Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel antioxidant peptides obtained by alcalase hydrolysis of Erythrina edulis (pajuro) protein.

BACKGROUND Oxidative reactions are responsible for the changes in quality during food processing and storage. Oxidative stress is also involved in multiple chronic diseases, such as cardiovascular and neurodegenerative disorders, diabetes, cancer, and aging. The consumption of dietary antioxidants has been demonstrated to help to reduce the oxidative damage in both the human body and food systems. In this study, the potential of Erythrina edulis (pajuro) protein as source of antioxidant peptides was evaluated. RESULTS Pajuro protein concentrate hydrolyzed by alcalase for 120 min showed potent ABTS·+ and peroxyl radical scavenging activity with Trolox equivalent antioxidant capacity (TEAC) and oxygen radical absorbance capacity (ORAC) values of 1.37 ± 0.09 µmol TE mg-1 peptide and 2.83 ± 0.07 µmol TE mg-1 peptide, respectively. Fractionation of the hydrolyzate to small peptides resulted in increased antioxidant activity. De novo sequencing of most active fractions collected by chromatographic analysis enabled 30 novel peptides to be identified. Of these, ten were synthesized and their radical activity evaluated, demonstrating their relevant contribution to the antioxidant effects observed for pajuro protein hydrolyzate. CONCLUSIONS The sequences identified represent an important advance in the molecular characterization of the pajuro protein, demonstrating its potential as a source of antioxidant peptides for food and nutraceutical applications. © 2018 Society of Chemical Industry.
Closing the Loop in Exergaming - Health Benefits of Biocybernetic Adaptation in Senior Adults

Exergames help senior players to get physically active by promoting fun and enjoyment while exercising. However, most exergames are not designed to produce recommended levels of exercise that elicit adequate physical responses for optimal training in the aged population. In this project, we developed physiological computing technologies to overcome this issue by making real-time adaptations in a custom exergame based on recommendations for targeted heart rate (HR) levels. This biocybernetic adaptation was evaluated against conventional cardiorespiratory training in a group of active senior adults through a floor-projected exergame and a smartwatch to record HR data. Results showed that the physiologically-augmented exergame leads players to exert around 40% more time in the recommended HR levels, compared to the conventional training, avoiding over exercising and maintaining good enjoyment levels. Finally, we made available our biocybernetic adaptation software tool to enable the creation of physiological adaptive videogames, permitting the replication of our study.
A Novel Approach for Swallow Detection by Fusing Throat Acceleration and PPG Signal

Swallow, as one of the most complex somatic reflexes, is a mirror of our daily ingestion and physical health. In recent years, accelerometry has become a simple and popular tool for non-invasive swallow detection. However, very few physiological signals are used in this field. In this paper, we first notice that swallowing causes significant throat photoplethysmogram (PPG) waveform fluctuation. With this inspiration, we present a novel approach for swallow detection by fusing throat acceleration (ACC) and PPG signal. The support vector machine (SVM) classifier is employed and a score level fusion method is used to access and fuse the information from ACC and PPG signal. The fusion result achieves 90.5{\% precision as well as 60.0{\% specificity, higher than the PPG based detection and the ACC based detection. The experiment result shows that our method combines the characteristics of ACC and PPG signal, providing better overall performance in swallow detection.
Adopting Centroid and Amended Trilateration for better accuracy of range-based non-GPS localization

There has been massive amount of research have been conducted in the area of indoor positioning systems specifically it's upwards research trending in Localization Based Services (LBS) within a non-open space environment or in the vicinity of high rise buildings due to the incapability of Global Positioning System (GPS) to do so. Most of the indoor localization techniques proposed by researchers to discover an optimized solution for indoor location tracking that has high precision and accuracy. This paper proposes a model for better accuracy on range-based localization algorithm in non-GPS positioning systems. The proposed model adopts the enhanced Kalman Filter (KF) and Centroid Localization Algorithm that can manipulate noise signal from raw Received Signal Strength Indicator (RSSI). There are 12 tests conducted in two different environments; at the area with less-obstacles and at the area with more obstacles. Three different algorithms are deployed with and without KF where a series of observations and comparisons are made to measure the effectiveness and reliability of KF implementation. Our analysis and finding show that the proposed model improves the accuracy percentage by more than 80%.
In Situ Measurement of Stimulus Induced pH Changes Using ThinFilm Embedded IrOx pH Electrodes

The high complexity of the biological response to implanted materials builds a serious barrier against implanted recording and stimulation electrode arrays to succeed in clinically relevant chronic studies. Some of the cell and molecular interactions and their contribution to inflammation and device failure are still unclear. The interrelated mechanisms leading to tissue damage and electrode array failure during simultaneous faradaic, electrochemical reactions and biological response under electrical stimulation are not understood sufficiently. One variable, with which inflammatory and electrode surface processes can be analyzed and assessed, is the pH change in the immediate environment of the material-tissue interface. Here, the greatest challenges are in the biocompatibility and in-vivo long-term stability of selected sensor materials, the measurement of small transient pH oscillations and positioning of the sensor at a defined and nearest possible distance in the micrometer range, to the site of activity without the pH sensing being affected by the material- issue interactions itself. This work represents the in-situ measurement of local and transient pH changes at apulsed electrode with an embedded in-vivo compatible pH sensor and therein differentiating from current approaches of pH sensing during electrical stimulation.
Current Therapies Focused on High-Density Lipoproteins Associated with Cardiovascular Disease

High-density lipoproteins (HDL) comprise a heterogeneous family of lipoprotein particles divided into subclasses that are determined by density, size and surface charge as well as protein composition. Epidemiological studies have suggested an inverse correlation between High-density lipoprotein-cholesterol (HDL-C) levels and the risk of cardiovascular diseases and atherosclerosis. HDLs promote reverse cholesterol transport (RCT) and have several atheroprotective functions such as anti-inflammation, anti-thrombosis, and anti-oxidation. HDLs are considered to be atheroprotective because they are associated in serum with paraoxonases (PONs) which protect HDL from oxidation. Polyphenol consumption reduces the risk of chronic diseases in humans. Polyphenols increase the binding of HDL to PON1, increasing the catalytic activity of PON1. This review summarizes the evidence currently available regarding pharmacological and alternative treatments aimed at improving the functionality of HDL-C. Information on the effectiveness of the treatments has contributed to the understanding of the molecular mechanisms that regulate plasma levels of HDL-C, thereby promoting the development of more effective treatment of cardiovascular diseases. For that purpose, Scopus and Medline databases were searched to identify the publications investigating the impact of current therapies focused on high-density lipoproteins.
Power Spectral Analysis of Short-Term Blood Pressure Recordings for Assessing Daily Variations of Blood Pressure in Human

Although daily variations of blood pressure (BP) predict cardiovascular event risk, their assessment requires ambulatory BP monitoring which hinders the clinical application of this approach. Since the baroreflex is a major determinant of BP variations, especially in the frequency range of 0.01-0.1 Hz (baro-frequency), we hypothesized that the power spectral density (PSD) of short-term BP recordings in the baro-frequency range may predict daily variations of BP. In nine-week-old Wister-Kyoto male rats (N =5) with or without baroreflex dysfunction, we telemetrically recorded continuous BP for 24 hours and estimated PSD using Welch’s periodogram for the recordings during the 12-hour light period. We compared the reference PSD of 12-hour recording with the PSDs obtained from shorter data lengths ranging from 5 to 240 minutes. The 30-minute BP recordings reproduced PSD of 12-hour recordingswell, and PSD in the baro-frequency range paralleled the standard deviation of 12-hour BP. Thus, the PSD of 30-minute BP reflects the daily BP variability in rats. In human subjects, we estimated PSD from 30-minute noninvasive continuous BP recordings. The rat and human PSDs shared remarkably similar characteristics. Furthermore, comparison of PSD between elderly and young subjects suggested that the baro-frequency range in humans overlapped with that in rats. In conclusion, PSD derived from 30-minute BP recordings is capable of predicting daily BP variations. Our proposed method may serve as a simple, noninvasive and practical tool for predicting cardiovascular events in the clinical setting.
Real-Life Dry-Contact Ear-EEG

Our brain state is affected by and adapted to our surroundings. Therefore, to study natural states of the brain, it is desirable to measure brain responses in natural environments outside the lab. Among functional brain scanning methods, electroencephalography (EEG) is the most promising method for non-invasive brain monitoring in real-life environments. To enable long-term recordings in real-life, EEG devices must be wearable, user-friendly, and discreet. Ear-EEG is a method where EEG signals are recorded from electrodes placed on an earpiece inserted into the ear. The compact and discreet nature of an ear-EEG device makes it suitable for long-term real-life recordings. In this study, 6 subjects were recorded with conventional scalp EEG and ear-EEG. All recordings were performed with the same instrumentation and paradigms in both a lab setting and a real-life setting. The ear-EEG recordings were performed with a previously developed drycontact ear-EEG platform. Signals from the scalp electrodes and ear-electrodes were recorded by the same biosignal recorder, enabling re-referencing in the post-processing and analysis. The study comprised four paradigms: auditory steady-state response (ASSR), steady-state visual evoked potential (SSVEP), auditory onset response, and alpha band modulation. When the data were analyzed with a scalp reference (Cz), all the investigated responses were statistically significant in recordings from both settings. Statistically significant ASSR and SSVEP were measured in the lab by ear-electrodes referenced to an electrode within the same ear. In real-life, only the ASSR was statistically significant for a reference within the same ear. The results demonstrates that electrical brain activity can be recorded from dry-contact electrode ear-EEG in real-life.
Attention-free encoder decoder for morphological processing

We present RACAI’s Entry for the CoNLL-SIGMORPHON 2018 shared task on universal morphological reinﬂection. The system is based on an attention-free encoder-decoder neural architecture with a bidirectional LSTM for encoding the input sequence and a uni-directional LSTM for decoding and producing the output. Instead of directly applying a sequence-to-sequence model at character-level we use a dynamic algorithm to align the input and output sequences. Based on these alignments we produce a series of special symbols which are similar to those of a ﬁnite-state-transducer (FST).
Effect of Controlled-Atmosphere Storage and Ethanol Rinsing on NaNi0.5Mn0.5O2 for Sodium-Ion Batteries.

NaNi0.5Mn0. 5O2 is a promising sodium-ion battery cathode material that has been extensively studied. However, the air sensitivity of this material limits practical application and is not well understood. Here, we present a detailed study of NaNi0.5Mn0. 5O2 powders stored in different atmospheres (oxygen, argon, and carbon dioxide), either dry or wet. X-ray diffraction and Fourier transform infrared measurements were used to characterize the materials and their surface species before and after controlled-atmosphere storage. It was determined that the exposure of untreated NaNi0.5Mn0. 5O2 powders to moisture results in desodiation and material degradation, leading to poor cycling. This effect was found to be caused by reactive surface species. From these results, a simple ethanol washing method was found to significantly reduce the air-reactivity and improve the electrochemical performance of NaNi0.5Mn0. 5O2 by removing surface impurities formed by air exposure.
SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer

We describe and evaluate a bug refutation extension for the Clang Static Analyzer (CSA) that addresses the limitations of the existing built-in constraint solver. In particular, we complement CSA's current heuristics for removing spurious bug reports. We encode the path constraints produced by CSA as Satisfiability Modulo Theories (SMT) problems, use SMT solvers to precisely check them for satisfiability, and remove bug reports whose associated path constraints are unsatisfiable. Our refutation extension refutes spurious bug reports in 8 out of 12 widely used open-source applications; on average, it refutes ca. 7% of all bug reports, and never refutes any true bug report. It incurs only negligible performance overheads, and on average adds 1.2% to the runtime of the full Clang/LLVM toolchain. A demonstration is available at https://www.youtube. com/watch? v=ylW5iRYNsGA.
Intercomparison of Cryogenic Frost-Point Hygrometer Observations With Radiosonde, SAPHIR, MLS, and Reanalysis Datasets Over Indian Peninsula

This paper assesses the performance of water vapor measurements by Sondeur Atmosphérique du Profild’ Humidité Intertropicale par Radiométrie (SAPHIR), microwave limb sounder (MLS), and the global reanalysis water vapor data [Modern Era Retrospective analysis for Research and Applications (MERRA) and European Center for Medium-Range Weather Forecasts reanalysis (ERA) interim] by comparing with water vapor-measured <italic>in situ</italic> by cryogenic frost-point hygrometer (CFH) at two tropical stations, Trivandrum (8.5°N, 76.9°E) and Hyderabad (17.47°N, 78.58°E). The iMet-1 radiosonde though overestimates frost-point temperature (3%–5%) in the 4–10-km altitude region with respect to CFH, it agrees well with CFH observations in the upper troposphere and the lower troposphere with a mean difference <2% and ~1%, respectively. SAPHIR–CFH intercomparison is done for the troposphere region, and MLS, MERRA, and ERA interim are compared with CFH in the lower stratosphere region. SAPHIR and CFH comparison shows a reasonable agreement between both the datasets with a relative humidity difference of about 15% in the lower and middle troposphere and a dry bias of ~40% in the upper troposphere. Intercomparison between CFH and MLS water vapor mixing ratios (WVMRs) shows a small wet bias (−10% to −20%) for the MLS in the lower stratospheric region between 100 and 50 hPa and a small dry bias (<10%) above that region. This paper shows that the MLS always underestimates when the CFH WVMR is greater than 6 ppmv and overestimates when the WVMR is less than 2 ppmv. The intercomparison of CFH with MERRA and ERA interim specific humidity shows results similar to that with MLS.
Fabrication and testing of multielectrode matrix of disordered Si nanowires for brain tissue sensing

In the field of neuroscience there is interest on manufacturing new recording devices. The relationship between individual action potentials of neurons and field potentials in multicellular records is complex. For this reason, there is a big interest in multielectrode arrays. This work describes the unconventional fabrication process of an alternative multielectrode and its use for sensing neuronal activity. It consists of a matrix of Si nanowires randomly distributed, coated with Ag nanoparticles, and with macrometric Ag back contacts. The Si nanowires are prepared by metal-assisted chemical etching of a Si wafer, which is an economical and highly reproducible technique. Recordings using the multielectrode array of randomly distributed Si nanowires look promising and comparable with recordings obtained with other multielectrode devices.
Editorial: refining the estimation of fitness for surgery.

Lung cancer is the second most common cancer in both men and women and remains the leading cause of cancer death worldwide. Non-small cell lung cancer (NSCLC) accounts for approximately 80% to 85% of new cases of lung cancer (1), with surgical resection serving as a potentially curative treatment for patients with early stage disease.
Current Status and Future Directions of mHealth Interventions for Health System Strengthening in India: Systematic Review

Background With the exponential increase in mobile phone users in India, a large number of public health initiatives are leveraging information technology and mobile devices for health care delivery. Given the considerable financial and human resources being invested in these initiatives, it is important to ascertain their role in strengthening health care systems. Objective We undertook this review to identify the published mobile health (mHealth) or telemedicine initiatives in India in terms of their current role in health systems strengthening. The review classifies these initiatives based on the disease areas, geographical distribution, and target users and assesses the quality of the available literature. Methods A search of the literature was done to identify mHealth or telemedicine articles published between January 1997 and June 2017 from India. The electronic bibliographic databases and registries searched included MEDLINE, EMBASE, Joanna Briggs Institute Database, and Clinical Trial Registry of India. The World Health Organization health system building block framework was used to categorize the published initiatives as per their role in the health system. Quality assessment of the selected articles was done using the Cochrane risk of bias assessment and National Institutes of Health, US tools. Results The combined search strategies yielded 2150 citations out of which 318 articles were included (primary research articles=125; reviews and system architectural, case studies, and opinion articles=193). A sharp increase was seen after 2012, driven primarily by noncommunicable disease–focused articles. Majority of the primary studies had their sites in the south Indian states, with no published articles from Jammu and Kashmir and north-eastern parts of India. Service delivery was the primary focus of 57.6% (72/125) of the selected articles. A majority of these articles had their focus on 1 (36.0%, 45/125) or 2 (45.6%, 57/125) domains of health system, most frequently service delivery and health workforce. Initiatives commonly used client education as a tool for improving the health system. More than 91.2% (114/125) of the studies, which lacked a sample size justification, had used convenience sampling. Methodological rigor of the selected trials (n=11) was assessed to be poor as majority of the studies had a high risk for bias in at least 2 categories. Conclusions In conclusion, mHealth initiatives are being increasingly tested to improve health care delivery in India. Our review highlights the poor quality of the current evidence base and an urgent need for focused research aimed at generating high-quality evidence on the efficacy, user acceptability, and cost-effectiveness of mHealth interventions aimed toward health systems strengthening. A pragmatic approach would be to include an implementation research component into the existing and proposed digital health initiatives to support the generation of evidence for health systems strengthening on strategically important outcomes.
Flexible Non-contact Electrodes for Bioelectrical Signal Monitoring

Physiological signals such as ECG and EMG are closely related with human health and a long term monitoring of the physiological signals would be beneficial to detect possible disorders at the early stage. The wet electrodes currently used in the clinics require adhesives gels to record high-quality signals, which might cause discomfort of the patients and introduce some risk of skin allergy. Non-contact capacitive electrodes that can be operated without skin contact have been developed in previous studies, but these electrodes were rigid with electronic components on the back, which might not be an optimal solution for long term healthcare monitoring. In this study, a flexible non-contact electrode without any electronic components on both sides was designed for the long term acquisition of bioelectrical signals to maximize subject comfort. The flexible electrode was made up of multi-layer flexible printed circuits (FPC) materials and could be bent according to the local shape to achieve better non-contact capacitive coupling with the skin. The performance of the proposed flexible electrode was compared with that of the conventional wet electrodes in different signal recording conditions. The results showed that the proposed non-contact flexible electrode can capture high quality ECG and EMG signals, and its performance was comparable to the commonly used wet electrodes. This study might provide a reliable solution with great patient comfort for the long-term monitoring of biological signals.
Neural Maximum Subgraph Parsing for Cross-Domain Semantic Dependency Analysis

We present experiments for cross-domain semantic dependency analysis with a neural Maximum Subgraph parser. Our parser targets 1-endpoint-crossing, pagenumber-2 graphs which are a good fit to semantic dependency graphs, and utilizes an efficient dynamic programming algorithm for decoding. For disambiguation, the parser associates words with BiLSTM vectors and utilizes these vectors to assign scores to candidate dependencies. We conduct experiments on the data sets from SemEval 2015 as well as Chinese CCGBank. Our parser achieves very competitive results for both English and Chinese. To improve the parsing performance on cross-domain texts, we propose a data-oriented method to explore the linguistic generality encoded in English Resource Grammar, which is a precisionoriented, hand-crafted HPSG grammar, in an implicit way. Experiments demonstrate the effectiveness of our data-oriented method across a wide range of conditions.