Miracle-dz/UniFAR-FTUs huggingface dataset:
Feedback stabilization of the 2-D and 3-D Navier-Stokes equations based on an extended system

We study the local exponential stabilization of the 2D and 3D Navier-Stokes equations in a bounded domain, around a given steady-state flow, by means of a boundary control. We look for a control so that the solution to the Navier-Stokes equations be a strong solution. In the 3D case, such solutions may exist if the Dirichlet control satisfies a compatibility condition with the initial condition. In order to determine a feedback law satisfying such a compatibility condition, we consider an extended system coupling the Navier-Stokes equations with an equation satisfied by the control on the boundary of the domain. We determine a linear feedback law by solving a linear quadratic control problem for the linearized extended system. We show that this feedback law also stabilizes the nonlinear extended system.
The influence of thermal expansion of a composite material on embedded polarimetric sensors

Some of the most critical issues of the influence of the thermal expansion of composite materials on embedded polarimetric sensors for measurements of strain and temperature are studied in this paper. A composite material sample with polarimetric fiber sensors embedded in two distinct layers of a multi-layer composite structure is fabricated and characterized. The polarimetric fiber sensors used in this study are based on Panda type fiber and polarization maintaining photonic crystal fiber (PM-PCF). The temperature sensitivities of polarimetric fiber sensors with acrylate buffer coated and buffer stripped polarization maintaining optical fibers are measured in free space and compared with those for sensors embedded in the composite material. It is found that a polarimetric fiber sensor with an acrylate coating embedded in the composite material shows the same response as the one in free space while the coating stripped fiber polarimetric sensor shows significant temperature sensitivity when embedded in the composite material. This is due to the stress induced change in birefringence created by the thermal expansion of the composite material, while in the case of a buffer coated fiber, the effect is considerably reduced as the thermal stress is largely eliminated by the buffer coating. The results obtained in this study demonstrated that thermal expansion of the composite material is the main source of error in strain and temperature measurement using embedded polarimetric fiber sensors and that more accurate strain and temperature measurements can be obtained with buffer coated polarimetric fiber sensors.
Grafting-Induced Gene Expression Change in Brassica rapa Leaves is Different from Fruit Trees

Grafting has widely used in the agriculture of fruit-bearing crops and trees because rootstocks have a profound influence on many aspects of scion development and scion responses to the environmental changes including biotic and abiotic stress tolerance. These effects appear to result from the change of gene expression on scion, but only limited numbers of papers have been published demonstrating it. To identify altered expression of genes in Chinese cabbage, Chiifu(Brassica rapa ssp. pekinensis, inbred line) shoot was grafted on three Brassica rootstocks: mustard, turnip and broccoli. After head formation, Br300K microarray experiment was conducted using total RNAs from scion leaves collected in two different seasons, spring (June) and fall (October). A large number of differentially expressed genes (DEGs) were identified both in two seasonal samples, but DEGs were more notable in June sample than in October sample. However, the number of DEGs by three rootstocks were high in October with respect to up-regulation, but high in June for down-regulation. Categories of DEGs included metal ion binding, response to hormonal stimuli, response to endogenous stimuli, regulation of transcription, oxidation reduction and response to stress. Up-regulated genes in both June and October samples were similar in mustard and turnip rootstocks, but different in broccoli rootstock. Two genes were found to respond to all experimental conditions: Brapa_ESTC049008 (hypothetical protein) as an up-regulated gene and Brapa_ESTC016027 (CNGC12) as a down-regulated gene. Together with the previous reports, these results suggest that grafting-induced gene expression depends on the species involved.
Space Telescope and Optical Reverberation Mapping Project. VII. Understanding the Ultraviolet Anomaly in NGC 5548 with X-Ray Spectroscopy

During the Space Telescope and Optical Reverberation Mapping Project observations of NGC 5548, the continuum and emission-line variability became decorrelated during the second half of the six-month-long observing campaign. Here we present Swift and Chandra X-ray spectra of NGC 5548 obtained as part of the campaign. The Swift spectra show that excess flux (relative to a power-law continuum) in the soft X-ray band appears before the start of the anomalous emission-line behavior, peaks during the period of the anomaly, and then declines. This is a model-independent result suggesting that the soft excess is related to the anomaly. We divide the Swift data into on- and off-anomaly spectra to characterize the soft excess via spectral fitting. The cause of the spectral differences is likely due to a change in the intrinsic spectrum rather than to variable obscuration or partial covering. The Chandra spectra have lower signal-to-noise ratios, but are consistent with the Swift data. Our preferred model of the soft excess is emission from an optically thick, warm Comptonizing corona, the effective optical depth of which increases during the anomaly. This model simultaneously explains all three observations: the UV emission-line flux decrease, the soft-excess increase, and the emission-line anomaly.
Mechanistic insights into longan (Dimocarpous longan Lour.) transcriptome for physiological characterization for defensive genes and differential gene expression analysis with longan embryogenic callus transcriptome

Longan is one of several subtropical and climateric fruit tree of South East Asia having economic and medicinal importance. To understand the mechanism behind altered expression of genetic variants towards various complex diseases, transcriptome analysis is pivotal in present biological scenario. Availability of transcriptomic data of longan facilitates its further functional genomics analysis, differential gene expression analysis and progressive research on the plant varieties of similar family belonging to Indian subcontinent. In the present study, a total number of 90,762,826 mixed paired end sequence reads from 7 different tissues of longan transcriptome (ID: SRR2864836) and 64,876,528 reads for longan embryogenic callus (EC) transcriptome (ID: SRR412534) were downloaded from SRA database, NCBI using SRA Tool Kit. A total number of 9,304 and 10,679 contigs (including scaffolded regions) were assembled from the longan and longan-EC clean reads. Cloud blast search was performed against multiple protein and nucleotide databases at NCBI to explore the mechanistic insights, of the longan transcriptome. A total 9,304 contigs/ putative transcripts were classified into 10 major biological processes, 30 GO functional groups, 08 various cellular components and 139 KEGG pathways. In blast analysis against Nr database, database of Arabidopsis thaliana, Zea mays and Oryza sativa 33 contigs were reported for possessing disease resistant proteins. Additionally differential gene expression analysis between longan and longan-EC transcripts showed a total of 34 genes to be highly upregulated and 26 downregulated genes. Thus our study paves way for further research to improvise and utilize its economic and medicinal characteristics of longan as reference in context to Indian plants viz. Litchi chinensis, Arytera divericata, Schleichera oleosa (Lour.) etc.
The Past, Present and Future of Diagnostic Imaging in Ovarian Cancer

Ovarian cancers (OC) include a group of diseases with variable prognoses. While most conventional imaging techniques rely on the detection of tumour burden and distant spread to identify treatment plans, more emphasis is now being placed on screening for early detection and also for more accurate staging using molecular imaging techniques. It is generally accepted that there are some incremental benefits of using serum CA125 levels coupled with cross-sectional diagnostic imaging to aid in the diagnosis, staging and treatment planning of OC. This chapter provides a review of tests and diag- nostic imaging modalities that aid in the detection and staging of OC with a particular focus on F18-Fluorodeoxyglucose positron emission tomography/computed tomog- raphy (F18-FDG PET/CT) imaging. This chapter also proposes a diagnostic algorithm for the management of ovarian cancer. F18-FDG PET/CT imaging can act as a catalyst for the development of personalised medicine by stimulating advancements in targeted therapy. In conclusion, diagnostic imaging with particular focus in molecular imaging has the potential for altering management plans, which can ultimately help improve the prognosis of ovarian cancer.
Theoretical and Practical Aspects of Implementing Automated Energy Control and Metering Systems for Commercial Accounting

The relevance and special importance of power consumption and energy-saving issues for sustainable development of energy strategy for Russia and the world community determine the need for their detailed elaboration at both theoretical and practical levels. The key factor of unsustainable costs is losses that occur during energy transportation from a supplier to a consumer. These costs will be reduced by the introduction of an automated energy control and metering systems for commercial accounting (AECMSCA) for the implementation of one-time, continuous, automatic control and organization of commercial payments between suppliers and consumers of energy. An introduction of ASCM is a prerequisite for the transition to payment of differentiated electricity rates. It is a strategic goal of improving the efficiency of country's energy potential. This article gives theoretical rationale for implementing AECMSCA for carrying out measurements, collecting, processing and storage of results of measurements, information on conditions of objects and measuring instruments, automatic transmission of information obtained to an integrated automated system of commercial accounting management at the wholesale electricity market. We characterize some practical aspects of AECMSCA implementation in the Far East of the Russian Federation, in particular, in the “South-Yakutsk electrical networks” subsidiary. The final result of the work on upgrading electricity metering systems will be a full (100 per cent) automated data collection on consumed electricity from all metering devices. In the project under consideration, the overall economic benefits due to introduction of AECMSCA will be up to 10 % of the amount of consumed energy.
Time series modeling and synchronization using neural networks

In the last few years, neural networks have found interesting applications in the field of time series modeling and forecasting. Some recent results show the ability of these models to approximate the dynamical behavior of nonlinear chaotic systems, leading to similar dimensions and Lyapunov exponents. In this paper we analyze further the dynamical properties of neural networks when comparted with chaotic systems. In particular, we show that the possibility of synchronizing chaotic systems gives a natural criterion for determining similar dynamical behavior between these systems and neural approximate models. In particular we show that a neural model obtained from an experimental scalar laser-intensity time series can be synchronized to the time series, indicating that it captures the dynamical behavior of the system underlying the data.
Automated Data-Driven Hint Generation in Intelligent Tutoring Systems for Code-Writing: On the Road of Future Research

Introductory programming is an essential part of the curriculum in any engineering discipline in universities. However, for many beginning students, it is very difficult to learn. In particular, these students often get stuck and frustrated when attempting to solve programming exercises. One way to assist beginning programmers to overcome difficulties in learning to program is to use intelligent tutoring systems (ITSs) for programming, which can provide students with personalized hints of students’ solving process in programming exercises. Currently, mostly these systems manually construct the domain models. They take much time to construct, especially for exercises with very large solution spaces. One of the major challenges associated with handling ITSs for programming comes from the diversity of possible code solutions that a student can write. The use of data-driven approaches to develop these ITSs is just starting to be explored in the field. Given that this is still a relatively new research field, many challenges are still remained unsolved. Our goal in this paper is to review and classify analysis techniques that are requested to generate data-driven hints in ITSs for programming. This work also aims equally to identify the possible future directions in this research field.
Tetracycline Accumulation in Pea Seedlings and its Effects on Proteome and Enzyme Activities

Among antibiotics, tetracyclines are the most commonly used and detected in the environment. In this study, the amount of tetracycline taken up from soil by pea seedlings was analyzed, identified its main site of accumulation in plants and determined also changes in the protein profile of pea. The study demonstrates that pea seedlings take up tetracycline from soil and transport the drug via roots to over-ground parts and then accumulate it in the youngest parts, such as upper stem and leaves. After the taken up of drug, the activity of guaiacol peroxidase is modified and changes in the profile of proteins, as determined by two-dimensional gel electrophoresis occur. The majority of proteins (∼40%) visualized possessed molecular weight between 25 and 37 kDa. Only 8% of the proteins had molecular weight lower than 20 kDa, and 2% greater than 75 kDa. The number of spots in the control samples was 194, which is less by 49 than at the concentration of 150 mg kg of soil. Isoflavone reductase was present only in seedlings growing with tetracycline. Tetracycline uptake from soil modify mainly the changes in biochemical processes connected with protein. © 2016 Friends Science Publishers
Developing an EVADE (EVAluation and DEbriefing) Method to Assess Trainees during Crisis Management Training for Major Hazards and Feedback Them

Lessons learnt from past accidents emphasize that major crisis management's limitations are mainly characterised by collective failures (organizational, behavioural and cognitive), absence and/or maladaptive training of actors (Guarnieri et al., 2015; Heiderich, 2010; Lagadec, 2012). Indeed, the training exercises have limitations such as the assessment: it focuses on the technical skills of the group, not on non-technical skills mobilized, and it is not conducted in real time. The presentation of the results during the debriefing is also incomplete (Tena-Chollet, 2012). The present work aims to present our method to assess trainees during crisis management training and feedback them, the EVADE (EVAluation and Debriefing) method. This method required the upstream creation of a typology of training objectives to be integrated into training and the identification of technical and non-technical skills of a crisis cell. The approach is based on behavioural markers which are used to identify mobilized skills of a group during exercise. The assessment tool is presented, through its construction and its functioning, and it is tested with trainees in crisis management exercises. Various examples of the results of restitution are then proposed in this paper.
The advisory brought to practice ; routine screening on depression ( and anxiety ) in coronary heart disease ; Consequences and implications

Introduction: Following the evidence, the American Heart Association recently published a Science Advisory with the recommendation that patients with Coronary Heart Disease (CHD) should be screened for depressive symptoms and depression. Also the Heart Failure Guidelines recommend routine screening for depressive symptoms. Screening for anxiety was not included in these recommendations, despite findings in literature suggesting that cardiac patients are at risk for high levels of anxiety. Objective: The aim of the current study is to obtain a realistic estimation of the consequences and implications of this advice for clinical practice. Method: Data on anxiety, and depression, need for help, demographics and disease related variables were collected in a cross-sectional study within a 2-month period (July–August 2008) at the cardiac outpatient clinic of the University Medical Center Groningen (The Netherlands). Patients: Data of 217 patients were analyzed, mean age was 58 years (±16) and 62% of the respondents were male. Results: Of 217 patients, 26% indicated to have depressive symptoms and 42% indicated elevated levels of anxiety. About 35–50% of these patients indicated a moderate to high need for help. The prevalence of anxiety and depression was mainly associated with demographic factors and the occurrence of stressful life events. Conclusion: Routine screening will put an increased demand on psychosocial diagnostics and treatment, therefore the availability of professionals should be guaranteed in advance. © 2010 European Society of Cardiology. Published by Elsevier B.V. All rights reserved.
Dynamic behavior of the coffee fruit-stem-branch system using Stochastic finite element method

The development of an efficient machine for harvesting coffee requires comprehensive knowledge of the dynamic behavior of the plant and its parts. The finite element method is a numerical approach used to determine natural frequencies and mode shapes. However, the stochastic finite element method has not been employed for the analysis of the dynamic behavior of coffee. The aim is to determine the natural frequencies and mode shapes for the coffee fruit-stem-branch system. The natural frequencies and the mode shapes were determined by employing the stochastic finite element method, in which the elastic modulus and the specific mass were treated as random variables, and the variation in the natural frequency was obtained as a function of the variability of these properties. The natural frequencies were reduced according to the evolution of the ripening process of the fruit and stem or due to the increase in the total weight of the system due to an increase in the number of fruits attached to the stem. The natural frequencies increased with an increase in the elastic modulus or with a reduction in the specific mass.
Montessori Materyallerinin Orta Düzeyde Zihinsel Yetersizliği Olan Çocukların Küçük Kas Becerilerine Etkisi

The effect of Montessori materials on fine muscle skills of five-six year-old children with moderate mental disabilities was studied in this research. The study group of the research included four children. A single-case multiple-probe-design-across-participants was used in the research. SSEIP-DSI for Children with Developmental Disabilities was used to collect data. Follow-up data were collected on the 7th, 14th, and 21st days following the teaching sessions. Follow-up sessions were completed with 100% performance for all subjects. In the generalization session, one of the subjects performed 80%, one 90% and two 100%. It can therefore be suggested that working with Montessori materials has an effect on the development of small muscle skills of children with moderate mental disability. In addition, using the semi-structured interview form, data were collected from the classroom teachers of the subjects to ensure the social validity data of the research. This collected data seem to support the findings of the research.
Effect of Stress-Response Psycho-Training on the Stress Levels of Mothers with Autistic Children.

The aim of the study was to assess the effect of stress-response psycho-training on the stress levels of mothers with autistic children. The research was experimental in design encompassing a pretest-posttest model with control and placebo groups. Participation in the study was voluntary with a total of 28 mothers of autistic children included with 10 in the experimental group, 11 in the control group and 7 in the placebo group. The Perceived Stress Scale was used as the data collection tool in the research. Stress-response psycho-training based on the cognitive-behavioral approach developed by the researcher was applied with the aim of lowering stress levels of participants in the experimental group over 9 weekly sessions. The placebo group participated in 3 sessions of group guidance activities about the causes of stress and place in life. The control group did not have any procedures applied. For statistical analysis the repeated measurements variance analysis technique was used. The stress-response psycho-training applied in the research was identified to have a significant effect in reducing the stress levels of mothers with autistic children. The obtained results are discussed within the framework of other research in the relevant literature and recommendations are made.
Scene Classification with Deep Neural Nets Using Background Suppression

Deep Learning can be a powerful tool to replace the human eyes in the field of Scene classification. In this paper, we propose scene classification for four different classes using background suppression and Convolutional Neural Network. Background suppression is achieved with luma transforms. Supervised learning is used and the processed images are fed to the four layered convolutional neural network, which would enable the system to classify the images. Background suppression seems to indicate an increase in the specificity which is very much essential for scene classification. However, with increase in layers, sensitivity of the system does increase resulting in lesser validation loss. The training and validation accuracies have shown much improvement in comparison with the convolutional neural network and several other approaches.
The "Need for Harmony" Defence Mechanisms as Co-Factor in Stress Sensitivity Producing Sadness and Depression

The aim of this investigation is to develop useful research toolsfor assessingpsychological traits and defence mechanisms towardnegative emotions. The present study examined 124 young women adults (19 - 39 years) participating in short-term stress sessions conducted with a non-invasive procedure called “Drawing Recollection” of real personal stressful life experiences (Biasi & Bonaiuto, 1997a, 1997b, 2007). This treatment lasts 20 minutes and is as effective as the heavier traditional techniques. Emotional and motivational changes are documented by pre- and post- treatment bipolar “Self-Appraisal Scales” (Biasi, Bonaiuto, & Giannini, 2010). With the LDM Inventory, the participants were selected and divided into two contrasting extreme groups, according to their very high or very low Need for Harmony (N/H) sub-scale scores. We identified favourable and unfavourable personality traits for developing specific negative emotions under stress: in particular the N/H, concerning the tendency to avoid interpersonal conflicts at the cost of self-sacrifice and self-punishment (Spielberger, 1988; Spielberger & Reheiser, 2000). Participants who obtained high “Sadness” scores under stress (measured by “Self-Appraisal Scales”), had significantly higher scores on N/H scales compared to the opposite group (p < 0.001). The N/H defence mechanism and negative emotion of “Sadness” (“Depression”) combination represents significant co-factors of stress sensitivity.