Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study

Background Although rates of preterm birth continue to increase globally, identification of preterm from low birth weight infants remains a challenge. The burden of low birth weight vs preterm is greatest in resource-limited settings, where gestational age (GA) prior to delivery is frequently not known because ultrasound in early pregnancy is not available and estimates of the date of the mother’s last menstrual period (LMP) may not be reliable. An alternative option is to assess GA at birth to optimize referral and care of preterm newborns. We previously developed and pilot-tested a system to measure the simplified gestational age score (SGAS) based on 4 easily observable neonatal characteristics. Objective The objective of this study is to adapt the scoring system as a tablet app (potentially scalable approach) to assess feasibility of use and to validate whether the scoring system accurately predicts prematurity by itself, over and above birth weight in a large sample of newborns. Methods The study is based in Nagpur, India, at the Research Unit of the National Institute of Child Health and Human Development’s Global Network for Women’s and Children’s Health Research. The Android tablet app for the SGAS (T-SGAS) displays de-identified photographs of skin, breasts, and genitalia across a range of GAs and line drawings of infant posture. Each item is associated with a score. The user is trained to choose the photograph or line drawing that most closely matches the newborn being evaluated, and the app determines the neonate’s GA category (preterm or term) from the cumulative score. The validation study will be conducted in 3 second level care facilities (most deliveries in India occur in hospitals, and women known to be at risk of preterm birth are referred to second level care facilities). Within 24 hours of delivery, women and their babies who are stable will be enrolled in the study. Two auxiliary nurse midwives (ANMs) blinded to prior GA assessments will use the T-SGAS to estimate the GA status of the newborn. An independent data collector will abstract the GA from the ultrasound recorded in the hospital chart and record the date of the mother’s LMP. Eligibility for analysis is determined by the ultrasound and LMP data being collected within 1 week of each other to have a rigorous assessment of true GA. Results Publication of the results of the study is anticipated in 2019. Conclusions Until GA dating by ultrasound is universally available and easy to use in resource-limited settings, and where there are restrictions on ultrasound use due to their use for sex determination and abortion of female fetuses, this study will determine whether the T-SGAS app can accurately assess GA in risk categories at birth. Trial Registration ClinicalTrials.gov NCT02408783; https://clinicaltrials.gov/ct2/show/NCT02408783 (Archived by Webcite at http://www.webcitation.org/75S2kmr3T) International Registered Report Identifier (IRRID) DERR1-10.2196/11913
Elements of Sequential Monte Carlo

A core problem in statistics and probabilistic machine learning is to compute probability distributions and expectations. This is the fundamental problem of Bayesian statistics and machine learning, which frames all inference as expectations with respect to the posterior distribution. The key challenge is to approximate these intractable expectations. In this tutorial, we review sequential Monte Carlo (SMC), a random-sampling-based class of methods for approximate inference. First, we explain the basics of SMC, discuss practical issues, and review theoretical results. We then examine two of the main user design choices: the proposal distributions and the so called intermediate target distributions. We review recent results on how variational inference and amortization can be used to learn efficient proposals and target distributions. Next, we discuss the SMC estimate of the normalizing constant, how this can be used for pseudo-marginal inference and inference evaluation. Throughout the tutorial we illustrate the use of SMC on various models commonly used in machine learning, such as stochastic recurrent neural networks, probabilistic graphical models, and probabilistic programs.
Raptor Codes

A Fountain code is a code of fixed dimension and a limitless block-length. This is a class of codes with many interesting properties and applications. In this talk I will introduce several classes of probabilistic Fountain codes, including LT-and Raptor codes, show tools for their design and analysis, and discuss how they are used today to solve various data transmission problems on heterogenous unreliable networks. I will also talk about the theory of these codes when transmission takes place over non-erasure channels, and low-complexity algorithms are used for their decoding.
Eliciting stakeholder preferences for patient-centered research

Background Rather than identifying exposures and outcomes for research solely based on interests of medical professionals, there is a need for research that answers questions that are important to patients, so that they may make treatment decisions based on evidence that reflect their individual preferences. Objective To identify exposures and outcomes of interest that could be studied with electronic health record data from inpatient care. Design, setting, participants Mixed-methods analysis of semi-structured interviews administered in 2017 to 76 patients and 26 physicians who receive or provide care at Beth Israel Deaconess Medical Center in Boston, MA. Measurements After conducting detailed semi-structured interviews about topics of interest that can be studied using electronic health records of inpatient care, we used an inductive approach to identify themes about the health care experience. Results Participants reported concerns about adverse effects of medication changes, drug interactions, and surgery and other invasive procedures. The outcomes of greatest concern to them were in-hospital deaths and hospital-acquired infections. Participants commented on the importance of clear communication and information transfers, the hospital environment, accurate skills and knowledge, and upholding patient dignity and respect. Conclusion Engaging patients and physicians in the research development process provided insight to the exposures and outcomes they consider important. Our questions about exposures and outcomes of interest were restricted to topics that could be studied with electronic health record data from inpatient care, but using a similar approach to elicit feedback about the health care experience could be used to glean insight for other areas of future research.
Parallel Medical Imaging: A New Data-Knowledge-Driven Evolutionary Framework for Medical Image Analysis

There has been much progress in data-driven artificial intelligence technology for medical image analysis in last decades. However, it still remains a challenge due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven evolutionary framework termed as Parallel Medical Imaging (PMI) for medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the parallel evolutionary optimization, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decision. A GANs-based PMI framework for case studies of mammogram analysis is demonstrated in this work.
Unifying Mechanism for Multiple Sclerosis and Amyotrophic Lateral Sclerosis: Reactive Oxygen Species, Oxidative Stress, and Antioxidants

Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) are neurological diseases whose symptoms are described. Evidence is presented for involvement of harmful reactive oxygen species (ROS) and oxidative stress (OS) with beneficial effects by antioxidants (AO). Details of action mode for AOs and ROS-OS are presented. Mechanistic similarity exists with other brain illnesses, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Schizophrenia (SCZ). Other factors are involved in a multifaceted manner.
EEG Motor Imagery Applications in Brain Computer Interface based Wheelchair Control

Principally, this study gives an overview about the Neuronal oscillations appear throughout the nervous system in structures as well as, the range of frequencies of clinical and physiological interests for motor imagery EEG signal. In addition, a brief description about MI paradigm which is also known as movement imagery, which is a mental process through which a person imagines a physical action, such as jumping, or moving hands. In particular, event-related desynchronization (ERD) and synchronization (ERS). Finally, a set of studies have been listed towards highlights the advantages of using BCI Competition dataset which is a public dataset that have been widely used in the analysis of the EEG motor imagery signal methods and technique.
Digital Signatures for Consensus

We present a pairing-based signature scheme for use in blockchains that achieves substantial savings in bandwidth and storage requirements while providing strong security guarantees. Our signature scheme supports aggregation on the same message, which allows us to compress multiple signatures on the same block during consensus, and achieves forward security, which prevents adaptive attacks on the blockchain. Our signature scheme can be applied to all blockchains that rely on multi-party consensus protocols to agree on blocks of transactions (such as proof-of-stake or permissioned blockchains).
Combinatorial primality test

In 1879, Laisant-Beaujeux gave the following result without proof: If n is a prime, then [EQUATION] This paper provides proofs of the result of Laisant-Beaujeux in two cases explicitly: (1) If an integer of the form n = 4k + 1, k > 0 is prime, then ([EQUATION]) and (2) If an integer of the form n = 4k + 3, k ≥ 0 is prime, then [EQUATION]. In addition, the author proposes important conjectures based on the converse of the above theorems which aim to establish primality of n. These conjectures are scrutinized by the given combinatorial primality test algorithm which can also distinguish patterns of prime n whether it is of the form 4k + 1 or 4k + 3.
What sets Verified Users apart?: Insights, Analysis and Prediction of Verified Users on Twitter

Social network and publishing platforms, such as Twitter, support the concept of a secret proprietary verification process, for handles they deem worthy of platform-wide public interest. In line with significant prior work which suggests that possessing such a status symbolizes enhanced credibility in the eyes of the platform audience, a verified badge is clearly coveted among public figures and brands. What are less obvious are the inner workings of the verification process and what being verified represents. This lack of clarity, coupled with the flak that Twitter received by extending aforementioned status to political extremists in 2017, backed Twitter into publicly admitting that the process and what the status represented needed to be rethought. With this in mind, we seek to unravel the aspects of a user's profile which likely engender or preclude verification. The aim of the paper is two-fold: First, we test if discerning the verification status of a handle from profile metadata and content features is feasible. Second, we unravel the features which have the greatest bearing on a handle's verification status. We collected a dataset consisting of profile metadata of all 231,235 verified English-speaking users (as of July 2018), a control sample of 175,930 non-verified English-speaking users and all their 494 million tweets over a one year collection period. Our proposed models are able to reliably identify verification status (Area under curve AUC > 99%). We show that number of public list memberships, presence of neutral sentiment in tweets and an authoritative language style are the most pertinent predictors of verification status. To the best of our knowledge, this work represents the first attempt at discerning and classifying verification worthy users on Twitter.
Low-dose methoxyflurane analgesia in adolescent patients with moderate-to-severe trauma pain: a subgroup analysis of the STOP! study

Introduction The undertreatment of acute pain presents a significant challenge in the Emergency Department. This post hoc subgroup analysis of a previously reported randomized controlled UK study reports the efficacy and safety of low-dose methoxyflurane analgesia in treating adolescent patients with moderate-to-severe trauma pain. Patients and methods Three hundred patients (96 in the adolescent subgroup) aged ≥12 years requiring analgesia for acute trauma pain (pain score of 4–7 on the Numerical Rating Scale) at triage were randomized 1:1 to methoxyflurane (up to 6 mL) or placebo (normal saline), both administered using a Penthrox® inhaler. The patient could request rescue medication (paracetamol/opioids) at any time. The primary endpoint was the change from baseline in visual analog scale (VAS) pain intensity. Results Mean VAS pain score for the adolescent subgroup at baseline was ~ 61 mm. Adjusted mean change in VAS pain intensity from baseline to 5, 10, 15, and 20 minutes was −24.5, −28.1, −31.6, and −31.7 mm for methoxyflurane and −14.6, −18.8, −19.2, and −23.7 mm for placebo, with a statistically significant treatment effect in favor of methoxyflurane overall across all four time points (−9.9 mm; 95% CI: −17.4, −2.4 mm; P=0.0104). Median time to first pain relief was significantly shorter with methoxyflurane (1 minute) than placebo (3 minutes, P<0.0001). Pain relief was reported within 1–10 inhalations in 95.7% of methoxyflurane-treated patients and 64.6% of placebo-treated patients. Rescue medication was requested by two (4.3%) methoxyflurane-treated patients and three (6.3%) placebo-treated patients. Over 95% of patients, physicians, and nurses rated methoxyflurane treatment as “Excellent”, “Very Good” or “Good” compared with between 64% and 68% for placebo. The incidence of adverse events was higher with methoxyflurane (51%) than placebo (42%), mostly comprising mild/transient dizziness and headache. Conclusion This subgroup analysis shows that low-dose inhaled methoxyflurane is a rapid-acting and effective analgesic in adolescent patients presenting with moderate-to-severe trauma pain. Trial registration Clinicaltrials.gov identifier: NCT01420159, EudraCT number: 2011-000338-12.
TEX - A Securely Scalable Trustless Exchange

Financial exchanges are typically built out of two trusted components: a trade matching and a trade settlement system. With the advent of decentralized ledgers, that perform transactions without a trusted intermediary, so called decentralized exchanges (DEX) emerged. Some DEXs propose to off-load trade order matching to a centralized system outside the blockchain to scale, but settle each trade trustlessly as an expensive on-chain transaction. While DEX are non-custodial, their order books remains trusted, a malicious exchange operator or miner could front-run trades — i.e. alter trade order execution for financial gain. The scalability limitations of the settlement layer (e.g. Proof of Work (PoW) blockchains) moreover hinders the practical growth of such DEX architectures. We propose TEX, a front-running resilient, non-custodial centralized exchange. Our matching system enforces the trade order sequence provided by traders, i.e. is resilient against trade sequence alteration by the exchange operator. As such the matching system can operate in conjunction with a blockchain based settlement layer (as proposed in the following), or make custodian exchanges provably accountable for their matching process. Our layer-two settlement system executes a trade without holding the assets, and allows to reach similar scales as traditional exchanges (trading volume in USD, number of trades/second), despite a slow underlying ledger. TEX might become a point of availability-failure, but we show how the settlement system’s security properties would not compromise the trader’s assets, even if the centralized operator is compromised and/or colludes with all other traders. We provide an evaluation on a PoW blockchain.
Effectiveness of Circuit Resistance Training Versus Progressive Resistance Exercises on Shoulder Pain among Paraplegic Patients

91% of the studied paraplegic wheelchair users suffered from chronic shoulder pain. This pain is due to the overuse of joint in day to day activities. Pain will limit the function and it affects the daily living activities of the patient. Resistance training programmes will effectively increase muscle strength and upper limb functionality, by decreasing shoulder pain. Aims and Objectives: To compare the effectiveness of circuit resistance training versus progressive resistance exercises in reducing shoulder pain and improving upper extremity function and strength among paraplegic patients. Methodology:30 paraplegic wheelchair users wereselected on the basis of inclusion and exclusion criteria, and divided equally into two groups, Group A and Group B. Each group consists of 15 subjects. Group A received CRT and Group B received PRE, 1 hour a day 3 times /week for 8 weeks. The outcome measures used are DASH questionnaire, Wheelchair User’s Shoulder Pain Index and Handheld Dynamometer. Results: The calculated value for disability is 3.687, with the p< 0.05. So, CRT group shows more significance in improving function. The calculated value for pain is 2.048 with p = 0.05. So, there is no significant difference for pain between groups. The calculated value for strength on left side is 4.69 with p< 0.05 and on right side is 3.15 with p<0.05. So, CRT group shows more significance in improving strength. Conclusion: The study revealed that Circuit Resistance Training demonstrated more significant improvement in upper limb function and strength. And both CRT and PRE group shows reduction in shoulder pain among paraplegic wheelchair users.
Complete Genome Sequence of Aeromonas Phage ZPAH7 with Halo Zones, Isolated in China

Phage ZPAH7, isolated from a sediment sample from a fish farm, is a novel lytic phage belonging to the Podoviridae family. It produces large plaques (3.5 ± 0.2 mm) with halo zones (10.5 ± 0.5 mm), suggesting it has the ability to depolymerize exopolysaccharides and biofilms. ABSTRACT Phage ZPAH7, isolated from a sediment sample from a fish farm, is a novel lytic phage belonging to the Podoviridae family. It produces large plaques (3.5 ± 0.2 mm) with halo zones (10.5 ± 0.5 mm), suggesting it has the ability to depolymerize exopolysaccharides and biofilms. It has a 30,791-bp genome encoding 29 putative coding sequences.
Early and sustained deep molecular response achieved with nilotinib in high Sokal risk chronic myeloid leukemia patients

Background Nilotinib (Tasigna®) is a second-generation tyrosine kinase inhibitor that shows faster and deeper molecular responses (MR) in comparison to Imatinib as initial therapy in chronic phase chronic myeloid leukemia (CML). Efficacy and safety data for nilotinib in the Asian population is scarce, particularly in Pakistan. We aimed to determine the MR to nilotinib and its safety profile in patients with chronic phase CML. Patients and methods This observational study was conducted among 173 patients with newly diagnosed CML presenting in the chronic phase. Most patients (50.1%) had a high Sokal score at diagnosis. All patients received nilotinib 600 mg/day. The hematological and molecular responses were assessed at 3 and 6 months respectively and thereafter at 6-monthly intervals. Long-term event free survival (EFS), transformation free survival (TFS), overall survival (OS) and adverse events were observed. Results Cumulative incidence of major MR (MMR) was 86% and deep MR (DMR ie MR 4.0 and MR4.5) was 39%. Early MMR and DMR after 6 months of therapy were achieved by 74.9% and 37% of patients, respectively. Two-year EFS, TFS and OS rates for all patients were 91.9%, 92% and 92.3%, respectively. At median follow-up of 24 months, 81% and 49% of patients sustained MMR and DMR, respectively. The main adverse events were weight gain (4.6%) and abdominal pain (4%). Conclusion This study showed promising results in terms of achievement of early and sustained DMR in chronic phase CML, therefore, we recommend nilotinib as frontline treatment in Pakistani population.
Income Sources Diversification: Empirical Evidence from Edo State, Nigeria

This study reviews the cases of income sources diversification in developing countries and concluded with empirical evidence from Edo state, Nigeria. It shows that non farm income as share of total income in Africa and Latin America was 43%, while it was 51% for Asia. The empirical evidence from Edo state in Nigeria indicates that 46% of the people have a well diversified portfolio. The evidence from Edo state shows that the major sources of income in Edo state are wages and salary (33%), rent from assets (33%), sales of farm produce (14%) and trading (7%). It also indicates that income increases with level of education, with Junior Secondary school education being the lowest and First degree being the highest. The empirical evidence also indicates generally that income increases with increase in number of income sources and five income sources being the optimum that gives the highest mean income. The regression analysis shows that income sources diversification, education and location are positive and significant determinants of income, while gender has non-significant relationship with income in Edo state. These findings suggest that the increase in opportunity for people to diversify their income base will increase their household income. Those opportunities were recommended in this paper.
Capturing complexity: field-testing the use of ‘structure from motion’ derived virtual models to replicate standard measures of reef physical structure

Reef structural complexity provides important refuge habitat for a range of marine organisms, and is a useful indicator of the health and resilience of reefs as a whole. Marine scientists have recently begun to use ‘Structure from Motion’ (SfM) photogrammetry in order to accurately and repeatably capture the 3D structure of physical objects underwater, including reefs. There has however been limited research on the comparability of this new method with existing analogue methods already used widely for measuring and monitoring 3D structure, such as ‘tape and chain rugosity index (RI)’ and graded visual assessments. Our findings show that analogue and SfM RI can be reliably converted over a standard 10-m reef section (SfM RI = 1.348 × chain RI—0.359, r2 = 0.82; and Chain RI = 0.606 × SfM RI + 0.465) for RI values up to 2.0; however, SfM RI values above this number become increasingly divergent from traditional tape and chain measurements. Additionally, we found SfM RI correlates well with visual assessment grades of coral reefs over a 10 × 10 m area (SfM RI = 0.1461 × visual grade + 1.117; r2 = 0.83). The SfM method is shown to be affordable and non-destructive whilst also allowing the data collected to be archival, less biased by the observer, and broader in its scope of applications than standard methods. This work allows researchers to easily transition from analogue to digital structural assessment techniques, facilitating continued long-term monitoring, whilst also improving the quality and additional research value of the data collected.