Miracle-dz/UniFAR-FTUs huggingface dataset:
Maternal depression and antidepressant use during pregnancy and the risk of autism spectrum disorder in offspring

Background Results of some studies suggest that prenatal antidepressant exposure increases the risk of autism spectrum disorder (ASD) in offspring, while other studies suggest that depression independently increases the risk of having a child with ASD. Thus, confounding by indication is a concern. Objective The aim of this study was to estimate the risk of ASD in offspring of women who were exposed to antidepressants and/or had depression during pregnancy compared to unexposed women. Materials and methods We conducted a cohort study with nested sibling case–control analysis. Using the UK Clinical Practice Research Datalink (CPRD), we identified mother– baby pairs where the mother had ≥12 months of history before the delivery date and the child had ≥3 years of follow-up. Exposures during pregnancy were classified as 1) depression treated with antidepressants, 2) untreated depression, 3) other indications for antidepressant use, and 4) 4:1 match of unexposed women with no history of depression or antidepressant use. We calculated the prevalence of ASD and relative risk (RR) with 95% CI. In the sibling analysis, we compared exposure among ASD cases to that of non-ASD siblings born to the same mother. We calculated ORs and 95% CIs for women with treated and untreated depression, compared to unexposed. Results We identified 2,154 offspring with ASD among 194,494 mother–baby pairs. Compared to unexposed, the RR of ASD was 1.72 (95% CI 1.54–1.93) for treated depression and 1.50 (95% CI 1.28–1.75) for untreated depression, while the RR was not elevated in women who received antidepressants for other indications (RR =0.73, 95% CI 0.41–1.29). Additional analyses to assess the effects of severity of depression suggest that the risk of ASD in offspring increases with increasing severity, not with the antidepressant treatment. The results of the sibling analysis were similar to the main analysis. Conclusion Women with depression during pregnancy have an increased risk of having a child with ASD, regardless of antidepressant use.
Differential  $E$ -Field Coupling to Shielded  $H$ -Field Probe in Near-Field Measurements and a Suppression Approach

In near-field scanning using <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field probes, <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field coupling is a major concern. <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field suppression performance must be characterized before an <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field probe can be used for near-field scanning. Common method of measurement involves measuring the <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field coupling in the same location where the strongest <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field coupling occurs. In microstrip line traces, it is assumed that this occurs right above the center of the trace and less coupling at all other locations across the microstrip line. In this paper, we show that the maximum <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field coupling occurs at a location slightly offset from the trace center. The <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field coupling to a shielded <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field probe at such a position leads to differential-mode coupling, which the standard shield of an <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field probe is unable to suppress. The coupling mechanism is investigated and a differential <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field coupling suppression approach is proposed. For the <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-field probe used in this paper, a proposed floating plate is shown to improve the measured <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-field suppression ratio by a factor of 18 dB compared to a similar probe without this modification.
Optical coherence tomography angiography (OCTA) flow speed mapping technology for retinal diseases

ABSTRACT Introduction: Optical coherence tomography angiography (OCTA) is a noninvasive imaging modality for depth-resolved visualization of retinal vasculature. Angiographic data couples with structural data to generate a cube scan, from which en-face images of vasculature can be obtained at various axial positions. OCTA has expanded understanding of retinal vascular disorders and has primarily been used for qualitative analysis. Areas covered: Recent studies have explored the quantitative properties of OCTA, which would allow for objective assessment and follow-up of retinal pathologies. Various quantitative metrics have been developed, such as foveal avascular zone area and vessel density. However, quantitative assessment of the characteristics of retinal blood flow remains limited, as OCTA provides an image depicting either the presence or absence of flow at a particular region without information of relative velocities. The development of variable interscan time analysis (VISTA) overcomes this limitation. The VISTA algorithm generates a color-coded map of relative blood flow speeds. VISTA has already demonstrated utility in furthering our understanding of various retinal pathologies, such as geographic atrophy, choroidal neovascularization, aneurysmal type 1 neovascularization, and diabetic retinopathy. Expert commentary: VISTA, an OCTA flow speed mapping technique, may have a role in developing the utility of OCTA as a screening tool.
Recently isolated antidiabetic hydrolysates and peptides from multiple food sources: a review

Abstract Diabetes, a metabolic syndrome of global importance has been on a progressive rise in recent years. Several pharmacological approaches have been made, which have proved effective, but with underlying side effects. Bioactive hydrolysates (BHs) and peptides (BPs) from food sources, however, have shown the relative advantage of imparting less adverse effects. Furthermore, BHs and BPs from food have been discovered to impart their antidiabetic potentials through one or more mechanisms such as inhibition of digestive enzymes, inhibition of the antigenic enzyme – Dipeptyl peptidase IV (DPP-IV), decrease in blood glucose levels and increase in insulin uptake. Several plants and animal sources have been used as protein sources for the isolation of antidiabetic hydrolysates and peptides through different mechanisms and analytical techniques. This review integrates recent research information about several popular and unconventional food sources of BHs and BPs, their isolation techniques, antidiabetic effects and protein profiles. In addition, the fractionation technique(s) employed in each study and inhibition potentials of BHs and BPs are reviewed. This article is intended to supplement accessible scholarly literature and intellectual awareness on the subject of food-oriented approach for the management of diabetes.
Sleep disordered breathing in children disrupts the maturation of autonomic control of heart rate and its association with cerebral oxygenation

Sleep disordered breathing (SDB) affects 4–11% of children and is associated with adverse neurocognitive, behavioural and cardiovascular outcomes, including reduced autonomic control. The relationship between heart rate variability (HRV; a measure of autonomic control) and age found in non‐snoring control children was absent during sleep in children with SDB. Age significantly predicted increasing cerebral oxygenation during wake in non‐snoring control children, whereas during sleep, HRV significantly predicted decreasing cerebral oxygenation. Cerebral oxygenation was not associated with either age or HRV in children with SDB during both wake and sleep. SDB significantly disrupts the normal maturation of autonomic control and the positive association between autonomic control and cerebral oxygenation found in non‐snoring children, and we speculate that the dampened autonomic control exhibited by children with SDB may have an attenuating effect on cerebral autoregulation via the moderating influence of HRV on cerebral blood flow.
PGR5-Dependent Cyclic Electron Flow Protects Photosystem I under Fluctuating Light at Donor and Acceptor Sides1

PGR5-dependent CET protects PSI from photodamage under fluctuating light via the regulation of electron transport at both donor and acceptor sides of PSI. In response to a sudden increase in light intensity, plants must cope with absorbed excess photon energy to protect photosystems from photodamage. Under fluctuating light, PSI is severely photodamaged in the Arabidopsis (Arabidopsis thaliana) proton gradient regulation5 (pgr5) mutant defective in the main pathway of PSI cyclic electron transport (CET). Here, we aimed to determine how PSI is protected by two proposed regulatory roles of CET via transthylakoid ΔpH formation: (1) reservation of electron sink capacity by adjusting the ATP/NADPH production ratio (acceptor-side regulation) and (2) down-regulation of the cytochrome b6f complex activity called photosynthetic control for slowing down the electron flow toward PSI (donor-side regulation). We artificially enhanced donor- and acceptor-side regulation in the wild-type and pgr5 backgrounds by introducing the pgr1 mutation conferring the hypersensitivity of the cytochrome b6f complex to luminal acidification and moss Physcomitrella patens flavodiiron protein genes, respectively. Enhanced photosynthetic control partially alleviated PSI photodamage in the pgr5 mutant background but restricted linear electron transport under constant high light, suggesting that the strength of photosynthetic control should be optimized. Flavodiiron protein-dependent oxygen photoreduction formed a large electron sink and alleviated PSI photoinhibition, accompanied by the induction of photosynthetic control. Thus, donor-side regulation is essential for PSI photoprotection but acceptor-side regulation also is important to rapidly induce donor-side regulation. In angiosperms, PGR5-dependent CET is required for both functions.
Market Design for IoT Data and Services the Emergent 21Th Century Commodities

In this work we discuss and propose a marketplace concept for the Internet of Things (IoT). We start from the vision that unlike the current IoT landscape where tech and consulting companies provide complete “solutions” for some vertical markets, in future we might witness an “uberization” of IoT, where every person or company will be able to offer or “consume” sensor data, actuator access and data analytics services to/from anybody else, leading to several marketplaces where these IoT services will be traded and exchanged. In this line, we assume that data and information about the places, things and persons will be the major asset in our future society, and that physical objects and cloud-based computing environments will be simply the resources that will allow greater interaction between the physical and digital world. In this paper, we present our initial analysis about the main principles and technologies enabling future trade of sensor data and actuation access, and how it might affect the economic organization of our society today.
Spatio-temporal Mobile Data Traffic Modeling Using Fourier Transform Techniques

The exponential growth in mobile data traffic is forcing telecom operators to invest on new infrastructures. But, devising techniques for optimum network utilization, which can be provided by traffic modeling, has the potential to reduce investment cost. Modeling traffic variation in different service areas and time is also applicable for energy efficient network planning, understanding customers’ data traffic usage behavior and dynamic resource allocation. In this paper, based on a week data collected from 734 Base Stations of an operator in Addis Ababa, Ethiopia, we model the real traffic in space and time with a tunable accuracy. Firstly, a rectangle that can inscribe the geographical area of the city is selected and divided equally into N by N smaller groups. Then, to understand the temporal behavior of the data, the time-series data traffic of each group is transformed to spectral domain by using Fast Fourier Transform, where it is observed that all groups have the same four major frequency components but with different magnitude of coefficients and phases. Secondly, matrices corresponding to coefficient and phase values are transformed from spatial to spectral domain by applying Two Dimensional Discrete Cosine Transform. In the spectral domain higher frequency components that contain less information are removed out and the remaining are used for the reverse transform. The different application areas of the model for the operator require different level of accuracy which, in turn, is dependent on the level of frequency components truncation. As a result, we have developed a relation between model performance and truncation level making the model to be tunable around accuracy.
Purchasing Process Analysis with Process Mining of a Heavy Manufacturing Industry

The rapid growth of information and communication technologies has put companies under the pressure of continuously improving their business processes to be able to maintain their position in a highly competitive environment. For this purpose, process mining has recently emerged to analyze the behavior of organizations through the extraction of process related knowledge from the event data recorded in today’s information systems such as Supply Chain Management System, Workflow Management System, Enterprise Resource Planning, Customer Relationship Management System, etc. This paper presents an industrial application of process mining in a real purchasing process of a heavy manufacturing industry. The event data of this process are extracted from the Shipbuilding Processing Plan Management System of the company, filtered and analyzed using process mining techniques. The findings of the analysis can be used by the company to optimize and improve their processes.
Blood pressure in children with attention deficit/hyperactivity disorder.

Objectives Children with attention deficit/hyperactivity disorder (ADHD) are frequently treated with psycho-stimulant agents causing a modest but significant increase in blood pressure and heart rate. The objective of this study was to define blood pressure characteristics in children with ADHD treated with a variety of medications in a community setup. Methods Children registered at a large paediatric clinic in Calgary, AB with documented histories of ADHD were randomly contacted. Consenting participants had standardized office BP measurements, ambulatory blood pressure monitoring (ABPM) studies and were asked to complete the sleep disturbance scale for children (SDSC) questionnaire. Findings were compared with data from the Canadian Health Measures Survey (CMHS). Results Fifty-five children (47 males) aged 7 to 17 years (average 11.6 ± 2.5 years) with an average BMI z-score of -0.37 ± 1.22 completed the study. All children were medicated, the majority (82%), with various types of stimulant agents. Elevated office BP values were more prevalent than in the CMHS; >90th percentile in 5 (9.1%) and >95th percentile in 3 (5.5%). ABPM confirmed 'white coat hypertension' in 3 (5.5%), masked hypertension in 2 (3.6%) and nondipping in 28 (51%). The SDSC score suggested that 43 (78%) children had disturbed sleep. Logistic regression modelling indicated that nondipping correlated with disturbed sleep. Conclusion The 'white coat' phenomenon may be responsible for increased prevalence of elevated rest/office BP values in children with ADHD. Prevalent sleep 'non-dipping' in this population is associated with sleep disturbances but clinical significance of this finding requires further investigation.
Gossiping GANs: Position paper

A recently celebrated kind of deep neural networks is Generative Adversarial Networks. GANs are generators of samples from a distribution that has been learned; they are up to now centrally trained from local data on a single location. We question the performance of training GANs using a spread dataset over a set of distributed machines, using a gossip approach shown to work on standard neural networks [1]. This performance is compared to the federated learning distributed method, that has the drawback of sending model data to a server. We also propose a gossip variant, where GAN components are gossiped independently. Experiments are conducted with Tensorflow with up to 100 emulated machines, on the canonical MNIST dataset. The position of this paper is to provide a first evidence that gossip performances for GAN training are close to the ones of federated learning, while operating in a fully decentralized setup. Second, to highlight that for GANs, the distribution of data on machines is critical (i.e., i.i.d. or not). Third, to illustrate that the gossip variant, despite proposing data diversity to the learning phase, brings only marginal improvements over the classic gossip approach.
Role of Stem Cells in the Pathogenesis of Chronic Obstructive Pulmonary Disease and Pulmonary Emphysema

Abstract There are only few human translational studies performed in the area of stem cell research in patients with chronic obstructive pulmonary disease (COPD) and/or pulmonary emphysema. Before progress to clinical trials with stem cells we strongly believe that more human translational studies are essential, otherwise, the clinical rationale would be solely based on limited in vitro and animal studies. In the future, stem cell therapy could be a treatment for this incurable disease. As of now, stem cell therapy is still to be considered as an area of active research, lacking any strong rationale for performing clinical trials in COPD. Although stem cells would be likely to represent a heterogeneous population of cells, the different cell subsets and their importance in the pathogenesis of the different clinical phenotypes need to be fully characterised before progressing to clinical trials. Moreover, the potential side effects of stem cell therapy are underestimated. We should not ignore that some of the most deadly neoplasms are arising from stem cells.
A Novel Location-Based Content Distribution Protocol for Vehicular Named-Data Networks

The peculiar characteristics of vehicular networks (e.g., high vehicular mobility, poor wireless link quality and short-lived and intermittent connectivity among vehicles) challenge host-centric content search and distribution in vehicular networking applications. In this regard, recent studies have proposed information-centric protocols to improve content distribution in vehicular networks. However, they are still severely impaired by the highly dynamic nature of vehicular network topologies and the broadcast storm problem due to uncontrolled Interest packet flooding for content discovery. In this paper, we tackle the broadcast storm problem of Interest packet transmissions for content discovery in vehicular named-data networks. We propose the location-based content distribution protocol (LOCOS) for oriented Interest packet transmissions towards the proximity area of a recently discovered content source vehicle. The LOCOS protocol leverages the recently discovered location of a vehicle content source to controlled transmit Interest packets to the area where the content source is located. Simulation results show that the LOCOS protocol improves content delivery rate in 10% and 28% when compared with related work, while it reduces the content delivery delay in 80%.
FingerInput: Capturing Expressive Single-Hand Thumb-to-Finger Microgestures

Single-hand thumb-to-finger microgestures have shown great promise for expressive, fast and direct interactions. However, pioneering gesture recognition systems each focused on a particular subset of gestures. We are still in lack of systems that can detect the set of possible gestures to a fuller extent. In this paper, we present a consolidated design space for thumb-to-finger microgestures. Based on this design space, we present a thumb-to-finger gesture recognition system using depth sensing and convolutional neural networks. It is the first system that accurately detects the touch points between fingers as well as the finger flexion. As a result, it can detect a broader set of gestures than the existing alternatives, while also providing high-resolution information about the contact points. The system shows an average accuracy of 91% for the real-time detection of 8 demanding thumb-to-finger gesture classes. We demonstrate the potential of this technology via a set of example applications.
Risk factors for cytological progression in HPV 16 infected women with ASC-US or LSIL: The Korean HPV cohort

Objective This study was to identify the risk factors for cytological progression in women with atypical squamous cells of undetermined significance (ASC-US) or low-grade squamous intraepithelial lesions (LSIL). Methods We analyzed data from women infected with the human papillomavirus (HPV) who participated in the Korean HPV cohort study. The cohort recruited women aged 20–60 years with abnormal cervical cytology (ASC-US or LSIL) from April 2010. All women were followed-up at every 6-month intervals with cervical cytology and HPV DNA testing. Results Of the 1,158 women included, 654 (56.5%) and 504 (43.5%) women showed ASC-US and LSIL, respectively. At the time of enrollment, 143 women tested positive for HPV 16 (85 single and 58 multiple infections). Cervical cytology performed in the HPV 16-positive women showed progression in 27%, no change in 23%, and regression in 50% of the women at the six-month follow-up. The progression rate associated with HPV 16 infection was higher than that with infection caused by other HPV types (relative risk [RR], 1.75; 95% confidence interval [CI], 1.08–2.84; P=0.028). The cytological progression rate in women with persistent HPV 16 infection was higher than that in women with incidental or cleared infections (P<0.001). Logistic regression analysis showed a significant relationship between cigarette smoking and cytological progression (RR, 4.15; 95% CI, 1.01–17.00). Conclusion The cytological progression rate in HPV 16-positive women with ASC-US or LSIL is higher than that in women infected with other HPV types. Additionally, cigarette smoking may play a role in cytological progression.
Robust Active Learning for Electrocardiographic Signal Classification

The classification of electrocardiographic (ECG) signals is a challenging problem for healthcare industry. Traditional supervised learning methods require a large number of labeled data which is usually expensive and difficult to obtain for ECG signals. Active learning is well-suited for ECG signal classification as it aims at selecting the best set of labeled data in order to maximize the classification performance. Motivated by the fact that ECG data are usually heavily unbalanced among different classes and the class labels are noisy as they are manually labeled, this paper proposes a novel solution based on robust active learning for addressing these challenges. The key idea is to first apply the clustering of the data in a low dimensional embedded space and then select the most information instances within local clusters. By selecting the most informative instances relying on local average minimal distances, the algorithm tends to select the data for labelling in a more diversified way. Finally, the robustness of the model is further enhanced by adding a novel noisy label reduction scheme after the selection of the labeled data. Experiments on the ECG signal classification from the MIT-BIH arrhythmia database demonstrate the effectiveness of the proposed algorithm.