 70 years old were randomly selected to participate. Of these, 200 (80%) signed the consent form and voluntarily agreed to take part. A structured questionnaire based on TPB constructs was applied for collecting data by interview. Analyses were conducted with SPSS version 16 using bivariate correlations, and logistic and linear regression. Some 26.5% of the participants demonstrated prostate cancer early detection behavior. Age higher than 60 (OR: 5.969), academic education (OR: 2.904), number of family members more than four (OR: 3.144), and knowledge about prostate cancer (OR: 3.693) were the most influential predictive factors for early detection behavior. Furthermore, among the TPB constructs, attitude (OR=1.090) and subjective norms (OR=1.280) were the most influential predictors. Attitude, subjective norms, and perceived behavioral control accounted for 43% of the variation in the outcome measure of the intention to screen for prostate cancer (adjusted R squared= 0.43, F= 49.270 and P < 0.001). Designing and implementation programs to increase positive attitudes and encourage subjective norms towards prostate cancer screening behavior may be useful for promotion of early detection.