Miracle-dz/UniFAR-FTUs huggingface dataset:
Occipital EEG Activity for the Detection of Nocturnal Hypoglycemia

Nocturnal hypoglycemia is dangerous that threatens patients because of its unclear symptoms during sleep. This paper is a study of hypoglycemia from 8 patients with type 1 diabetes (T1D) at night. O1 and O2 EEG data of the occipital lobe associated with glycemic episodes were analyzed. Frequency features were computed from Power Spectral Density using Welch’s method. Centroid alpha frequency reduced significantly ($\mathrm{P}\lt 0.0001$) while centroid theta increased considerably ($\mathrm{P}\lt 0.01$). Spectral entropy of the unified theta-alpha band rose significantly ($\mathrm{P}\lt 0.005$). These occipital features acted as the input of a Bayesian regularized neural network for detecting hypoglycemic episodes. The classification results were 73% and 60% of sensitivity and specificity, respectively.
Estimation of Neural Inputs and Detection of Saccades and Smooth Pursuit Eye Movements by Sparse Bayesian Learning

Eye movements reveal a great wealth of information about the visual system and the brain. Therefore, eye movements can serve as diagnostic markers for various neurological disorders. For an objective analysis, it is crucial to have an automatic and robust procedure to extract relevant eye movement parameters. An essential step towards this goal is to detect and separate different types of eye movements such as fixations, saccades and smooth pursuit. We have developed a model-based approach to perform signal detection and separation on eye movement recordings, using source separation techniques from sparse Bayesian learning. The key idea is to model the oculomotor system with a state space model and to perform signal separation in the neural domain by estimating sparse inputs which trigger saccades. The algorithm was evaluated on synthetic data, neural recordings from rhesus monkeys and on manually annotated human eye movement recordings with different smooth pursuit paradigms. The developed approach shows a high noise-robustness, provides saccade and smooth pursuit parameters, as well as estimates of the position, velocity and acceleration profiles. In addition, by estimating the input to the oculomotor system, we obtain an estimate of the neural inputs to the oculomotor muscles.
Paracosms: The Imaginary Worlds of Middle Childhood.

The invention of imaginary worlds ("paracosms") is a creative activity of middle childhood that has previously been investigated primarily with retrospective adult reports and biographical accounts. In descriptions collected from 8- to 12-year-old children, the prevalence was 16.9% in Study 1 (n = 77) and 17.4% in Study 2 (n = 92). Children with and without paracosms did not differ in verbal comprehension, divergent thinking (Studies 1 and 2) or working memory (Study 2). However, children with paracosms had more difficulty with inhibitory control (Study 2) and had higher creativity scores on a story-telling task (Studies 1 and 2). Paracosms provided a vehicle for stories associated with imaginary companions and/or for developing complex narratives alone or with friends.
F3Hand: A Five-Fingered Prosthetic Hand Driven with Curved Pneumatic Artificial Muscles

Recently, many five-fingered prosthetic hands have been commercialized. However, most five-fingered prosthetic hands have heavyweight problems. In addition, their fingers with high rigidity are difficult to fit the object to be grasped. This paper reports a five-fingered prosthetic hand driven with curved pneumatic artificial muscles. By using the curved pneumatic artificial muscles as a skeleton and an actuator of the finger, flexible grasps and natural motions are achieved. Its weight of 255 g is less than one-third of the conventional fivefingered prosthetic hand. An evaluation using SHAP demonstrated that an amputee was able to operate various abstract objects.
Cold-Water Immersion Has No Effect on Muscle Stiffness After Exercise-Induced Muscle Damage.

OBJECTIVE To analyze the effect of cryotherapy on muscle stiffness after exercise-induced muscle damage. DESIGN A leg-to-leg comparison model. SETTING University research laboratory. PARTICIPANTS Thirty (30) untrained men (21.1 ± 1.6 years, 177.6 ± 6.4 cm, 75.9 ± 10.0 kg, and 15.9 ± 2.9% fat mass) with no history of lower-limb injury and no experience in resistance training. INTERVENTION All participants underwent a plyometric exercise program to induce muscle damage; however, randomly, one leg was assigned to a treatment condition and subjected twice to cold-water immersion of the lower limb at 10°C (±1°C) for 10 minutes, while the other leg was assigned to control. MAIN OUTCOMES MEASURES Longitudinal stiffness and passive transverse stiffness were evaluated on the soleus and gastrocnemius muscles at 4 moments: pre-exercise, immediately after exercise, 24 hours, and 72 hours after the damage protocol. Furthermore, pressure pain threshold (PPT) and maximal voluntary isometric contraction (MVIC) were also assessed in the same periods. RESULTS No significant differences between control and cryotherapy were observed in regard to MVIC (P = 0.529), passive longitudinal stiffness (P = 0.315), and passive transverse stiffness (P = 0.218). Only a significant decrease was observed in PPT on the soleus muscle in the cryotherapy compared with the control leg immediately after exercise (P = 0.040). CONCLUSIONS The results show that cryotherapy had no influence on muscle stiffness. However, cryotherapy had a positive effect on PPT immediately after exercise.
MicroRNA‐140‐5p targeting tumor necrosis factor‐α prevents pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is characterized by the apoptosis resistance and hyperproliferation of pulmonary artery smooth muscle cells (PASMCs). Its pathogenesis has not been revealed. Here, we carried out experiments to investigate the functions of miR‐140‐5p and tumor necrosis factor‐α (TNF‐α).
In vitro Measurement of Release Kinetics of Temperature Sensitive Liposomes with a Fluorescence Imaging System

Temperature sensitive liposomes (TSL) are a promising type of nanoparticles for localized drug delivery. TSL typically release the contained drug at mild hyperthermic temperatures (40-42 °C). Combined with localized hyperthermia, this allows for local drug delivery. In vitro characterization of TSL involves measurements of drug release at varying temperatures, but current methods are inadequate due to low temporal resolution of ~8 – 10 seconds. We present a novel method for measuring the drug release with sub-second temporal resolution. In the proposed system, the TSL entrapping the fluorescent drug (Doxorubicin) are pumped through a capillary tube. The tube is rapidly heated to a desired temperature via Peltier element. Since fluorescence increases as drug is released from TSL, drug release kinetics can be measured via fluorescent imaging. By fitting exponential models, we calculated the time constants of drug release at temperatures of 39.5, 40.5 and 41.5. C were about 6.09, 2.06 and 1.03 seconds, respectively. Our initial tests show that the developed system can measure TSL release at subsecond resolution, and thus allow adequate in vitro evaluation of TSL formulations.
Update on Vaccine-Derived Polioviruses — Worldwide, January 2017–June 2018

Since the Global Polio Eradication Initiative was launched in 1988 (1), the number of polio cases worldwide has declined by >99.99%. Among the three wild poliovirus (WPV) serotypes, only type 1 (WPV1) has been detected since 2012. This decline is attributable primarily to use of the live, attenuated oral poliovirus vaccine (OPV) in national routine immunization schedules and mass vaccination campaigns. The success and safety record of OPV use is offset by the rare emergence of genetically divergent vaccine-derived polioviruses (VDPVs), whose genetic drift from the parental OPV strains indicates prolonged replication or circulation (2). Circulating VDPVs (cVDPVs) can emerge in areas with low immunization coverage and can cause outbreaks of paralytic polio. In addition, immunodeficiency-associated VDPVs (iVDPVs) can emerge in persons with primary immunodeficiencies and can replicate and be excreted for years. This report presents data on VDPVs detected during January 2017-June 2018 and updates previous VDPV summaries (3). During this reporting period, new cVDPV outbreaks were detected in five countries. Fourteen newly identified persons in nine countries were found to excrete iVDPVs. Ambiguous VDPVs (aVDPVs), isolates that cannot be classified definitively, were found among immunocompetent persons and environmental samples in seven countries.
On the Convergence Rate of Training Recurrent Neural Networks

How can local-search methods such as stochastic gradient descent (SGD) avoid bad local minima in training multi-layer neural networks? Why can they fit random labels even given non-convex and non-smooth architectures? Most existing theory only covers networks with one hidden layer, so can we go deeper? In this paper, we focus on recurrent neural networks (RNNs) which are multi-layer networks widely used in natural language processing. They are harder to analyze than feedforward neural networks, because the $\textit{same}$ recurrent unit is repeatedly applied across the entire time horizon of length $L$, which is analogous to feedforward networks of depth $L$. We show when the number of neurons is sufficiently large, meaning polynomial in the training data size and in $L$, then SGD is capable of minimizing the regression loss in the linear convergence rate. This gives theoretical evidence of how RNNs can memorize data. More importantly, in this paper we build general toolkits to analyze multi-layer networks with ReLU activations. For instance, we prove why ReLU activations can prevent exponential gradient explosion or vanishing, and build a perturbation theory to analyze first-order approximation of multi-layer networks.
Transcriptomic and proteomic insight into the mechanism of cyclooctasulfur‐ versus thiosulfate‐oxidation by the chemolithoautotroph Sulfurimonas denitrificans

Chemoautotrophic bacteria belonging to the genus Sulfurimonas (class Campylobacteria) were previously identified as key players in the turnover of zero-valence sulfur, a central intermediate in the marine sulfur cycle. S. denitrificans was further shown to be able to oxidize cyclooctasulfur (S8 ). However, at present the mechanism of activation and metabolism of cyclooctasulfur is not known. Here, we assessed the transcriptome and proteome of S. denitrificans grown with either thiosulfate or S8 as the electron donor. While the overall expression profiles under the two growth conditions were rather similar, distinct differences were observed that could be attributed to the utilization of S8 . This included a higher abundance of expressed genes related to surface attachment in the presence of S8 , and the differential regulation of the sulfur-oxidation multienzyme complex (SOX), which in S. denitrificans is encoded in two gene clusters: soxABXY 1 Z 1 and soxCDY 2 Z 2 . While the proteins of both clusters were present with thiosulfate, only proteins of the soxCDY 2 Z 2 were detected at significant levels with S8 . Based on these findings a model for the oxidation of S8 is proposed. Our results have implications for interpreting metatranscriptomic and -proteomic data and for the observed high level of diversification of soxY 2 Z 2 among sulfur-oxidizing Campylobacteria.
The Underestimated Role of Refractive Error (Hyperopia, Myopia, and Astigmatism) and Strabismus in Children With ADHD

Objective: To examine the association of refractive error (myopia, hyperopia, astigmatism) and strabismus with ADHD. Method: Based on data from the large, representative, epidemiological sample of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) study (N = 13,488), the associations of myopia, hyperopia, astigmatism, and strabismus with ADHD were examined, with and without consideration of other common ADHD risk factors. Results: In single logistic regression models, all examined forms of refractive error and strabismus showed an association with ADHD. After controlling for confounding variables, results remained stable and showed an increased risk for ADHD in children with hyperopia, astigmatism, and strabismus compared with the control group. Only the association between myopia and ADHD in children was not significant. Conclusion: Hyperopia, astigmatism, and strabismus seem to be independently associated with ADHD. Health care professionals in different medical fields should consider this association to adequately diagnose and treat affected children.
A Context Encoder For Audio Inpainting

In this article, we study the ability of deep neural networks (DNNs) to restore missing audio content based on its context, i.e., inpaint audio gaps. We focus on a condition which has not received much attention yet: gaps in the range of tens of milliseconds. We propose a DNN structure that is provided with the signal surrounding the gap in the form of time-frequency (TF) coefficients. Two DNNs with either complex-valued TF coefficient output or magnitude TF coefficient output were studied by separately training them on inpainting two types of audio signals (music and musical instruments) having 64-ms long gaps. The magnitude DNN outperformed the complex-valued DNN in terms of signal-to-noise ratios and objective difference grades. Although, for instruments, a reference inpainting obtained through linear predictive coding performed better in both metrics, it performed worse than the magnitude DNN for music. This demonstrates the potential of the magnitude DNN, in particular for inpainting signals that are more complex than single instrument sounds.
Efficacy, effectiveness, and safety of herpes zoster vaccines in adults aged 50 and older: systematic review and network meta-analysis

Abstract Objective To compare the efficacy, effectiveness, and safety of the herpes zoster live attenuated vaccine with the herpes zoster adjuvant recombinant subunit vaccine or placebo for adults aged 50 and older. Design Systematic review with bayesian meta-analysis and network meta-analysis. Data sources Medline, Embase, and Cochrane Library (inception to January 2017), grey literature, and reference lists of included studies. Eligibility criteria for study selection Experimental, quasi-experimental, and observational studies that compared the live attenuated vaccine with the adjuvant recombinant subunit vaccine, placebo, or no vaccine in adults aged 50 and older. Relevant outcomes were incidence of herpes zoster (primary outcome), herpes zoster ophthalmicus, post-herpetic neuralgia, quality of life, adverse events, and death. Results 27 studies (22 randomised controlled trials) including 2 044 504 patients, along with 18 companion reports, were included after screening 2037 titles and abstracts, followed by 175 full text articles. Network meta-analysis of five randomised controlled trials found no statistically significant differences between the live attenuated vaccine and placebo for incidence of laboratory confirmed herpes zoster. The adjuvant recombinant subunit vaccine, however, was statistically superior to both the live attenuated vaccine (vaccine efficacy 85%, 95% credible interval 31% to 98%) and placebo (94%, 79% to 98%). Network meta-analysis of 11 randomised controlled trials showed the adjuvant recombinant subunit vaccine to be associated with statistically more adverse events at injection sites than the live attenuated vaccine (relative risk 1.79, 95% credible interval 1.05 to 2.34; risk difference 30%, 95% credible interval 2% to 51%) and placebo (5.63, 3.57 to 7.29 and 53%, 30% to 73%, respectively). Network meta-analysis of nine randomised controlled trials showed the adjuvant recombinant subunit vaccine to be associated with statistically more systemic adverse events than placebo (2.28, 1.45 to 3.65 and 20%, 6% to 40%, respectively). Conclusions Using the adjuvant recombinant subunit vaccine might prevent more cases of herpes zoster than using the live attenuated vaccine, but the adjuvant recombinant subunit vaccine also carries a greater risk of adverse events at injection sites. Protocol registration Prospero CRD42017056389.
Epidemiology of sarcoidosis: current findings and future directions

Sarcoidosis is a granulomatous inflammatory disease with unknown etiology. Epidemiological studies have contributed greatly to our knowledge about sarcoidosis, providing critical information on the determinants and distribution of the disease. In this review, we summarize recently published findings from epidemiological studies on sarcoidosis. We review the epidemiological tools used, the incidence and prevalence of disease, mortality and cancer risk after sarcoidosis and nongenetic risk factors for sarcoidosis. Genetics studies have not been included as they deserve a separate review. Leveraging existing epidemiological data to conduct etiological studies aimed towards understanding and preventing disease is critical for future sarcoidosis research.
Social Connectedness: Measurement, Determinants, and Effects.

Social networks can shape many aspects of social and economic activity: migration and trade, job-seeking, innovation, consumer preferences and sentiment, public health, social mobility, and more. In turn, social networks themselves are associated with geographic proximity, historical ties, political boundaries, and other factors. Traditionally, the unavailability of large-scale and representative data on social connectedness between individuals or geographic regions has posed a challenge for empirical research on social networks. More recently, a body of such research has begun to emerge using data on social connectedness from online social networking services such as Facebook, LinkedIn, and Twitter. To date, most of these research projects have been built on anonymized administrative microdata from Facebook, typically by working with coauthor teams that include Facebook employees. However, there is an inherent limit to the number of researchers that will be able to work with social network data through such collaborations. In this paper, we therefore introduce a new measure of social connectedness at the US county level. Our Social Connectedness Index is based on friendship links on Facebook, the global online social networking service. Specifically, the Social Connectedness Index corresponds to the relative frequency of Facebook friendship links between every county-pair in the United States, and between every US county and every foreign country. Given Facebook’s scale as well as the relative representativeness of Facebook’s user body, these data provide the first comprehensive measure of friendship networks at a national level.
UZH at CoNLL–SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection

This paper presents the submissions by the University of Zurich to the CoNLL–SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection. Our system is based on the prior work on neural transitionbased transduction (Makarov and Clematide, 2018b; Aharoni and Goldberg, 2017). Unlike the prior work, we train the model in a fully end-to-end fashion—without the need for an external character aligner—within the framework of imitation learning. In the type-level morphological inflection generation challenge (Task I), our five-strong ensemble outperforms all competitors in all three data-size settings. In the token-level inflection generation challenge (Task II), our single model achieves the best results on three out of four sub-tasks that we have participated in.
Automated Myocardial Wall Motion Classification using Handcrafted Features vs a Deep CNN-based mapping

Compared to other modalities such as computed tomography or magnetic resonance imaging, the appearance of ultrasound images is highly dependent on the expertise of the sonographer or clinician making the image acquisition, as well as the machine used, making it a challenge to analyze due to the frequent presence of artefacts, missing boundaries, attenuation, shadows, and speckle. In addition, manual contouring of the epicardial and endocardial walls exhibits large inconsistencies and variations as it is strongly dependent on the sonographer’s training and expertise. Hence, in this paper we propose a fully automated image analysis framework to ultimately perform wall motion abnormality classification in 2D+T images. We explore both traditional Random Forests classification with handcrafted features and spatio-temporal hierarchical aggregation of information with a deep learning CNN-based approach. Regarding the later classifier, we also investigate the effect of local phase information retrieval through the use of Feature Asymmetry (FA), and demonstrate that pre-processing videos with FA enables the spatio-temporal CNN to better discover relevant left ventricle endocardial abstractions from low-level features to high-level representations automatically.
Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks

Current sleep medicine relies on the supervised analysis of polysomnographic measurements, comprising amongst others electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals. Convolutional neural networks (CNN) provide an interesting framework to automated classification of sleep based on these raw waveforms. In this study, we compare existing CNN approaches to four databases of pathological and physiological subjects. The best performing model resulted in Cohen's Kappa of $\kappa = 0 . 75$ on healthy subjects and $\kappa = 0 . 64$ on patients suffering from a variety of sleep disorders. Further, we show the advantages of additional sensor data (i.e., EOG and EMG). Deep learning approaches require a lot of data which is scarce for less prevalent diseases. For this, we propose a transfer learning procedure by pretraining a model on large public data and fine-tune this on each subject from a smaller dataset. This procedure is demonstrated using a private REM Behaviour Disorder database, improving sleep classification by 24.4%.
“It is like a jungle gym, and everything is under construction”: The parent's perspective of caring for a child with a rare disease

DESCRIPTIVE TITLE Parents of children with rare diseases face pervasive challenges in meeting medical and social care needs. Existing research on the parents' experience of caring for a child with a rare disease is limited. This paper offers suggestions for better supporting families living with rare disease as well as possible avenues of future research. BACKGROUND Parents of children with rare diseases face pervasive challenges in meeting medical and social care needs. Existing research on the parent's experience of caring for a child with a rare disease is limited. METHODS An interpretive phenomenological approach was applied in this inquiry. Fifteen parents of children with rare diseases participated in semistructured interviews. RESULTS Interpretive thematic analysis revealed that due to the rarity of the disease and an overall lack of knowledge of the disease, there is an increase in the burden on the family in relation to "rarity" in addition to "disability. " Four insights were also revealed: (a) Parents often know more about the disease then Health Care providers, and this leads to entanglements in communication and collaboration as experts and parents; (b) there is lack of coordination of care between providers and services caring for children with rare diseases; (c) there is a gap in accessibility to government supports; and (d) due to fragmented care, parents must fill the aforementioned gaps by juggling multiple roles including that of advocate, case manager, and medical navigator. CONCLUSION This paper offers suggestions for better supporting families living with rare disease as well as possible avenues of future research.