Miracle-dz/UniFAR-FTUs huggingface dataset:
Fetal brain response to maternal inflammation requires microglia

In utero infection and maternal inflammation can adversely impact fetal brain development. Maternal systemic illness, even in the absence of direct fetal central nervous system infection, is associated with an increased risk of autism and schizophrenia in affected offspring. The cell types mediating the response of the fetal brain to maternal inflammation are largely unknown, hindering the development of therapies to prevent and treat adverse neuropsychiatric outcomes. Here, we show that microglia, the resident phagocytes of the brain, are enriched for expression of receptors for relevant pathogens and cytokines, throughout embryonic development. Using a rodent maternal immune activation (MIA) model in which polyinosinic:polycytidylic acid is injected into pregnant dams, we demonstrate long-lasting transcriptional changes in fetal microglia that persist into postnatal life. We find that MIA induces widespread gene expression changes in neuronal and non-neuronal cells; importantly, these responses are abolished by selective genetic deletion of microglia, indicating that microglia are required for the transcriptional response of other cortical cell types to MIA. These findings demonstrate that microglia play a critical, durable role in fetal response to maternal inflammation, pointing at microglia as a potential therapeutic cell target.
Finimizers: Variable-length bounded-frequency minimizers for k-mer sets

The minimizer of a k-mer is the smallest m-mer inside the k-mer according to some order relation < of the m-mers. Minimizers are often used as keys in hash tables in indexing tasks in metagenomics and pangenomics. The main weakness of minimizer-based indexing is the possibility of very frequently occurring minimzers, which can slow query times down significantly. Popular minimizer alignment tools employ various and often wild heuristics as workarounds, typically by ignoring frequent minimizers or blacklisting commonly occurring patterns, to the detriment of other metrics (e.g., alignment recall, space usage, or code complexity). In this paper, we introduce frequency-bounded minimizers, which we call finimizers, for indexing sets of k-mers. The idea is to use an order relation < for minimizer comparison that depends on the frequency of the minimizers within the indexed k-mers. With finimizers, the length m of the m-mers is not fixed, but is allowed to vary depending on the context, so that the length can increase to bring the frequency down below a user-specified threshold t. Setting a maximum frequency solves the issue of very frequent minimizers and gives us a worstcase guarantee for the query time. We show how to implement a particular finimizer scheme efficiently using the Spectral Burrows-Wheeler Transform (SBWT) (Alanko et al., Proc. SIAM ACDA, 2023) augmented with longest common suffix information. In experiments, we explore in detail the special case in which we set t = 1. This choice simplifies the index structure and makes the scheme completely parameter-free apart from the choice of k. A prototype implementation of this scheme exhibits k-mer localization times close to, and often faster than, stateof-the-art minimizer-based schemes. The code is available at https://github.com/ElenaBiagi/Finito.
Computing: A Brief Review of Impacts and Issues

: The rapid evolution of state of the art technologies has blended inadvertently into the physical world that now offer more than ubiquitous availability of computing infrastructure and resources. Over the past decade we are witnessing new paradigms of application driven computing capabilities by constant access to information and computational capabilities. Application driven Ubicomp has fundamentally changed the relationship between humans and computers, making them indispensable yet providing continuous interaction. The rapid evolution of state of the art technologies have blended inadvertently into the physical world that now offer more than ubiquitous availability of computing infrastructure and resources. Ubicomp has resulted in interaction of natural interfaces, context-aware applications, and automated capture and access. The aim of this paper is to highlight the impact of currently available ubiquitous computing technology on business processes in variety of domains. It briefly discusses technologies and its drivers, and gives some examples of their application including automatic identification, localization, and sensor technology technologies that appear to have impacted business processes in a variety of ways. The paper closes with some future perspectives on ubiquitous computing applications and visits some areas of issues and challenges posed by it.
Pathological mechanisms and candidate therapeutic approaches in the hearing loss of mice carrying human MIR96 mutations

Progressive hearing loss is a common problem in the human population with no effective therapeutics currently available. However, it has a strong genetic contribution, and investigating the genes and regulatory interactions underlying hearing loss offers the possibility of identifying therapeutic candidates. Mutations in regulatory genes are particularly useful for this, and an example is the microRNA miR-96, a transcriptional regulator which controls hair cell maturation. Mice and humans carrying mutations in Mir96 all develop hearing loss, but different mutations result in different physiological, structural and transcriptional phenotypes. Here we present our characterisation of two lines of mice carrying different human mutations knocked-in to Mir96. While mice homozygous for either mutation are profoundly deaf from two weeks old, the heterozygous phenotypes differ markedly, with only one mutation resulting in hearing impairment in heterozygosis. Investigations of the structural phenotype showed that one mutation appears to lead to synaptic defects, while the other has a much more severe effect on the hair cell stereociliary bundles. Transcriptome analyses revealed a wide range of misregulated genes in both mutants which were notably dissimilar. We used the transcriptome analyses to investigate candidate therapeutics, and tested one, finding that it delayed the progression of hearing loss in heterozygous mice. Our work adds further support for the importance of the gain of novel targets in microRNA mutants, and offers a proof of concept for the identification of pharmacological interventions to maintain hearing.
A Systematic Review of Technology-Driven Methodologies for Estimation of Energy Intake

Accurate measurement of energy intake (EI) is important for estimation of energy balance, and, correspondingly, body weight dynamics. Traditional measurements of EI rely on self-report, which may be inaccurate and underestimate EI. The imperfections in traditional methodologies such as 24-hour dietary recall, dietary record, and food frequency questionnaire stipulate development of technology-driven methods that rely on wearable sensors and imaging devices to achieve an objective and accurate assessment of EI. The aim of this research was to systematically review and examine peer-reviewed papers that cover the estimation of EI in humans, with the focus on emerging technology-driven methodologies. Five major electronic databases were searched for articles published from January 2005 to August 2017: Pubmed, Science Direct, IEEE Xplore, ACM library, and Google Scholar. Twenty-six eligible studies were retrieved that met the inclusion criteria. The review identified that while the current methods of estimating EI show promise, accurate estimation of EI in free-living individuals presents many challenges and opportunities. The most accurate result identified for EI (kcal) estimation had an average accuracy of 94%. However, collectively, the results were obtained from a limited number of food items (i.e., 19), small sample sizes (i.e., 45 meal images), and primarily controlled conditions. Therefore, new methods that accurately estimate EI over long time periods in free-living conditions are needed.
Eye Movement Pattern Modeling and Visual Comfort Viewing S3D Images

Stereoscopic-3D (S3D) displays are widely used but present problems related to experiences of visual discomfort for human vision. One aspect of this issue is the movement of the gaze point within different depth fields. Here we aim to analyze the relationship between eye movement patterns and visual comfort experienced when viewing S3D images. Rather than simply labeling eye movement data according to categories such as gaze, saccade and so on, we depoly nonparametric Bayesian method to analyze and cluster several eye movement patterns, and to relate them to visual comfort. The results are relevant to the prediction of visual comfort assessment in S3D images by automatic algorithms.
Fast Korean Text Detection and Recognition in Traffic Guide Signs

In this paper, we propose a fast method based on deep neural networks to detect and recognize Korean characters in traffic guide signs. To detect character candidates quickly, we first employ a region proposal network (RPN) which is in this paper ResNet-18, being relatively shallow. We also apply the Inception architecture to residual blocks for reducing parameters of the network. After character candidates are detected, we classify them into 709 Korean characters by using a classification network (CLSN). Similar to the RPN, our CLSN consists of residual blocks with the Inception architecture. In experiments, we achieved 97.69 % of accuracy at 5.9fps on both detection and recognition of Korean characters in traffic guide signs.
PCA-Based Speech Enhancement For Distorted Speech Recognition

This paper deals with application of speech recognition using distorted speech signal. When speech signal is given as an input to any system some background noise always gets added to it which is undesirable. In order to overcome this difficulty we transform the signal using Kernel Principal Component Analysis and then the task of recognition is done using the Hidden Markov Models. The developed system is capable of recognizing the speech from distorted speech signal by extracting the MFCCs. And then transformed using PCA to obtain eigenvalues. The eigenvalues with highest values contain important information which are retained and others are discarded as noise. Hidden Markov Models is most capable method used for speech recognition
28nm Fault-Tolerant Hardening-by-Design Frequency Divider for Reducing Soft Errors in Clock and Data Recovery

A fault-tolerant hardening-by-design frequency divider has been proposed for clock and data recovery in a 28-nm CMOS process. By means of the mandatory updating mechanism, the proposed divider can update the state of the D flip-flops from an error state to a correct state so as to avoid single-event transient (SET) accumulation in different finite-state machines (FSMs). Our proposed divider also does not destroy the original structure and can, thus, greatly reduce performance degradation. Laser tests show that the threshold of the proposed divider can be significantly improved. The heavy-ion experiment shows good SET/single-event upset (SEU) tolerance during the ion strike under 83.7 MeV<inline-formula> <tex-math notation="LaTeX">$\cdot $ </tex-math></inline-formula>cm<sup>2</sup>/mg.
Predictors of Exercise Training and Physical Activity Adherence in People Recently Hospitalized With Heart Failure

Purpose: For individuals with heart failure (HF), frequent attendance at exercise training programs and meeting physical activity (PA) guidelines are significantly associated with improvements in 6-min walk distance. Despite the evidence, adherence to exercise interventions remains poor. The aim of this study was to identify predictors of these 2 variables in patients recently hospitalized with HF. Methods: In this substudy of the Exercise Joins Education: Combined Therapy to Improve Outcomes in Newly-discharged Heart Failure (EJECTION-HF) trial, all participants were enrolled in a HF disease management program, including weekly review of a home exercise program for 12 wk. Intervention group participants additionally undertook twice weekly supervised exercise training. Primary outcomes were frequent exercise training program attendance (≥12 sessions) and attainment of PA guidelines (150 min/wk of moderate intensity exercise) at 12 wk. Participant and clinical characteristics were analyzed using a logistic regression model to identify significant predictors of each outcome. Results: A total of 278 participants provided PA data and 140 contributed attendance data. New diagnosis of HF was a significant predictor of frequent program attendance (OR = 2.3; 95% CI, 1.1-4.7; P = .03). Predictors of meeting PA guidelines at follow-up included new HF diagnosis (OR = 2.4; 95% CI, 1.2-4.8, P = .013), and being physically active at baseline (OR = 2.7; 95% CI, 1.3-5.6; P = .007). Gender, symptom severity, multimorbidity, and disability were not significantly associated with either outcome in multivariate analysis. Conclusion: To improve adherence, specific strategies may be required for patients with decompensated HF and those physically inactive at time of referral.
All-Optical 216 Gbps Super-channel Data Switching Using Co-Polarized Pump in SOA

Efficient bit transmission, flexible spectrum utilization, polarization and space division multiplexing (PDM and SDM), and advanced laser designs are among the recent technologies adopted for boosting the capacity and spectral efficiency (SE) of optical communication networks. In addition, all-optical wavelength conversion is required to reduce network latency and energy consumption. In this paper, we exploit the modulation and polarization transparency features of the semiconductor optical amplifiers (SOAs) in order to build a photonics-based wavelength converter for single and super-channel quadrature phase shift keying (QPSK)-PDM signals. An experimental demonstration is conducted and high transmission speeds are achieved including 18-, 20-, and 25-Gbaud. The experimental results show a conversion of a super-channel signal consisting of three dual-polarization QPSK signals with 216-Gbps total aggregated data rate using a co-propagated pump four-wave mixing (FWM) configuration.
20-kW Zero-Voltage-Switching SiC-mosfet Grid Inverter With 300 kHz Switching Frequency

Although SiC-mosfet has significant advantages on switching performance over traditional Si-IGBT, the switching loss of SiC-mosfet devices at hard switching rises quickly with the increment in the switching frequency. This has narrowed down further possibilities of improving efficiency and power density of the grid inverter. Zero-voltage-switching (ZVS) space-vector-modulation (SVM) technique is introduced to further push the power density of SiC-mosfet inverter. This paper focuses on the impact of applying the ZVS-SVM to three-phase two-level SiC-mosfet inverter. With the same efficiency requirement the ZVS-SVM SiC inverter can operate at a much higher switching frequency, which gives the opportunity to further reduce the size of passive components. The loss distributions, conversion efficiencies, and volumes of passive components of both a 20-kW SiC-mosfet hard-switching inverter and a 20-kW SiC-mosfet ZVS-SVM inverter have been compared under switching-frequency range from 50 to 300 kHz. Meanwhile, a new metric called “efficiency stiffness” is proposed to compare different inverters with respect to the efficiency performance against switching-frequency characteristics. In addition, high voltage overshoot of SiC-mosfet and high thermal stress of resonant inductor are the two critical issues in the SiC-mosfet ZVS-SVM inverter with high switching frequency. A power module including seven SiC-mosfet bare dies with low stray inductance is designed for ZVS-SVM inverter instead of the existing seven discrete TO-247 package SiC-mosfets to reduce the voltage overshoots on the switches. Besides, to reduce the power loss of the resonant inductor caused by large amplitude of current at hundreds of kHz excitation frequency, design of the inductor with distributed air gap and optimal winding thickness are studied. A 20-kW SiC-mosfet ZVS-SVM grid inverter prototype is built to verify the proposed design.
Utilisation of coaching practices in early interventions in children at risk of developmental disability/delay: a systematic review

Abstract Background: To conduct a systematic review of early intervention programs (0–5 years) utilising coaching practice characteristics, to identify (i) implementation fidelity; (ii) parent training processes, and (iii) outcome measures of capacity building in parents. The coaching practice characteristics of (1) joint planning, (2) observation, (3) action/practice, (4) reflection and (5) feedback identified by Rush and Shelden were utilised. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was followed. A comprehensive search of 6 electronic databases was undertaken in March 2016 and updated in February 2018. Results: Of 2397 articles, 18 papers met full inclusion criteria. Of these, 5 were randomised controlled trials. Only one specifically evaluated the impact of parent coaching versus therapist only delivered interventions. Risk of bias and study quality using Downs and Black checklist for clinical trial quality yielded the following descriptive ratings: Seven studies: “Poor” (scores 1–13); Six studies: “Fair” (scores 15–17); and five “Good” (scores 20–24). Conclusion: Coaching in early intervention is well accepted. Nevertheless, this review identified a continued lack of operationalised definitions; inconsistency in the reporting of therapist training and adherence to active ingredients/coaching principles; and an absence of outcome measures focused on parent capacity. Implications for Rehabilitation Contemporary early intervention services recognise the importance of engaging parents as active participators in their child’s development. This is evident by the increase in interventions that utilise parent coaching practices. The findings of this systematic review indicate the need for professionals to: •Describe and document fidelity of coaching practices in the delivery of intervention. •Objectively measure changes in parent capacity and self-efficacy as a result of the coaching based intervention. The reporting of parent capacity measures will allow us to truly examine the effectiveness of coaching practices in empowering families to support their child to realise their full potential.
Robust Heart Rate Monitoring for Quasi-Periodic Motions by Wrist-Type PPG Signals

Heart rate (HR) monitoring using photoplethysmography (PPG) is a promising feature in modern wearable devices. PPG is easily contaminated by motion artifacts (MA), hindering estimation of HR. For quasi-periodic motions, previous works generally focused on a few specific motions, such as walking and fast running. However, they may not work well for many different quasi-periodic motions where MA are very complex. In this paper, a robust HR monitoring scheme for different quasi-periodic motions using wrist-type PPG is proposed, which consists of dictionary learning for signal characteristics learning, human motion recognition for the current motion recognition and dictionary selection, sparse representation-based MA elimination for denoising, and spectral peak tracking for HR-related spectral peak tracking. The proposed scheme is robust to MA caused by different motions and has high accuracy. Experiments on six common quasi-periodic motions showed that the average absolute error of heart rate estimation was 2.40 beat per minute, and also showed that the proposed method is more robust than some state-of-the-art approaches for different motions.
When Collaboration Bridges Institutions: The Impact of University-Industry Collaboration on Academic Productivity

Prior research suggests that academic scientists who collaborate with firms may experience lower publication rates in their collaborative lines of work due to industry’s insistence on intellectual property protection through patenting or secrecy. In contrast, we posit that university–industry collaboration can sometimes foster specialization and boost academic contribution to open science. Specifically, research lines with both scientific and commercial potential (i.e., in Pasteur’s quadrant) provide an opportunity for a productive division of tasks between academic scientists and their industry counterparts, whereby the former focus on exploiting the scientific opportunities and the latter focus on the commercial ones. The main empirical challenge of examining this proposition is that research projects that involve industry collaborators may be qualitatively different from those that do not. To address this issue, we exploit the occurrence of simultaneous discoveries where multiple scientists make roughly the same discovery around the same time. Following a simultaneous discovery, we compare the follow-on research output of academic scientists who collaborated with industry on the discovery with that of academic scientists who did not. We find that academic scientists with industry collaborators produced more follow-on publications and fewer follow-on patents than did academic scientists without industry collaborators. This effect is particularly salient when the research line has important commercial implications and when the industry partner is an established firm.
Reducing tuberculosis transmission: a consensus document from the World Health Organization Regional Office for Europe

Evidence-based guidance is needed on 1) how tuberculosis (TB) infectiousness evolves in response to effective treatment and 2) how the TB infection risk can be minimised to help countries to implement community-based, outpatient-based care. This document aims to 1) review the available evidence on how quickly TB infectiousness responds to effective treatment (and which factors can lower or boost infectiousness), 2) review policy options on the infectiousness of TB patients relevant to the World Health Organization European Region, 3) define limitations of the available evidence and 4) provide recommendations for further research. The consensus document aims to target all professionals dealing with TB (e.g. TB specialists, pulmonologists, infectious disease specialists, primary healthcare professionals, and other clinical and public health professionals), as well as health staff working in settings where TB infection is prevalent. Sound implementation of administrative and environmental controls, personal protection and FAST approach (rapid diagnosis and effective treatment tailored to drug resistance profile with focus on undetected cases) are necessary to reduce TB transmission http://ow.ly/hEhw30of6Gk
Heuristic search procedures for cryptanalysis and development of enhanced cryptographic techniques

Cryptology is a thriving research area of great practical importance. It is a fundamental building block of communications security. Cryptographic techniques currently being utilized in the field of communication. This paper presents an approach for the heuristic search procedures for cryptanalysis and development of enhanced cryptographic techniques. To implement the proposed Tabu search, Genetic, and Simulated Annealing algorithms firstly by utilising cipher text as well as some plain text and secondly by using only the cipher text to retrieve the original data. The cryptanalysis of simplified data encryption standard can be formulated as NP-Hard combinatorial problem. The goal of this paper is to comparison between Tabu Search, Genetic Algorithm and simulated annealing were made in order to investigate the performance for the cryptanalysis on SDES. The methods were tested and extensive computational results show that Tabu Search algorithm performs better than Genetic algorithm and simulated annealing for such type of NP-Hard combinatorial problem.