Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Approach in Automatic Iceberg - Ship Detection with SAR Remote Sensing Data

Deep Learning is gaining traction with geophysics community to understand subsurface structures, such as fault detection or salt body in seismic data. This study describes using deep learning method for iceberg or ship recognition with synthetic aperture radar (SAR) data. Drifting icebergs pose a potential threat to activities offshore around the Arctic, including for both ship navigation and oil rigs. Advancement of satellite imagery using weather-independent cross-polarized radar has enabled us to monitor and delineate icebergs and ships, however a human component is needed to classify the images. Here we present Transfer Learning, a convolutional neural network (CNN) designed to work with a limited training data and features, while demonstrating its effectiveness in this problem. Key aspect of the approach is data augmentation and stacking of multiple outputs, resulted in a significant boost in accuracy (logarithmic score of 0.1463). This algorithm has been tested through participation at the Statoil/C-Core Kaggle competition.
Strawberry Vein Banding Virus P6 Protein Is a Translation Trans-Activator and Its Activity Can be Suppressed by FveIF3g

The strawberry vein banding virus (SVBV) open reading frame (ORF) VI encodes a P6 protein known as the RNA silencing suppressor. This protein is known to form inclusion like granules of various sizes and accumulate in both the nuclei and the cytoplasm of SVBV-infected plant cells. In this study, we have determined that the P6 protein is the only trans-activator (TAV) encoded by SVBV, and can efficiently trans-activate the translation of downstream gfp mRNA in a bicistron derived from the SVBV. Furthermore, the P6 protein can trans-activate the expression of different bicistrons expressed by different caulimovirus promoters. The P6 protein encoded by SVBV from an infectious clone can also trans-activate the expression of bicistron. Through protein-protein interaction assays, we determined that the P6 protein could interact with the cell translation initiation factor FveIF3g of Fragaria vesca and co-localize with it in the nuclei of Nicotiana benthamiana cells. This interaction reduced the formation of P6 granules in cells and its trans-activation activity on translation.
Fuzzy Leaky Bucket with Application to Coordinating Smart Appliances in Smart Homes

In the smart houses of the future, artificial intelligence will play a significant role in optimizing residents' every day life. It is envisioned that smart appliances in smart houses will work autonomously and make decisions by analyzing the house data. One important aspect of smart houses is the efficient consumption of electrical energy. To that end, there is a need for coordinating the smart appliances in a house in such a way that the energy consumption is efficient while the consumption cost remains as low as possible. In this paper, we present a new methodology for coordinating the energy consumption of smart appliances in smart homes to achieve a consumption efficiency. To that end the use of artificial intelligence technologies is essential. In particular, a smart system that integrates fuzzy logic inference with the notion of leaky bucket is proposed and tested. Results show that the proposed methodology automates the efficient scheduling of the smart appliances and subsequently achieves low consumption cost and prevents from unnecessary load morphing.
A study of modulation schemes and error correction mechanism in a Wireless underground sensor network

A cluster of sensor nodes can form a wireless underground sensor network (WUSN) deployed beneath the earth's surface for applications, like smart irrigation in agriculture field. Comparing with a free space communication, the channel in this context can also cause various signal propagation effects, which needs to be modelled and analysed, including the small-scale effects like Rayleigh fading. Different modulation schemes have been analysed to select an optimum one and an Error correction mechanism has been simulated with BPSK modulation for the performance evaluation in an AWGN channel. In this paper, the communication channel, that is, the soil medium, has been considered as a linear time varying filter in which the filter coefficients are strongly correlated, which will give the channel state information.
Interventions targeted at health professionals to reduce unnecessary caesarean sections: a qualitative evidence synthesis

Objective To establish the views and experiences of healthcare professionals in relation to interventions targeted at them to reduce unnecessary caesareans. Design Qualitative evidence synthesis. Setting Studies undertaken in high-income, middle-income and low-income settings. Data sources Seven databases (CINAHL, MEDLINE, PsychINFO, Embase, Global Index Medicus, POPLINE and African Journals Online). Studies published between 1985 and June 2017, with no language or geographical restrictions. We hand-searched reference lists and key citations using Google Scholar. Study selection Qualitative or mixed-method studies reporting health professionals’ views. Data extraction and synthesis Two authors independently assessed study quality prior to extraction of primary data and authors’ interpretations. The data were compared and contrasted, then grouped into summary of findings (SoFs) statements, themes and a line of argument synthesis. All SoFs were Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) assessed. Results 17 papers were included, involving 483 health professionals from 17 countries (nine high-income, six middle-income and two low-income). Fourteen SoFs were identified, resulting in three core themes: philosophy of birth (four SoFs); (2) social and cultural context (five SoFs); and (3) negotiation within system (five SoFs). The resulting line of argument suggests three key mechanisms of effect for change or resistance to change: prior beliefs about birth; willingness or not to engage with change, especially where this entailed potential loss of income or status (including medicolegal barriers); and capacity or not to influence local community and healthcare service norms and values relating to caesarean provision. Conclusion For maternity care health professionals, there is a synergistic relationship between their underpinning philosophy of birth, the social and cultural context they are working within and the extent to which they were prepared to negotiate within health system resources to reduce caesarean rates. These findings identify potential mechanisms of effect that could improve the design and efficacy of change programmes to reduce unnecessary caesareans. PROSPERO registration number CRD42017059455.
Visual attention in adults with attention-deficit/hyperactivity disorder before and after stimulant treatment

Abstract Background Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder which frequently persists into adulthood. The primary goal of the current study was to (a) investigate attentional functions of stimulant medication-naïve adults with ADHD, and (b) investigate the effects of 6 weeks of methylphenidate treatment on these functions. Methods The study was a prospective, non-randomized, non-blinded, 6-week follow-up design with 42 stimulant medication-naïve adult patients with ADHD, and 42 age and parental education-matched healthy controls. Assessments included measures of visual attention, based on Bundesen's Theory of Visual Attention (TVA), which yields five precise measures of aspects of visual attention; general psychopathology; ADHD symptoms; dyslexia screening; and estimates of IQ. Results At baseline, significant differences were found between patients and controls on three attentional parameters: visual short-term memory capacity, threshold of conscious perception, and to a lesser extent visual processing speed. Secondary analyses revealed no significant correlations between TVA parameter estimates and severity of ADHD symptomatology. At follow-up, significant improvements were found specifically for visual processing speed; this improvement had a large effect size, and remained when controlling for re-test effects, IQ, and dyslexia screen performance. There were no significant correlations between changes in visual processing speed and changes in ADHD symptomatology. Conclusions ADHD in adults may be associated with deficits in three distinct aspects of visual attention. Improvements after 6 weeks of medication are seen specifically in visual processing speed, which could represent an improvement in alertness. Clinical symptoms and visual attentional deficits may represent separate aspects of ADHD in adults.
Study in Natural Time of Geoelectric Field and Seismicity Changes Preceding the Mw6.8 Earthquake on 25 October 2018 in Greece

A strong earthquake of magnitude Mw6.8 struck Western Greece on 25 October 2018 with an epicenter at 37.515∘ N 20.564∘ E. It was preceded by an anomalous geolectric signal that was recorded on 2 October 2018 at a measuring station 70 km away from the epicenter. Upon analyzing this signal in natural time, we find that it conforms to the conditions suggested for its identification as precursory Seismic Electric Signal (SES) activity. Notably, the observed lead time of 23 days lies within the range of values that has been very recently identified as being statistically significant for the precursory variations of the electric field of the Earth. Moreover, the analysis in natural time of the seismicity subsequent to the SES activity in the area candidate to suffer this strong earthquake reveals that the criticality conditions were obeyed early in the morning of 18 October 2018, i.e., almost a week before the strong earthquake occurrence, in agreement with earlier findings. Finally, when employing the recent method of nowcasting earthquakes, which is based on natural time, we find an earthquake potential score around 80%.
Investigating the Efficiency of Machine Learning Algorithms on MapReduce Clusters with SSDs

In the big data era, the efficient processing of large volumes of data has became a standard requirement for both organizations and enterprises. Since single workstations cannot sustain such tremendous workloads, MapReduce was introduced with the aim of providing a robust, easy, and fault-tolerant parallelization framework for the execution of applications on large clusters. One of the most representative examples of such applications is the machine learning algorithms which dominate the broad research area of data mining. Simultaneously, the recent advances in hardware technology led to the introduction of high-performing alternative devices for secondary storage, known as Solid State Drives (SSDs). In this paper we examine the perfor-mance of several parallel data mining algorithms on MapReduce clusters equipped with such modern hardware. More specifically, we investigate standard dataset preprocessing methods including vectorization and dimensionality reduction, and two supervised classifiers, Naive Bayes and Linear Regression. We compare the execution times of these algorithms on an experimental cluster equipped with both standard magnetic disks and SSDs, by employing two different datasets and by applying several different cluster configurations. Our experiments demonstrate that the usage of SSDs can accelerate the execution of machine learning methods by a margin which depends on the cluster setup and the nature of the applied algorithms.
Monotone Precision and Recall Measures for Comparing Executions and Specifications of Dynamic Systems

The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specification discovery and specification mining are concerned with measuring the consistency between a collection of execution traces and a program specification. This problem is also tackled in process mining with the help of measures that describe the quality of a process specification automatically discovered from execution logs. Though various measures have been proposed, it was recently demonstrated that they neither fulfil essential properties, such as monotonicity, nor can they handle infinite behaviour. In this article, we address this research problem by introducing a new framework for the definition of behavioural quotients. We prove that corresponding quotients guarantee desired properties that existing measures have failed to support. We demonstrate the application of the quotients for capturing precision and recall measures between a collection of recorded executions and a system specification. We use a prototypical implementation of these measures to contrast their monotonic assessment with measures that have been defined in prior research.
Applying Deep Learning for Improving Image Classification in Nuclear Fusion Devices

Deep learning has become one of the most promising approaches in recent years. One of the main applications of deep learning is the automatic feature extraction with auto-encoders (AEs). Feature extraction, one of the most important stages in machine learning, that can reduce drastically the dimensionality of the problem, making easier any subsequent process such as classification. The main contribution of this research is to evaluate the use of AEs for automatic feature extraction in massive thermonuclear fusion databases. In order to show the performance of AEs in a practical way, the problem of image classification of the TJ-II Thomson Scattering diagnostic has been selected. The classification has been performed by the algorithm of support vector machines and conformal predictors. The results show that the use of AEs produces the predictions faster, with more reliable models, and with higher success rates in comparison to the performance without using the deep learning approach.
Seamless Designs: Current Practice and Considerations for Early-Phase Drug Development in Oncology

Abstract Traditionally, drug development has evaluated dose, safety, activity, and comparative benefit in a sequence of phases using trial designs and endpoints specifically devised for each phase. Innovations in drug development seek to consolidate the phases and rapidly expand accrual with “seamless” trial designs. Although consolidation and rapid accrual may yield efficiencies, widespread use of seamless first-in-human (FiH) trials without careful consideration of objectives, statistical analysis plans, or trial oversight raises concerns. A working group formed by the National Cancer Institute convened to consider and discuss opportunities and challenges for such trials as well as encourage responsible use of these designs. We reviewed all abstracts presented at American Society of Clinical Oncology annual meetings from 2010 to 2017 for FiH trials enrolling at least 100 patients. We identified 1786 early-phase trials enrolling 57 559 adult patients. Fifty-one of the trials (2.9%) investigated 50 investigational new drugs, were seamless, and accounted for 14.6% of the total patients. The seamless trials included a median of 3 (range = 1–13) expansion cohorts. The overall risk of clinically significant treatment-related adverse events (grade 3–4) was 49.1% (range = 0.0–100%), and seven studies reported at least one toxic death. Rapid expansion of FiH trials may lead to earlier drug approval and corresponding widespread patient access to active therapeutics. Nevertheless, seamless designs must adhere to established ethical, scientific, and statistical standards. Protocols should include prospectively planned analyses of efficacy in disease- or biomarker-defined cohorts of sufficient rigor to support accelerated approval.
Retromer has a selective function in cargo sorting via endosome transport carriers

Retromer is a peripheral membrane protein complex that coordinates multiple vesicular trafficking events within the endolysosomal system. Here, we demonstrate that retromer is required for the maintenance of normal lysosomal morphology and function. The knockout of retromer subunit Vps35 causes an ultrastructural alteration in lysosomal structure and aberrant lysosome function, leading to impaired autophagy. At the whole-cell level, knockout of retromer Vps35 subunit reduces lysosomal proteolytic capacity as a consequence of the improper processing of lysosomal hydrolases, which is dependent on the trafficking of the cation-independent mannose 6-phosphate receptor (CI-M6PR). Incorporation of CI-M6PR into endosome transport carriers via a retromer-dependent process is restricted to those tethered by GCC88 but not golgin-97 or golgin-245. Finally, we show that this retromer-dependent retrograde cargo trafficking pathway requires SNX3, but not other retromer-associated cargo binding proteins, such as SNX27 or SNX-BAR proteins. Therefore, retromer does contribute to the retrograde trafficking of CI-M6PR required for maturation of lysosomal hydrolases and lysosomal function.
Quanti-Qualitative Analysis of a Memetic Algorithm to Optimize Product Line Architecture Design

The Product Line Architecture (PLA) is one of the most important artifacts of a Software Product Line (SPL). PLA design can be formulated as an optimization problem with many factors. In this context, OPLA-Tool was developed to automatically identify the best alternatives for a PLA design using multi-objective evolutionary algorithms, based on genetic algorithms (GA). From an original PLA, OPLA-Tool obtains alternative designs to improve the original one in terms of the objectives selected for optimization. In a recent study, we extend OPLA-Tool to add a memetic algorithm (MA) and promising empirical results were obtained. However, the results allow us to hypothesize that including feature modularization as an objective to be optimized by MA could obtain even better solutions. In addition, it is interesting to know the experts' opinion about PLA designs automatically obtained, what has not been done yet. Thus, the objective of this work is twofold: to investigate the aforementioned hypothesis and to conduct the first qualitative evaluation of the PLA design solutions automatically obtained by search algorithms. An empirical study involving MA and GA was carried out with four different PLA designs. MA presented the best solutions according the quality indicators used in the quantitative analysis. The results of the qualitative evaluation showed that the optimized solutions are well evaluated by the experts. After both analyzes, the hypothesis could be confirmed.
Tactile-Based Manipulation of Wires For Switchgear Assembly

This paper presents a mechatronic approach to the robotic manipulation of electrical wires for switchgear assembly. One of the challenges is the implementation of the wire insertion task, i.e., a wire, grasped by a robot, has to be inserted into the hole of a switchgear component to be then tightened. To this aim, a tactile sensor, installed on the robot gripper, has been optimized and a suitable algorithm has been developed for the wire shape estimation. The same tactile sensor is used to automatically evaluate if the insertion task and the following tightening have been correctly completed. The proposed approach allows to reconstruct the wire end point with a precision sufficient to allow the robot correctly execute the insertion phase with a high success rate. Experimental results validate the effectiveness of the proposed approach.
Wideband Circular Polarized Antenna for Satellite Based Navigation Systems

In this paper we propose a wideband antenna structure to cover the non-military satellite navigation frequency spectrum. The antenna structure consists cross dipole elements fed with 90° phase difference to provide proper axial ratio within the whole frequency band. The axial ratio is improved by using two parasitic elements near to each dipole arm. The dipole arms are designed on a FR4 substrate and placed above a ground plane to reduce the effect of any metallic object behind the antenna. The impedance matching is better than -15 dB in 1-1.7 GHz and axial ratio is better than 3 dB in 1.17-1.67 GHz, covering the required bandwidth for satellite navigation systems.
A Low-Loss Broadband Quadrature Signal Generation Network for High Image Rejection at Millimeter-Wave Frequencies

This paper presents a broadband low-loss quadrature-hybrid-based network that enhances the phase and the amplitude matching of quadrature signals. The performance of this network is investigated, and a detailed theoretical analysis is provided. Several stages of this network can be cascaded to generate broadband balanced quadrature signals. Each stage has a loss of 0.5 dB and enhances the image rejection ratio (IRR) by approximately 8 dB. Compared with the conventional polyphase quadrature signal generation methods, the proposed network enables lower insertion loss, wider bandwidth, and reduced sensitivity to process variations. To verify the theoretical analyses, two proof-of-concept image-reject mixers are implemented in a 0.13- $\mu \text{m}$ SiGe BiCMOS technology. The first mixer achieves an average IRR of 37.5 dB across 40–76 GHz, whereas the second mixer achieves an average IRR of 33.5 dB across 40–102 GHz. The proposed network is a promising solution for broadband quadrature signal generation at millimeter-wave frequencies, as it eliminates the need for calibration and tuning.
Top-k Query for Weighted Interactive Product Configuration

Interactive product configuration should be complete and backtrack free. it requires that the system responds quickly. A popular solution to implement interactive product configuration is Binary Decision Diagrams(BDDs) which represents the solution space of product model, the structure of BDDs is very compact, and the interactive configuration can be carried out in linearly dependent time of BDD's size. In this paper, we proposed the concept of top-k query about weighted interactive product configuration based on BDDs. the solution space of BDD may be exponential explosion in practice, we defined weight value for each valid configuration, the weight represents price, quality etc., in the interactive phase, users input a rule and k, the system lists top-k maximum(minimum) valid configurations to user for reference. Using our code, we solved a number of problems including those from real application and synthetic data set. Our experiment results showed that our algorithm had a faster response time than the traditional algorithm.
Implementation of the hybrid technology for quadcopter motion control in a complex non-deterministic environment

This paper represents the results of development and research of the autonomous control system for the UAV. Existing control systems do not provide flight performance necessary for successful operations in non-deterministic environments. So, we propose hybrid intelligent technology based on unstable modes and the conception ofa virtual goal. The main feature of our approach is the efficient integration of global and local path planning providing smooth and quick correction of trajectories for the avoidance of obstacles detected by the quadrotor vision system. Moreover, our local planning approach gives the tool for passing areas with complex obstacles where other local path planning algorithms fail. The hardware-software architecture of the control system based on client-server model with the loose coupling in ROS is presented. The results of simulation and real test flights confirming the efficiency of the proposed technology are shown. We used the commercially available quadcopter and flight controller. That proves absence of necessity in special hardware tools for autonomous flight in environments with uncertainties.