Miracle-dz/UniFAR-FTUs huggingface dataset:
Mother–infant sleep patterns and parental functioning of room-sharing and solitary-sleeping families: a longitudinal study from 3 to 18 months

Study Objectives To examine longitudinally differences in (a) objective and subjective sleep patterns and (b) parenting functioning (i.e., maternal emotional distress, maternal separation anxiety and parental involvement in infant care( between room-sharing and solitary sleeping mother-infant dyads. Methods Maternal and infant sleep, sleeping arrangements and parental functioning were assessed at three (N=146), six (N=141), twelve (N=135), and eighteen (N=130) months postpartum. Maternal and infant sleep were assessed with actigraphy and sleep diaries for 5 nights. Questionnaires were used to assess sleeping arrangements, nighttime breastfeeding, and parental functioning. Results Persistent room-sharing mothers (i.e., sharing a room with the infant on at least three assessment points) had significantly lower actigraphy-based sleep percent, lower longest sleep periods and more night-wakings than persistent solitary sleeping mothers. For infants, differences in actigraphic sleep were found only in longest sleep period, although mothers of persistent room-sharing infants reported more infant night-wakings than mothers of persistent solitary sleeping infants. The trajectories of maternal and infant sleep in both room-sharing and solitary sleeping groups demonstrated that sleep became more consolidated with time. Group differences indicated higher maternal separation anxiety and lower paternal overall and nighttime involvement in infant caregiving in room-sharing families compared to solitary-sleeping families. Conclusions The findings are discussed in light of the latest American Academy of Pediatrics recommendation to room-share until 12 months postpartum. Although no causal effects can be inferred from this study, maternal sleep quality and certain parenting characteristics seem to be important factors to consider when parents consult about sleeping arrangements.
Nonlinear dynamics of divide‐by‐two injection‐locked frequency dividers in locked operation mode

A method for analyzing the nonlinear dynamics of the injection‐locked frequency dividers in synchronized operation mode is presented, including the stability analysis of locked states. We use a specific divide‐by‐two circuit, namely a differential LC CMOS divider with a complementary topology, as a guideline for presentation, showing that the sizing of the devices significantly affects the synchronization mechanism of the divider, which exhibits a very rich dynamical behavior. We provide closed‐form expressions to determine the amplitude and the phase in the locked state, as well as the locking range, leading to accurate results, which are validated by numerical simulations. The presented analysis of the frequency divider dynamics enables us to establish that stable locked oscillations occur on the whole locking range predicted by the well‐known Adler's equation and that these are possible also beyond that range. Copyright © 2013 John Wiley & Sons, Ltd.
Facilitating HRI by Mixed Reality Techniques

Mobile robots start to appear in our everyday life, e.g., in shopping malls, airports, nursing homes or warehouses. Often, these robots are operated by non-technical staff with no prior experience/education in robotics. Additionally, as with all new technology, there is certain reservedness when it comes to accepting robots in our personal space. In this work, we propose making use of state-of-the-art Mixed Reality (MR) technology to facilitate acceptance and interaction with mobile robots. By integrating a Microsoft HoloLens into the robot»s operating space, the MR device can be used to a) visualize the robot»s behavior-state and sensor data, b) visually notify the user about planned/future behavior and possible problems/obstacles of the robot, and c) to actively use the device as an additional external sensor source. Moreover, by using the HoloLens, users can operate and interact with the robot without being close to it, as the robot is able to sense with the users» eyes.
BioPAXViz: a cytoscape application for the visual exploration of metabolic pathway evolution

Summary: BioPAXViz is a Cytoscape (version 3) application, providing a comprehensive framework for metabolic pathway visualization. Beyond the basic parsing, viewing and browsing roles, the main novel function that BioPAXViz provides is a visual comparative analysis of metabolic pathway topologies across pre‐computed pathway phylogenomic profiles given a species phylogeny. Furthermore, BioPAXViz supports the display of hierarchical trees that allow efficient navigation through sets of variants of a single reference pathway. Thus, BioPAXViz can significantly facilitate, and contribute to, the study of metabolic pathway evolution and engineering. Availability and Implementation: BioPAXViz has been developed as a Cytoscape app and is available at: https://github.com/CGU‐CERTH/BioPAX.Viz. The software is distributed under the MIT License and is accompanied by example files and data. Additional documentation is available at the aforementioned GitHub repository. Contact: ouzounis@certh.gr.
A Deep Autoencoder approach for Speaker Identification

Speaker Identification (SID) is one of the most prominent and leading research arena that gained tremendous momentum in the recent years. This increased attention of machine learning approaches, especially deep neural networks (DNNs), further enhanced the interest towards SID research. Despite success stories of DNNs, there has been limited attention towards deep autoencoders (DAEs) and their applications has not been explored properly. In this paper, we attempt to address this gap by applying DAEs to identify speakers using analytical and experimental research prospects. The experiments were conducted using the data obtained from 84 speakers provided in AN4 corpus. To understand the significance of 'depth', i.e. the number of autoencoders in the DAE, multiple experiments with different number of autoencoder layers in the DAE were conducted. The experimental results show that DAE network with three autoencoders was able to achieve superior identification accuracy of 98.8% over the traditional neural networks. The findings of this study confirm the importance of 'depth' as highlighted in previous deep learning studies especially with the difference in accuracy between regular back propagation and layer-wise training. This paper further provides a new direction in the implementation of deep autoencoders for speaker identification.
Autobalancing Analog Front End for Full-Range Differential Capacitive Sensing

The authors here propose an analog interface for differential capacitance estimation, able to reveal and quantify capacitive variations. Different from other works in the literature, the proposed interface can operate on a full-range scale. This solution takes inspiration from a preliminary work of the same authors, whose working principle is based on a modified De-Sauty AC bridge configuration; in particular, two (differential) capacitors and two resistors are employed, one of which is implemented by a voltage-controlled resistor (VCR). In this paper, the electronic interface has been redesigned to obtain full-range operation and a linear input–output characteristic. The implemented autobalancing mechanism controls the VCR generating a reference voltage following the sensor output. Simulation results in two different circuit configurations performed by OrCAD PSpice have shown a very good agreement with a theoretical model implemented in MATLAB/Simulink environment. In addition, an evaluation of the goodness of the experimental measurements at steady and unsteady conditions is given. Experimental tests on a discrete-component prototype have been carried out using an automated test equipment including National Instruments tools and a dedicated software in the LabVIEW environment. Measurements have shown satisfactory results, the standard deviation being on the order of 0.01, in the worst case. The linearity error has been evaluated as well, resulting in lower than 1% full scale.
Tamm–Horsfall Protein is a Potent Immunomodulatory Molecule and a Disease Biomarker in the Urinary System

Tamm–Horsfall protein (THP), or uromodulin (UMOD), is an 80–90-kDa phosphatidylinositol-anchored glycoprotein produced exclusively by the renal tubular cells in the thick ascending limb of the loop of Henle. Physiologically, THP is implicated in renal countercurrent gradient formation, sodium homeostasis, blood pressure regulation, and a defense molecule against infections in the urinary system. Investigations have also revealed that THP is an effective binding ligand for serum albumin, immunoglobulin G light chains, complement components C1 and C1q, interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor (TNF)-α, and interferon-γ through its carbohydrate side chains for maintaining circulatory and renal immune homeostasis. Thus, THP can be regarded as part of the innate immune system. UMOD mutations play crucial roles in congenital urolithiasis, hereditary hyperuricemia/gout, and medullary cystic kidney diseases. Recent investigations have focused on the immunomodulatory effects of THP on immune cells and on THP as a disease biomarker of acute and chronic kidney diseases. Our studies have suggested that normal urinary THP, through its epidermal growth factor (EGF)-like domains, binds to the surface-expressed EGF-like receptors, cathepsin G, or lactoferrin to enhance polymorphonuclear leukocyte phagocytosis, proinflammatory cytokine production by monocytes/macrophages, and lymphocyte proliferation by activating the Rho family and mitogen-activated protein kinase signaling pathways. Furthermore, our data support both an intact protein core structure and carbohydrate side chains are important for the different protein-binding capacities of THP. Prospectively, parts of the whole THP molecule may be used for anti-TNF-α therapy in inflammatory diseases, autoantibody-depleting therapy in autoimmune disorders, and immune intensification in immunocompromised hosts.
Apathy Is Associated With Greater Decline in Subjective, but not in Objective Measures of Physical Functioning in Older People Without Dementia

Background In older people, both apathy and depression (which frequently co-occurs with apathy) have been associated with poor physical functioning, a major health concern. We investigated the association between apathy and physical functioning in older people without dementia and whether this association is modified by depression. Methods We used the data from 380 older participants (with and without depression) taking part in the Netherlands Study of Depression in Older Persons, with baseline scores on the Apathy Scale and baseline and 2-year follow-up scores on at least one measure of physical functioning. These included the International Physical Activities Questionnaire (IPAQ, self-reported), WHO Disability Assessment Schedule (WHO-DASII mobility subset, self-reported), walking speed, or handgrip strength. Multivariable linear regression analyses were performed to examine the association between apathy at baseline and physical functioning at 2-year follow-up. We also investigated effect modification by sex, age, and depression. Results Cross-sectionally, participants with higher baseline Apathy Scale scores performed significantly worse on all measures of physical functioning. Longitudinally, higher baseline Apathy Scale scores were associated with higher delta scores on the IPAQ (B = -59.81) in the basic model, and higher delta scores on the WHO-DASII (B = .09) in all models. Apathy was not associated with higher delta scores for walking speed or handgrip strength. Furthermore, sex, age, and depression did not modify any association. Conclusion In a Dutch cohort of older people without dementia, apathy was associated with more decline in self-reported, but not in objective physical functioning. Sex, age, and depression did not modify these associations. In older people with apathy, subjective decline may precede decline in physical performance tests.
Towards Data-driven Continuous Compliance Testing

Recent studies show that security vulnerabilities are caused by neglecting best-practices for the configuration of software and the underlying infrastructure. Due to the rising complexity of software systems and the accelerated speed of software releases using mechanisms like continuous delivery the problem gets even more challenging. Existing processes and methods are not adequate to cope with these challenges. This paper proposes an approach for continuous compliance testing. Using well-known methods from software testing, this approach enables an organization to define, organize, and execute compliance tests in a structured and reusable way. We focus in our approach onto integrating a software-centric point of view for modeling compliance requirements. By embedding our approach into a deployment pipeline automated continuous compliance testing can be realized.
Learning and the transformative potential of citizen science

The number of collaborative initiatives between scientists and volunteers (i.e., citizen science) is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS) in the policy domain. We examined the transformative capacity of citizen science in particular learning through environmental CS as conservation tool. We reviewed the CS and social‐learning literature and examined 14 conservation projects across Europe that involved collaborative CS. We also developed a template that can be used to explore learning arrangements (i.e., learning events and materials) in CS projects and to explain how the desired outcomes can be achieved through CS learning. We found that recent studies aiming to define CS for analytical purposes often fail to improve the conceptual clarity of CS; CS programs may have transformative potential, especially for the development of individual skills, but such transformation is not necessarily occurring at the organizational and institutional levels; empirical evidence on simple learning outcomes, but the assertion of transformative effects of CS learning is often based on assumptions rather than empirical observation; and it is unanimous that learning in CS is considered important, but in practice it often goes unreported or unevaluated. In conclusion, we point to the need for reliable and transparent measurement of transformative effects for democratization of knowledge production.
Information Fusion on Oversegmented Images: An Application for Urban Scene Understanding

The large number of tasks one may expect from a driver assistance system leads to consider many object classes in the neighborhood of the so-called intelligent vehicle. In order to get a correct understanding of the driving scene, one has to fuse all sources of information that can be made available. In this paper, an original fusion framework working on segments of over-segmented images and based on the theory of belief functions is presented. The problem is posed as an image labeling one. It will first be applied to ground detection using three kinds of sensors. We will show how the fusion framework is flexible enough to include new sensors as well as new classes of objects, which will be shown by adding sky and vegetation classes afterward. The work was validated on real and publicly available urban driving scene data.
Noncontact Human–Machine Interface With Planar Probing Coils in a Differential Sensing Architecture

This paper presents a noncontact human–machine interface which is capable of sensing and indicating the position of a human hand that is approaching a probing coil. High sensitivity is achieved by utilizing a structure including two oscillators and a mixer to compare and extract the electromagnetic shift between two probing coils. The probing coils chosen in this system have a planar structure and small size, which can be easily built on a printed circuit board or integrated into a portable device for hand detection. The hand–coil interface is analyzed quantitatively for both the inductive and the capacitive links. Based on the analysis, a circuit model for the hand–coil interaction is presented. The proposed sensing circuit was built on an evaluation board with two commercial planar coils. A small phantom was used to imitate the hand electrical characteristic for a reliable and repeatable experimental setup. The measured results showed a hand-detection sensitivity of 10 kHz/mm at the output of the mixer stage and 30 mV/mm at the final output of the proposed interface.
Original Contribution A Prospective Study of Magnesium and Iron Intake and Pancreatic Cancer in Men

Many studies have investigated the relation between magnesium and iron intake and diabetes and, separately, between diabetes and pancreatic cancer. However, no known study has examined the direct association of magnesium and iron intake with pancreatic cancer risk. The authors obtained magnesium and iron intake data using food frequency questionnaires from the US male Health Professionals Follow-up Study, which began in 1986. During 851,476 person-years and 20 years of follow-up, 300 pancreatic cancer cases were documented. Cox proportional hazards models were used to estimate relative risks, adjusting for age, smoking, and body mass index. No associations were observed between magnesium or iron intake and pancreatic cancer (highest vs. lowest quintile: relative risk (RR) 1⁄4 0.94, 95% confidence interval (CI): 0.66, 1.32 and RR 1⁄4 0.93, 95% CI: 0.65, 1.34, respectively). Similarly, iron or magnesium supplement use was not related to pancreatic cancer. A statistically significant inverse relation was noted between magnesium and pancreatic cancer for subjects with a body mass index of 25 kg/m (RR 1⁄4 0.67, 95% CI: 0.46, 0.99; P-trend 1⁄4 0.04). Although, overall, no relation between magnesium or iron intake and pancreatic cancer was observed in this cohort of men, an inverse association with magnesium was suggested among overweight individuals, which should be examined in other studies.
The Advance Care Planning Readiness Scale: Development and Validation of a Measure of Willingness to Discuss and Acceptance of End-of-Life Care in Gynecologic Cancer Patients

Objective The objective of this article was to develop and validate a scale that assesses the readiness of gynecologic oncology patients to engage in advance care planning. Methods The Advance Care Planning Readiness Scale (ACPRS) was validated across 3 independent samples of gynecologic oncology patients. In step I, patients underwent cognitive interviewing to determine if the scale items were comprehensible and applicable to patients. Based on this, modifications to the scale (addition, removal, and merger of items) were completed. In step II, the revised scale was administered to a new sample of patients to assess scale reliability and validity. An exploratory factor analysis determined if the scale loaded onto unique factors. In step III, the revised scale was administered to a third sample of patients, and a confirmatory factor analysis was conducted to test the factor structure proposed in step II. Associations between ACPRS score and completion of advance directives were evaluated. Results Based on patients’ responses, the original ACPRS used in step I was modified to the ACPRS used in step II. The final 8-item ACPRS is a valid, reliable (Cronbach &agr; = 0.81) scale and has 2 primary factors. Women with medical power of attorney documents and living wills had higher ACPRS total scores than those who did not have these advance directives (P = 0.0030). Women with do-not-resuscitate (DNR) orders had higher ACPRS total scores than women without DNRs (P = 0.0176). Conclusions The ACPRS is a valid and reliable 8-item scale that assesses the readiness of gynecologic oncology patients to discuss advance care planning issues.
Deferoxamine-paper for iron(III) and vanadium(V) sensing

The development of a sensor based on the functionalization of common filter paper with deferoxamine (DFO) is proposed with the prospect to produce a solid phase for iron(III) and vanadium(V) sensing. The main features of this sensor are the simplicity of operation, good sensitivity and feasible applicability to real samples without the need of pre-treatment procedures. DFO was selected not only for it is easily anchored to the solid support, but also because it forms colored complexes with iron(III) and vanadium(V); hence, the developing of a simple colorimetric sensor can be considered. In particular, an innovative and economic way to perform colorimetric measurements using a desktop scanner is described. A complete characterization of the functionalized material is also reported.
An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.
Rapid hardware and software reconfiguration in a robotic workcell

In an increasingly competitive manufacturing industry it is becoming ever more important to rapidly react to changes in market demands. In order to satisfy these requirements, it is crucial that automated manufacturing processes are flexible and can be adapted to new production requirements quickly. In this paper we present a novel automatically reconfigurable robot workcell that addresses the issues of flexible manufacturing. The proposed workcell is reconfigurable in terms of hardware and software. The hardware elements of the workcell, both those selected off-the-shelf and those developed specifically for the system, allow for fast cell setup and reconfiguration, while the software aims to provide a modular, robot-independent, ROS-based programming environment. While the proposed workcell is being developed in such a way as to address the needs of production-oriented SMEs where batch sizes are relatively small, it will also be of interest to enterprises with larger production lines since it additionally targets high performance in terms of speed, interoperability of robotic elements, and ease of use.