Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterioplankton Community Composition Along Environmental Gradients in Lakes From Byers Peninsula (Maritime Antarctica) as Determined by Next-Generation Sequencing

This study comprises the first attempt to describe the planktonic bacterial communities of lakes from Byers Peninsula, one of the most significant limnological districts in the Maritime Antarctica, leveraging next-generation sequencing (NGS) technologies. For the survey, we selected 7 lakes covering the environmental gradient from inland to coastal lakes, some of them sampled both in surface and deep waters. Analysis provided just over 85,000 high quality sequences that were clustered into 864 unique Zero-radius Operational Taxonomic Units (ZOTUs) (i.e., 100% sequence similarity). Yet, several taxonomic uncertainties remained in the analysis likely suggesting the occurrence of local bacterial adaptations. The survey showed the dominance of the phyla Proteobacteria and Bacteroidetes. Among the former, the Gammaproteobacteria class, more specifically the order Betaproteobacteriales, was the dominant group, which seems to be a common trend in nutrient-limited Antarctic lakes. Most of the families and genera ubiquitously detected belonging to this class are indeed typical from ultra-oligotrophic environments, and commonly described as diazotrophs. On the other hand, among the members of the phylum Bacteroidetes, genera such as Flavobacterium were abundant in some of the shallowest lakes, thus demonstrating that also benthic and sediment-associated bacteria contributed to water bacterial assemblages. Ordination analyses sorted bacterial assemblages mainly based on the environmental gradients of nutrient availability and conductivity i.e., salinity. However, transient bacterial associations, that included the groups Clostridiaceae and Chloroflexi, also occurred as being forced by other drivers such as the influence of the nearby fauna and by the airborne microorganisms. As we intended, our NGS-based approach has provided a much greater resolution compared to the previous studies conducted in the area and confirmed to a large extent the previously obtained patterns, thus reinforcing the view of Byers as a hotspot of microbial biodiversity within Antarctica. This high microbial diversity allows the use of these aquatic ecosystems and their bacterial assemblages as sentinels for the monitoring of adaptive responses to climate change in this rapidly warming area.
THREADS WITH GRAPH CONTEXTUALIZATION By

We propose a graph contextualization method, pairGraphText, to study political engagement on Facebook during the 2012 French presidential election. It is a spectral algorithm that contextualizes graph data with text data for online discussion thread. In particular, we examine the Facebook posts of the eight leading candidates and the comments beneath these posts. We find evidence of both (i) candidate-centered structure, where citizens primarily comment on the wall of one candidate and (ii) issue-centered structure (i.e. on political topics), where citizens’ attention and expression is primarily directed towards a specific set of issues (e.g. economics, immigration, etc). To identify issue-centered structure, we develop pairGraphText, to analyze a network with high-dimensional features on the interactions (i.e. text). This technique scales to hundreds of thousands of nodes and thousands of unique words. In the Facebook data, spectral clustering without the contextualizing text information finds a mixture of (i) candidate and (ii) issue clusters. The contextualized information with text data helps to separate these two structures. We conclude by showing that the novel methodology is consistent under a statistical model.
Paper 1: Detecting Ponzi Schemes on Ethereum: Towards Healthier Blockchain Technology

Problem: In Ethereum network, a smart contract is software code that implements a computer protocol. Smart contracts automatically execute when preset conditions are met and cannot be terminated. Smart contracts can disguise Ponzi schemes in which only few out of hundreds of participants make profit from a contract. As the blockchain legal framework is still not fully developed, regulators may be unable to deter the creators of Ponzi schemes.
Knowledge development, technology and questions of nursing ethics

This article explores emerging ethical questions that result from knowledge development in a complex, technological age. Nursing practice is at a critical ideological and ethical precipice where decision-making is enhanced and burdened by new ways of knowing that include artificial intelligence, algorithms, Big Data, genetics and genomics, neuroscience, and technological innovation. On the positive side is the new understanding provided by large data sets; the quick and efficient reduction of data into useable pieces; the replacement of redundant human tasks by machines, error reduction, pattern recognition, and so forth. However, these innovations require skepticism and critique from a profession whose mission is to care for and protect patients. The promise of technology and the new biological sciences to radically and positively transform healthcare may seem compelling when couched in terms of safety, efficiency, and effectiveness but their role in the provision of ethical nursing care remains uncertain. Given the profound moral and clinical implications of how today’s knowledge is developed and utilized, it is time to reconsider the relationship between ethics and knowledge development in this new uncharted area.
Lenalidomide combined with intensive chemotherapy in acute myeloid leukemia and higher-risk myelodysplastic syndrome with 5q deletion. Results of a phase II study by the Groupe Francophone Des Myélodysplasies

Patients with acute myeloblastic leukemia or higher risk myelodysplastic syndromes with 5q deletion (generally within a complex karyotype) respond poorly to intensive chemotherapy and have very poor survival. In this population, we evaluated escalating doses of lenalidomide combined with intensive chemotherapy in a phase II study. Treatment consisted of daunorubicin (45 mg/m2/day, days 1–3 in cohort 1, escalated to 60 mg/m2/day, days 1–3 in cohorts 2 and 3) combined with cytosine arabinoside (200 mg/m2/day, days 1–7) and lenalidomide (10 mg/day, days 1–21 in cohorts 1 and 2, escalated to 25 mg/day, days 1–21 in cohort 3). Eighty-two patients with 5q deletion were enrolled, including 62 with acute myeloblastic leukemia, 62/79 (78%) of whom had a complex karyotype (median 7 cytogenetic abnormalities, all but 2 of them monosomal) and three had unknown karyotypes. Thirty-eight patients (46%) achieved complete remission and the overall response rate was 58.5%. Among the 62 patients with a complex karyotype, 27 achieved complete remission (44%) and 21 had cytogenetic responses. A lower response rate was observed in patients with acute myeloblastic leukemia but other pretreatment factors, including cytogenetic complexity and treatment cohort, did not significantly influence response. Fifteen patients underwent allogeneic stem cell transplantation, including 11 patients in first remission. The 1-year cumulative incidence of relapse was 64.6% and the median overall survival was 8.2 months. By comparison with conventional intensive chemotherapy, the treatment protocol we used appeared to produce higher hematologic and cytogenetic complete remission rates in patients with very poor cytogenetics, but response duration was short in this very poor risk population, highlighting the need for better post-induction strategies. Clinical trial registry number: NCT00885508
Biomechanical Adaptations and Performance Indicators in Short Trail Running

Our aims were to measure anthropometric and oxygen uptake (V˙O2) variables in the laboratory, to measure kinetic and stride characteristics during a trail running time trial, and then analyse the data for correlations with trail running performance. Runners (13 men, 4 women: mean age: 29 ± 5 years; stature: 179.5 ± 0.8 cm; body mass: 69.1 ± 7.4 kg) performed laboratory tests to determine V˙O2 max, running economy (RE), and anthropometric characteristics. On a separate day they performed an outdoor trail running time trial (two 3.5 km laps, total climb: 486 m) while we collected kinetic and time data. Comparing lap 2 with lap 1 (19:40 ± 1:57 min vs. 21:08 ± 2:09 min, P < 0.001), runners lost most time on the uphill sections and least on technical downhills (-2.5 ± 9.1 s). Inter-individual performance varied most for the downhills (CV > 25%) and least on flat terrain (CV < 10%). Overall stride cycle and ground contact time (GCT) were shorter in downhill than uphill sections (0.64 ± 0.03 vs. 0.84 ± 0.09 s; 0.26 ± 0.03 vs. 0.46 ± 0.90 s, both P < 0.001). Force impulse was greatest on uphill (248 ± 46 vs. 175 ± 24 Ns, P < 0.001) and related to GCT (r = 0.904, P < 0.001). Peak force was greater during downhill than during uphill running (1106 ± 135 vs. 959 ± 104 N, P < 0.01). Performance was related to absolute and relative V˙O2 max (P < 0.01), vertical uphill treadmill speed (P < 0.001) and fat percent (P < 0.01). Running uphill involved the greatest impulse per step due to longer GCT while downhill running generated the highest peak forces. V˙O2 max, vertical running speed and fat percent are important predictors for trail running performance. Performance between runners varied the most on downhills throughout the course, while pacing resembled a reversed J pattern. Future studies should focus on longer competition distances to verify these findings and with application of measures of 3D kinematics.
Control and Design of DC-Grids for Offshore Wind Farms

Recently, the interest in offshore wind farms has been increased significantly. Besides the huge amount of space available they have the advantage of an increased and more constant wind speed, leading to a higher and more constant production of power. Although, a lot of mechanical problems for constructing these farms have been solved during the past decade, the electrification is still a major issue in research. For large wind farms situated more than 60 km from the shore a HVDC connection is favorable. Consequently, a pure DC system could be an interesting and cost effective solution for offshore wind farms. In this paper a control structure for such a DC-grid is presented and analyzed. Furthermore, different configurations are compared and the developed simulation models are presented
Extend the Frequency Range and reduce the Path Loss in the Cellular Systems

In this research a model was applied for the purpose of studying the coefficient of loss and studying the propagation coefficient and then calculating the number of cells required for insurance. The required coverage of a given area within a given network (GSM) and the compatibility of the constituent cells of the network. In this study, the Walifsh-Ikagamei model was used to calculate the amount of path and frequency loss specified in the period from 1000 th to 3000 th. The program was simulated in the Matlab environment and based on maps from Google Earth and compared this type with the smaller squares method, a program of the fractal program. In this research it is possible to increase the frequency band used in the network and test the location.
Recent evidence for the effects of nonnutritive sweeteners on glycaemic control.

PURPOSE OF REVIEW By replacing sugar, nonnutritive sweeteners (NNSs) are thought to aid in weight management and decrease insulin resistance. We reviewed the latest randomized clinical trials (RCTs) investigating the effects NNSs on glycaemic control. RECENT FINDINGS Six RCTs addressed this topic between 2017 and 2018; the majority tested artificial NNS (sucralose or aspartame), with only one testing natural NNS (stevia and monk fruit extract). Most found no effect of NNS on blood glucose, insulin, gastric inhibitory polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) levels; however, two trials showed an effect of sucralose on the acute insulin response. SUMMARY We are still incapable of reaching a definite judgement on which types of NNS, if any, impact glycaemic control. There is a need for more research to overcome the limitations of recent RCTs, related to sample size, intervention duration, dose, form of NNSs used, and inclusion of males or female participants only. Future studies should also compare different NNS types with each other, and include the increasingly popular 'natural' NNS.
Utility of trial-to-trial latency variability of somatosensory evoked potentials for diagnosis of spinal cord demyelination.

Traditional measurement of somatosensory evoked potentials (SEPs) depends on averaging of many recordings, which introduces loss of dynamic variability. Single trial extraction provides a new measurement of SEP latency variability for evaluation of the neurodynamic status of the somatosensory pathway. The aim of this study was to apply a single trial SEP to diagnose the severity of demyelination in a chronical spinal cord injury model. The severity of demyelination was measured by myelin area and staining intensity at ventral column (VC), lateral column (LC) and dorsal column (DC) by histological examination with Luxol fast blue staining. Results showed that there was a strong negative correlation of the latency variability of trial-to-trial SEP with the myelin area in three columns (DC: r = -0.90, p < 0.05; VC: r = -0.91, p < 0.05; LC: r = -0.89, p < 0.05), and the staining intensity in three columns (DC: r = -0.95, p < 0.05; VC: r = -0.94, p < 0.05; LC: r = -0.93, p < 0.05). These data suggest that single trial SEP can provide a dynamic indicator of spinal cord demyelination.
Unique brain regions involved in positive versus negative emotional modulation of pain

Abstract Background and aims Research has shown that negative emotions increase perceived pain whereas positive emotions reduce pain. Here we aim to investigate the neural mechanisms underlying this phenomenon. Methods While undergoing functional magnetic resonance imaging of the brain, 20 healthy adult females were presented with negative, neutral, and positive emotion-evoking visual stimuli in combination with the presentation of a noxious thermal stimulus to the hand. Participants rated the intensity and unpleasantness of the noxious thermal stimulus during each of the valence conditions. General linear model analyses were performed on the imaging data for each valence condition and specific contrasts were run. Results Significant differences were detected for the emotional modulation of pain (EMP) between the positive and negative conditions. Unique to the positive condition, there was increased activity in the inferior parietal, parahippocampal/perirhinal, precuneus/superior parietal, and the prefrontal cortices. Unique to the negative condition, there was increased activity in anterior and posterior cingulate and angular gyrus. Conclusions Positive and negative EMP appear to involve different brain regions. Implications Although there is some overlap in the brain regions involved in the positive and negative EMP, brain regions unique to each condition are identified and, moreover, the regions identified are involved in internal and external focus, respectively, pointing to a potential mechanism underlying this phenomenon.
Cooperative Ambient Backscatter Communications for Green Internet-of-Things

Ambient backscatter communication (AmBC) enables a passive backscatter device to transmit information to a reader using ambient RF signals, and has emerged as a promising solution to green Internet-of-Things (IoT). Conventional AmBC receivers are interested in recovering the information from the ambient backscatter device (A-BD) only. In this paper, we propose a cooperative AmBC (CABC) system in which the reader recovers information not only from the A-BD, but also from the RF source. We first establish the system model for the CABC system from spread spectrum and spectrum sharing perspectives. Then, for flat fading channels, we derive the optimal maximum-likelihood (ML) detector, suboptimal linear detectors as well as successive interference-cancellation (SIC) based detectors. For frequency-selective fading channels, the system model for the CABC system over ambient orthogonal frequency division multiplexing carriers is proposed, upon which a low-complexity optimal ML detector is derived. For both kinds of channels, the bit-error-rate expressions for the proposed detectors are derived in closed forms. Finally, extensive numerical results have shown that, when the A-BD signal and the RF-source signal have equal symbol period, the proposed SIC-based detectors can achieve near-ML detection performance for typical application scenarios, and when the A-BD symbol period is longer than the RF-source symbol period, the existence of backscattered signal in the CABC system can enhance the ML detection performance of the RF-source signal, thanks to the beneficial effect of the backscatter link when the A-BD transmits at a lower rate than the RF source.
Artificial Neural Network for LiDAL Systems

In this paper, we introduce an intelligent light detection and localization (LiDAL) system that uses artificial neural networks (ANN). The LiDAL systems of interest are MIMO LiDAL and MISO IMG LiDAL systems. A trained ANN with the LiDAL system of interest is used to distinguish a human (target) from the background obstacles (furniture) in a realistic indoor environment. In the LiDAL systems, the received reflected signals in the time domain have different patterns corresponding to the number of targets and their locations in an indoor environment. The indoor environment with background obstacles (furniture) appears as a set of patterns in the time domain when the transmitted optical signals are reflected from objects in LiDAL systems. Hence, a trained neural network that has the ability to classify and recognize the received signal patterns can distinguish the targets from the background obstacles in a realistic environment, especially given the mobility of targets (humans) which distinguishes them from static obstacles (furniture). The LiDAL systems with ANN are evaluated in a realistic indoor environment through computer simulation.
Recurrent Embedding Aggregation Network for Video Face Recognition

Recurrent networks have been successful in analyzing temporal data and have been widely used for video analysis. However, for video face recognition, where the base CNNs trained on large-scale data already provide discriminative features, using Long Short-Term Memory (LSTM), a popular recurrent network, for feature learning could lead to overfitting and degrade the performance instead. We propose a Recurrent Embedding Aggregation Network (REAN) for set to set face recognition. Compared with LSTM, REAN is robust against overfitting because it only learns how to aggregate the pre-trained embeddings rather than learning representations from scratch. Compared with quality-aware aggregation methods, REAN can take advantage of the context information to circumvent the noise introduced by redundant video frames. Empirical results on three public domain video face recognition datasets, IJB-S, YTF, and PaSC show that the proposed REAN significantly outperforms naive CNN-LSTM structure and quality-aware aggregation methods.
Can Continuous Positive Airway Pressure Reduce the Risk of Stroke in Obstructive Sleep Apnea Patients? A Systematic Review and Meta-Analysis

Background and Purpose Obstructive sleep apnea (OSA) has been shown to increase the risk of stroke. Although continuous positive airway pressure (CPAP) is considered the treatment of choice for OSA, whether treating OSA with CPAP reduces the risk of stroke remains unclear. We aimed to evaluate the effects of CPAP on incidence of stroke in patients with OSA. Materials and Methods We conducted a systematic review and meta-analysis of all published studies that provided the number of incident strokes in OSA patients in light of their treatment status with CPAP. Results We identified 8 relevant studies: one randomized controlled study (RCT), 5 cohort studies, and 2 studies using administrative health data. The two overlapping cohort studies in women and the elderly and the 2 studies using administrative health data had analyzed the impact of CPAP on stroke apart from cardiac events, whereas the others had focused on the overall cardiovascular events. Based on a meta-analysis of the cohort studies, treatment with CPAP was associated with a lower incidence of stroke and cardiac events with relative risks of 0.27 [0.14–0.53], and 0.54 [0.38–0.75], respectively, although this could not be reproduced in the RCT and the studies using administrative data. Conclusions Treating with CPAP in patients with OSA might decrease the risk of stroke, although there is some conflicting evidence. Such effect was more pronounced in stroke than in cardiac events. Future studies analyzing stroke apart from cardiac disease would be of interest.
Impact of Subliminally Presented Words Valence’ on Risk-Taking Decisions in a Game of Chance

A positive mood is thought to accompany performing a risk-taking tendency, for instance in games of chance or gambling. This study concerns the impact of emotional stimuli presented in a subliminal manner on the riskiness of decisions made in a game of chance. The heights of stakes called in the game were adopted as the measure of risk taken. Special simulation of a real game of chance, based on coin tossing, was used for this experiment. The stimuli displayed subliminally were words differing in valence (three levels: negative, neutral, and positive). We expected that positive valence would provoke the riskiness of the subsequent decision. The main effect of the valence observed was that the subjects in positive word conditions bet higher stakes than in neutral and negative conditions. Positive emotions influenced the riskiness of decisions made by the subjects, which confirmed the set hypothesis. The results of the study, in addition to their theoretical implications, may have practical meaning due to realistic simulation of popular games of chance.
Learning walk and trot from the same objective using different types of exploration

In quadruped gait learning, policy search methods that scale high dimensional continuous action spaces are commonly used. In most approaches, it is necessary to introduce prior knowledge on the gaits to limit the highly non-convex search space of the policies. In this work, we propose a new approach to encode the symmetry properties of the desired gaits, on the initial covariance of the Gaussian search distribution, allowing for strategic exploration. Using episode-based likelihood ratio policy gradient and relative entropy policy search, we learned the gaits walk and trot on a simulated quadruped. Comparing these gaits to random gaits learned by initialized diagonal covariance matrix, we show that the performance can be significantly enhanced.