Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximizing Influence Diffusion over Evolving Social Networks

Influence diffusion in social networks has been intensively studied over last two decades. Most prior arts assume that the underlying network structure is static, remaining fixed during the influence diffusion process. However, many real networks are growing over time in terms of both the number of users and the relations in between. This motivates us to make the first study on influence diffusion over such evolving networks, where we extend the classical Influence Maximization (IM) problem to accomodate network evolution, i.e., a fairly general joining in behavior of new users. The goal of evolving IM problem studied in this paper is to select, at a given time, a few influential nodes (seeds) to initiate a diffusion with maximum spread over the network evolved after a certain time period. To tackle the both unknown network topology and influence probability arisen from the network evolution, our solution is to propose an Uppber Confidence Bound (UCB) based learning method to learn, on a multi-round basis, the unknown influence probabilities from previous diffusion feedbacks, and perform seed selection for diffusion maximization accordingly in each round. Our influence learning method provably returns a sub-linear regret bound of influence diffusion size to time. Meanwhile, empirical results performed under real evolving network datasets unravel the effect of network evolution on the influence diffusion, and demonstrate that the proposed solution significantly outperforms the non-evolving counterparts on maximizing the influence diffusion size over evolving social networks.
Fractional Order Simple Chaotic Oscillator with Saturable Reactors and Its Engineering Applications

Chaos is often observed in forced nonlinear electrical circuits with saturable reactors. Simplest of such a circuit is presented and investigated in both integer order and non-integer (fractional) order form. For numerical analysis of fractional order system we used Adam-Bashforth-Moulton method and investigated the various dynamic properties of the system. For implementing the system in field programmable gate arrays (FPGA) we used the Adomian decomposition method. Power and resource utilization of the fractional order system for implementing in FPGA are presented. Also, in this work, a new fractional based sound encryption application has been implemented as a unique application.
Lens antenna adjustment for telecommunication and imaging modes in a sub‐THz radio system

This article presents a concept of a dual‐mode operated sub‐THz frequency radio system by adjusting the lens‐antenna distance for either telecommunication or imaging modes. The signal transmittance and imaging capabilities are demonstrated using a continuous wave operated transceiver with operation frequency 220 to 330 GHz where the 6G wireless radio system could be allocated. A high‐gain bullet‐shape lens antenna was investigated for imaging the natural object (Bergenia leaf) in the short‐range line‐of‐sight radio link. The bullet lens performed with the gain of 28 dB and the 1° beamwidth over the frequency band. For the demonstration of dual‐mode operation, the leaf was placed into the middle of the radio link path and then its image was synthesized at three lenses to the antenna‐distances by utilizing the inverse synthetic‐aperture radar technique. For image synthesizing, the movement pattern area (100 mm × 100 mm) is defined with 5 mm steps to sweep the object area. Three 100 mm × 100 mm images by 5 mm steps from different lens positions in focal axis distances (4, 15, and 30 mm were synthesized. The comparison shows that 15 mm distance has the highest gain and 30 mm distance has the higher image quality. Therefore, there is the possibility to switch from the high gain low‐resolution mode to the low gain high‐resolution mode by changing the lens position in terms of the feed. The imaging feasibility can be applied at 6G radio systems if adjustable lens systems are used revealing the new potential features in future radios.
Checklist for Theoretical Report in Epidemiological Studies (CRT-EE): explanation and elaboration

Abstract Introduction: The theory is considered essential to research, however, its value is often underestimated in development and/or reporting in epidemiological studies. Objective: To present a document for the elaboration and explanation of an instrument for theoretical reporting in epidemiological studies. Methods: A theoretical model was developed, based on the theory of Meaningful Learning and literature review, to list dimensions and variables related to the quality of theoretical reporting. The review was carried out between July 2018 and August 2019, in the databases: Medline, SciELO, LILACS, SCOPUS and Web of Science. There were no restrictions related to the period of publications. The languages used were: Portuguese, English and Spanish. Results: A checklist of 15 points was developed, related to the title (1), abstract (1), introduction (4), methods (4), results (2), discussion (2) and conclusion (1) of the articles; and presents a column for marking the information requested in the article for each point. Explanations about each point of the instrument are presented, including examples, references to studies and justifications. Conclusion: This document provides guidance for improving theoretical reporting in epidemiological research and facilitates theoretical evaluation and interpretation of studies by reviewers, editors and readers.
Characterization of Brassica rapa RAP2.4-Related Proteins in Stress Response and as CUL3-Dependent E3 Ligase Substrates

The turnip Brassica rapa has important economic value and represents a good model system to study gene function in crop plants. ERF/AP2 transcription factors are a major group of proteins that are often involved in regulating stress-responses and developmental programs. Some ERF/AP2 proteins are targets of CULLIN3-based E3 ligases that use BTB/POZ-MATH proteins as substrate receptors. These receptors bind the transcription factor and facilitate their ubiquitylation and subsequent degradation via the 26S proteasome. Here, we show tissue and stress-dependent expression patterns for three Brassica rapa ERF/AP2 proteins that are closely related to Arabidopsis thaliana AtRAP2.4. Cloning of the Brassica genes showed that the corresponding proteins can assemble with a BPM protein and CULLIN3, and that they are instable in a 26S proteasome dependent manner. This work demonstrates the conserved nature of the ERF/AP2-CULLIN3-based E3 ligase interplay, and represents a first step to analyze their function in a commercially relevant crop plant.
The Dose Response for Sprint Interval Training Interventions May Affect the Time Course of Aerobic Training Adaptations

Low vs. high volume sprint-interval training (SIT) sessions have shown similar physiological benefits after 8 weeks. However, the dose response and residual effects of shorter SIT bouts (<10 s) are unknown. Following a 6-wk control period, 13 healthy inactive males were assigned to a low dose (LDG: n = 7) or high dose (HDG: n = 6) supervised 6-wk intervention: ×2/wk of SIT (LDG = 2 sets of 5 × 6 s ON: 18 s OFF bouts; HDG = 4–6 sets); ×1/wk resistance training (3 exercises at 3 × 10 reps). Outcome measures were tested pre and post control (baseline (BL) 1 and 2), 72 h post (0POST), and 3-wk post (3POST) intervention. At 0POST, peak oxygen uptake (VO2peak) increased in the LDG (+16%) and HDG (+11%) vs. BL 2, with no differences between groups (p = 0.381). At 3POST, VO2peak was different between LDG (−11%) and HDG (+3%) vs. 0POST. Positive responses for the intervention’s perceived enjoyment (PE) and rate of perceived exertion (RPE) were found for both groups. Blood pressure, blood lipids, or body composition were not different between groups at any time point. Conclusion: LDG and HDG significantly improved VO2peak at 0POST. However, findings at 3POST suggest compromised VO2peak at 0POST in the HDG due to the delayed time course of adaptations. These findings should be considered when implementing high-dose SIT protocols for non-athletic populations.
The prevalence of histologic acute chorioamnionitis among HIV infected pregnant women in Uganda and its association with adverse birth outcomes

Background Preterm birth (PTB) is a leading cause of neonatal mortality and longer-term morbidity. Acute chorioamnionitis (ACA) is a common cause of PTB, however, there are limited data on the prevalence of ACA and its association with PTB in resource limited settings. Methods Data and samples came from a clinical trial evaluating novel strategies for the prevention of malaria in HIV infected pregnant women in Uganda. Women were enrolled between 12–28 weeks of gestation and followed through delivery. For each placenta delivered, three placental tissue types (membrane roll, umbilical cord and chorionic plate/villous parenchyma) were collected. Slides were assessed for diagnosis of maternal and fetal ACA by microscopic evaluation of neutrophilic infiltration using a standardized grading scale. The primary outcomes were PTB (<37 weeks), low birth weight (LBW, <2500 grams), and small-for-gestational age (SGA, birth weight <10th percentile for age). Univariate and multivariate logistic regression were used to estimate associations between 1) maternal characteristics (age, education, wealth, gravidity, gestational age at enrollment, placental malaria, anti-malarial prophylaxis treatment regimen, HIV disease parameters) and ACA, and 2) associations between ACA and adverse birth outcomes. Findings A total of 193 placentas were included in the analysis. The prevalence of maternal and fetal ACA was 44.5% and 28.0%, respectively. HIV infected women between 28–43 years of age had a higher risk of maternal ACA compared to those between 17–21 years of age (50.9% vs. 19.1%; aOR = 4.00 (1.10–14.5), p = 0.04) and the diagnosis of severe maternal ACA was associated with a significantly higher risk of PTB (28.6% vs. 6.0%; aOR = 6.04 (1.87–19.5), p = 0.003), LBW (33.3% vs. 9.4%; aOR = 4.86 (1.65–14.3); p = 0.004), and SGA (28.6% vs. 10.1%; aOR = 3.70 (1.20–11.4), p = 0.02). No maternal characteristics were significantly associated with fetal ACA and the diagnosis of fetal ACA was not associated with adverse birth outcomes. Conclusions Histological evidence of severe maternal ACA was associated with an increased risk of PTB, LBW, and SGA in HIV infected, pregnant Ugandan women.
Greater Peri-Aortic Fat Volume at Midlife is Associated with Slower Gait Speed Later in Life in Women: The SWAN Cardiovascular Fat Ancillary Study.

BACKGROUND Higher perivascular adipose tissue (PVAT) contributes to adverse physiologic alterations in the vascular wall, and thus could potentially limit normal physical function later in life. We hypothesize that higher PVAT volume at midlife is prospectively associated with slower gait speed later in life, independent of overall adiposity and other risk factors. METHODS Participants from the Study of Women's Health Across the Nation (SWAN) cardiovascular fat ancillary study were included. PVAT volume around the descending aorta was quantified using existing CT scans at midlife, while gait speed was measured after an average of 10.4 ± 0.7 years. RESULTS 276 women (age 51.3±2.8 years at PVAT assessment) were included. Mean gait speed was 0.96 ± 0.21 m/s. Adjusting for study-site, race, education-level, menopausal status, and length of descending aorta at PVAT assessment, and age, body mass index, difficulty paying for basics, overall health and smoking status at gait speed assessment, a higher midlife PVAT volume was associated with a slower gait speed later in life (P=0.03). With further adjustment for presence of any comorbid conditions by the time of gait speed assessment, the association persisted; every 1-SD increase in log-PVAT was associated with 3.3% slower gait speed (95% CI: 0.3%-6.3%; P=0.03). CONCLUSION Greater PVAT in midlife women may contribute to poorer physical function in older age supporting a potential role of midlife PVAT in multiple domains of healthy aging. Additional research is needed to fully elucidate the physiologic changes associated with PVAT that may underlie the observed associations.
Mitogen Activated Protein Kinases in Steatotic and Non-Steatotic Livers Submitted to Ischemia-Reperfusion

We analyzed the participation of mitogen-activated protein kinases (MAPKs), namely p38, JNK and ERK 1/2 in steatotic and non-steatotic livers undergoing ischemia-reperfusion (I-R), an unresolved problem in clinical practice. Hepatic steatosis is a major risk factor in liver surgery because these types of liver tolerate poorly to I-R injury. Also, a further increase in the prevalence of steatosis in liver surgery is to be expected. The possible therapies based on MAPK regulation aimed at reducing hepatic I-R injury will be discussed. Moreover, we reviewed the relevance of MAPK in ischemic preconditioning (PC) and evaluated whether MAPK regulators could mimic its benefits. Clinical studies indicated that this surgical strategy could be appropriate for liver surgery in both steatotic and non-steatotic livers undergoing I-R. The data presented herein suggest that further investigations are required to elucidate more extensively the mechanisms by which these kinases work in hepatic I-R. Also, further researchers based in the development of drugs that regulate MAPKs selectively are required before such approaches can be translated into clinical liver surgery.
Machine Learning Approach for Gesture Based Arabic Sign Language Recognition for Impaired People

Exceptional research activities have been endorsed by the Arabic Sign Language for recognizing gestures and hand signs utilizing the deep learning model. Sign languages refer to the gestures, which are utilized by hearing impaired people for communication. These gestures are complex for understanding by normal people. Due to variation of Arabic Sign Language (ArSL) from one territory to another territory or between countries, the recognition of Arabic Sign Language (ArSL) became an arduous research problem. The recognition of Arabic Sign Language has been learned and implemented utilizing multiple traditional and intelligent approaches and there were only less attempts made for enhancing the process with the help of deep learning networks. The proposed system here encapsulates a Convolutional Neural Network (CNN) based machine learning technique, which utilizes wearable sensors for recognition of the Arabic Sign Language (ArSL). The model suits to all local Arabic gestures, which are used by the hearing-impaired people of the local Arabic community. The proposed system has a reasonable and moderate accuracy. Initially a deep Convolutional network is built for feature extraction, which is extracted from the collected data by the wearable sensors. These sensors are used for recognizing accurately the 30 hand sign letters of the Arabic sign language. DG5-V hand gloves embedded with wearable sensors are used for capturing the hand movements in the dataset. The CNN approach is utilized for the classification purpose. The hand gestures of the Arabic sign language are the input and the vocalized speech is the output of the proposed system. The results achieved a recognition rate of 90%. The proposed system was found highly efficient for translating hand gestures of the Arabic Sign Language into speech and writing.
Arrhythmogenic Propensity of the Fibrotic Substrate after AF Ablation: A Longitudinal Study using MRI-Based Atrial Models.

AIMS Inadequate modification of the atrial fibrotic substrate necessary to sustain reentrant drivers (RDs) may explain atrial fibrillation (AF) recurrence following failed pulmonary vein isolation (PVI). Personalized computational models of the fibrotic atrial substrate derived from late gadolinium enhanced (LGE)-MRI can be used to non-invasively determine the presence of RDs. The objective of this study is to assess the changes of the arrhythmogenic propensity of the fibrotic substrate after PVI. METHODS AND RESULTS Pre-and post-ablation individualized left atrial models were constructed from 12 AF patients who underwent pre- and post-PVI LGE-MRI, in 6 of whom PVI failed. Pre-ablation AF sustained by RDs was induced in 10 models. RDs in the post-ablation models were classified as either preserved or emergent. Pre-ablation models derived from patients for whom the procedure failed exhibited a higher number of RDs and larger areas defined as promoting RD formation as compared to atrial models from patients who had successful ablation, 2.6±0.9 vs. 1.8±0.2 and 18.9±1.6% vs. 13.8±1.5% vs. respectively. In cases of successful ablation, PVI eliminated completely the RDs sustaining AF. Preserved RDs unaffected by ablation were documented only in post-ablation models of patients who experienced recurrent AF (2/5 models); all of these models had also one or more emergent RDs at locations distinct from those of pre-ablation RDs. Emergent RDs occurred in regions that had the same characteristics of the fibrosis spatial distribution (entropy and density) as regions that harbored RDs in pre-ablation models. CONCLUSIONS Recurrent AF after PVI in the fibrotic atria may be attributable to both preserved RDs that sustain AF pre- and post-ablation, and the emergence of new RDs following ablation. The same levels of fibrosis entropy and density underlie the pro-RD propensity in both pre- and post-ablation substrates.
Effects of Poly(Amidoamine) Dendrimer-Coated Mesoporous Bioactive Glass Nanoparticles on Dentin Remineralization

Dentin hypersensitivity (DH) is one of the most common clinical conditions usually associated with exposed dentinal surfaces. In this study, we identified the effectiveness of poly(amidoamine) (PAMAM) dendrimer-coated mesoporous bioactive glass nanoparticles (MBN) (PAMAM@MBN) on DH treatment, examining the ion-releasing effect, dentin remineralization, and the occluding effect of dentinal tubules. We synthesized MBN and PAMAM@MBN. After soaking each sample in simulated body fluid (SBF), we observed ion-releasing effects and dentin remineralization effects for 30 days. Also, we prepared 30 premolars to find the ratio of occluded dentinal tubules after applying MBN and PAMAM@MBN, respectively. The results showed that PAMAM did not disrupt the calcium ion-releasing ability or the dentin remineralization of MBN. The PAMAM@MBN showed a better occluding effect for dentinal tubules than that of MBN (p < 0.05). In terms of dentinal tubule occlusion, the gap between MBN was well occluded due to PAMAM. This implies that PAMAM@MBN could be effectively used in dentinal tubule sealing and remineralization.
Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network

Although many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications over the years, an optimal, consensual approach remains elusive. Recent advances in deep learning algorithms provide new opportunities for improving the design of BMI decoders, including the use of recurrent artificial neural networks to decode neuronal ensemble activity in real time. Here, we developed a long-short term memory (LSTM) decoder for extracting movement kinematics from the activity of large (N = 134–402) populations of neurons, sampled simultaneously from multiple cortical areas, in rhesus monkeys performing motor tasks. Recorded regions included primary motor, dorsal premotor, supplementary motor, and primary somatosensory cortical areas. The LSTM's capacity to retain information for extended periods of time enabled accurate decoding for tasks that required both movements and periods of immobility. Our LSTM algorithm significantly outperformed the state-of-the-art unscented Kalman filter when applied to three tasks: center-out arm reaching, bimanual reaching, and bipedal walking on a treadmill. Notably, LSTM units exhibited a variety of well-known physiological features of cortical neuronal activity, such as directional tuning and neuronal dynamics across task epochs. LSTM modeled several key physiological attributes of cortical circuits involved in motor tasks. These findings suggest that LSTM-based approaches could yield a better algorithm strategy for neuroprostheses that employ BMIs to restore movement in severely disabled patients.
“Candidatus Colwellia aromaticivorans” sp. nov., “Candidatus Halocyntiibacter alkanivorans” sp. nov., and “Candidatus Ulvibacter alkanivorans” sp. nov. Genome Sequences

Unplanned oil spills during offshore production are a serious problem for the industry and the marine environment. Here, we present the genome sequence analysis of three novel hydrocarbon-degrading bacteria, namely, “Candidatus Colwellia aromaticivorans” sp. ABSTRACT Unplanned oil spills during offshore production are a serious problem for the industry and the marine environment. Here, we present the genome sequence analysis of three novel hydrocarbon-degrading bacteria, namely, “Candidatus Colwellia aromaticivorans” sp. nov., “Candidatus Halocyntiibacter alkanivorans” sp. nov., and “Candidatus Ulvibacter alkanivorans” sp. nov.
An Assistive Technology-based Approach towards Helping Visually Impaired People

The most important point to consider before considering any solution or tool for blind people is to analyze what they need. This paper describes an approach to develop a smartphone-based solution for the varied problems faced by individuals with vision disabilities. The proposed approach is based on the assumption that smartphones are highly accessible and Developers simply ignore to create solutions to help the blind users with the problems they face in using the capabilities of the smartphone. The proposed approach is a user interface that provides an abstraction layer on the top of the Operating System (OS) and it contains various functionalities to make it work seamlessly for a blind user. It includes the use of gestures, text to speech, and voice APIs provided by the OS SDK to develop a UI that eliminates the inherent need to look into the smartphone display to perform essential functions. The user interface provides a simple sequence of gestures to perform actions and in turn, provides voice feedback and response to the user. The application supports all the basic functionalities like Calls, Texts, Music, Internet, Alarm, etc. The application also enables users to adjust the app settings viz. the speed and pitch of the voice feedback. The basic gestures include swiping right for entering into a menu, swiping left for an existing menu, and swiping upward or downwards for moving through the options in the menu. Using these only gestures users can perform any action on the smartphone. The User doesn't even need to tap the app icon to open the application every time as once configured it acts as a standalone interface for using the phone and performs necessary functions. The proposed interface also supports voice-based input in addition to the gestures. User can perform the necessary actions just by giving voice commands, possibly in their native languages, like a personal assistant, making it more usable and efficient. The complete user interface is developed by keeping in mind the capabilities and limitations of outwardly disabled people. The fundamental design goal of the App is to provide the blind user with an additional tool in the form of their smartphones to perform their tasks, keeping simplicity and minimalism in mind.