Miracle-dz/UniFAR-FTUs huggingface dataset:
Turbulent Boundary Layer Response to Active Control Actuator

It has been established that the dynamics of large-scale structures (LSS) in the outer region of turbulent boundary layers (TBL) and the near-wall small-scale turbulence are correlated. In the study reported here, a plasma-based active flow control device was placed within the TBL to introduce periodic motions into the outer region. The boundary layer Reynolds number was low enough, Reτ = 700 that no naturally occurring energetic coherent large-scale structure was present. Via actuation, a periodic synthetic large-scale structure was introduced into the TBL, and the TBL’s response to this structure in the near-wall region was studied using both hot-wire anemometry and planar PIV. In previous experiments, it was shown that this large-scale structure had a strong modulating effect on the near-wall turbulence downstream of the actuator. In this study an optimized actuator design is tested, and changes to the modulating effect are discussed. In addition, planar PIV is implemented to measure the spatially and temporally resolved two-dimensional velocity field downstream of the actuator. The PIV measurements are shown to be consistent with the hot-wire measurements and capable of capturing the synthetic LSS dynamics and their modulating effect on the near wall turbulence. Ongoing PIV work and the benefits of supplementing the original hot-wire measurements with PIV are discussed.
ON SOME APPLICATIONS OF ALGEBRAIC HYPERSTRUCTURES FOR THE MANAGEMENT OF TEACHING AND RELATIONSHIPS IN SCHOOLS

In terms of school context, the effectiveness of a teaching process frequently depends to a large extent on the relationship system, which had been formed within a classroom. This paper is going to present how algebraic hyperstructures can contribute significantly to understanding the system of relationships within a classroom. Furthermore, it becomes possible to assess the impact of interventions targeted at improving the system of relationships and thus to establish undisturbed and fundamental participation of students in the learning process.
Privacy in Paralinguistic Tasks

The widespread use of devices with internet access, together with the emerging market for data mining applications has raised concerns over the level of privacy currently given to users. Taking advantage of increasingly accurate Machine Learning algorithms, many services use sensitive data to extract information and make predictions about the characteristics of their users. Among other data types, speech stands out for the amount of information it holds. Aside from the linguistic content, from speech one can obtain other information, such as the speakers age, gender, health and personality traits. However, the reasons that make speech useful also make it a target for malicious third parties intending to obtain sensitive information about unsuspecting users. This is especially true for health-related applications where a system may try to uncover whether someone presents symptoms of a medical condition, as this information is deeply sensitive. In this thesis we show how Homomorphic Encryption can be used to build speech-based privacy-preserving Neural Networks, with focus on three speech affecting conditions: the common Cold, Depression and Parkinsons Disease. To this end, in a first experiment we apply an Encrypted Neural Network, whose operations have been replaced with their encrypted counterparts, to the three aforementioned conditions. On a second approach, we discuss and experiment on the feasibility of building an end-toend network for the same purpose. Finally, as a last experiment we show how a Neural Network, and its input features, can be discretized in order to allow the use of a Homomorphic Encryption batching technique.
Parental Education Mitigates the Rising Transmission of Income between Generations

This article provides evidence on the causal relationship between maternal education and the intergenerational transmission of income. Using a novel linkage between intergenerational income tax data and Census data for individuals born between 1963 and 1985 and their parents, we show that rank mobility has decreased over time, and that this decline was sharpest for children of mothers without a high school diploma. Using variation in compulsory schooling laws, we show that rank mobility increases as the percentage of mothers with a high school diploma increases. We find weaker evidence that mobility increases with the percentage of mothers with a university degree. JEL codes: J62, D63
BRAIN TYPE, SEX DIFFERENCES, AND MOTIVATION TO LEARN SCIENCE: A CROSS-CULTURAL STUDY

Sex is considered to be one of the most significant factors influencing attitudes towards science. However, the so-called brain type approach from cognitive science suggests that the difference in motivation to learn science does not primarily differentiate the girls from the boys, but rather the so-called systemisers from the empathizers. Boys are, on average, more motivated to learn science, not because they are boys but because boys tend to be systemizers, and vice versa for girls. Previous research on Swiss students has indeed shown full mediation between sex and motivation to learn science. The present study was conducted in order to confirm this relation in a cross-cultural study. It involved four countries (Malaysia, Slovenia, Switzerland, and Turkey) and 1200 students in upper secondary level. The study used structural equation modelling in order to test the hypothesised relationship. The results confirm the full mediation of systemizing between sex and motivation to learn science. The results are stable and the model fit is excellent. Systemizing explains 27% of the motivation to learn science. The indirect impact of sex on motivation is significant but low. The results are invariant across all four cultures. It is therefore concluded that students’ brain type, seen as a basic cognitive personal trait, is more important as a predicator for motivation to learn science than sex. It should be taken into account both in science teaching and research of science education.
Implementation Analysis of Cloud Radio Access Network Architectures in Small Cells

The main objective of this work was to analyse the performance parameters of a Cloud Radio Access Network in an already deployed LTE-A network of a mobile operator by taking advantage of the functional Remote Radio Head and Baseband Unit split, with the centralisation of the processing power in standard data centres. The work consists of the analysis of the current macro base station location and a list of the possible data centre to present a possible C-RAN deployment under different strategies and algorithms that a mobile operator may be interested in. The metrics studied are fronthaul latency, pool capacity in traffic per hour, processing power capacity and multiplexing gain. A total cost of ownership model is also presented to estimate cost savings possible with the technology. The model is implemented in a computational tool to provide a generic study of any scenario. The results obtained in the central area of Porto have proven that C-RAN implementation with 19 pools is possible without introducing latency problems. In this kind of implementation, the operator can combine different traffic profiles and achieve a multiplexing gain of up to 1.31 that can be translated in capacity savings. A cost reduction of 63 % in capital investment and 31 % in operational expenditures was predicted for a centralised deployment when compared to another green field deployment without centralisation. A futuristic approach was also added to the approach to simulate how massive small cell deployment to handle an 8-time increase in traffic affect the results.
The Role Of Enterprenuerial Orientations On Micro Small Enterprises (MSEs) Performance (Study Of Indonesia MSEs Performance in a Border Area)

The purpose of this study was to determine the effect of social capital and human capital on the performance of MSEs through entrepreneurial orientations in the Belu Regency, Indonesia. The population in this study were all MSEs in the furniture and animal husbandry sectors in Belu Regency and the number of samples in this study amounted to 250 units of MSES consisting of 2 types of furniture and animal husbandry sectors. Data analyzed using path analysis model. The reults was found, both variables (human capital and social capital), will have a greater influence on the performance of MSEs if through entrepreneurial orientation variables.
History of Past/Current of Medication Use in Severe or Destructive Bruxers: An Intragroup Comparison Study

Introduction: Severe or destructive bruxing behavior being diurnal, nocturnal or mixed is a significant problem and a challenge regarding both, restorative dentistry and pharmacological intervention. Aim:Evaluate past and current use of medication in destructive bruxers, test the hypothesis that they have a history of greater use of antidepressants and anti-anxiety medication. Methods: Clinical examination, use of self-reported questionnaires, history of chief complaint and data collection about past present use of medication in 41 subjects with both craniomandibular disorders and destructive bruxing behavior. Results: Mean of different past and or current medications reported were about 5,1 (destructive bruxers); 1,8 (mild bruxers) and 2,6 (No CMDs). Kruskal-Wallis statistics, p<0,0001: Destructive versus mild bruxers (p<0,001); destructive bruxers versus no CMDs (p<0,001); mild bruxers versus No CMDs (p>0,05). 82,9% destructive bruxers, 56,7% mild bruxers and 40% Non CMDs subjects respectively, reported past and or current use of analgesics or anti-inflammatory drugs: Chi-squared for independence p<0,0008, for trends p<0,0002. Destructive versus mild bruxers p<0,01; destructive bruxers versus Non CMDs p<0,0003; mild bruxers versus Non CMDs p=0,30. 29=70,7% destructive bruxers, 13=43,3% mild bruxers and 9=30% Non CMDs subjects reported past and or current use of muscle relaxation drugs. Chi-squared for independence p<0,002, for trends p<0,0005: destructive versus mild bruxers (p<0,02); destructive bruxers versus No CMDs (p<0,0008); mild bruxers versus No CMDs (p=0,42). 31,7% (n=13) destructive bruxers, 4=13,3% mild bruxers and 6=20% No CMDs subjects reported past or current use of antidepressants. Chi-squared for independence p=0,17, for trends p=0,19: destructive versus mild bruxers (p=0,09): destructive bruxers versus No CMDs (p=0,29): mild bruxers versus No CMDs (p=0,73). Use of anti-anxiety drugs were reported by 17,1% destructive bruxers, 0% mild bruxers and 3,3% No CMD subjects, respectively. Chi-squared for independence (p<0,01), for trends (p<0,02): Fisher ́s exact test, Destructive versus mild bruxers (p<0,01); destructive versus no CMDs (p=0,12): mild bruxers versus No CMDs (p=1,000). Conclusions: Destructive bruxers used a higher frequency o different medications to alleviate or reduce their pain, muscle tension, anxiety and depression.
Cryptosporidiosis among Patient with and without Lymphohematopoietic Malignancy in Baghdad

Patients with malignant disease are frequently affected by parasitic diseases such as cryptosporidiosis. Cryptosporidium is a parasite causing self-limited diarrhea and enteritis in healthy individuals. The prevalence and intensity of Cryptosporidium infection was studied in two groups including 30 subjects with lymphohematopoietic malignancy undergo chemotherapy and 146 non malignant subjects. Stool specimen was obtained from each case. The specimens were concentrated by the formalin-ether method and smear was prepared from each. The smears were stained by modified Ziehl-Neelsen method and were observed under a light microscope. 23 (76.66%) malignant and 22(15.06%) non-malignant patients were positive for Cryptosporidium infection. The results showed a statistically significant difference between malignant and nonmalignant groups (P<0.05). The results also showed that the intensity of Cryptosporidium infection in malignant patients was significant(P<0.05) much (higher than non-malignant patients. and this could be due to immunosuppressive therapy in these malignant patients.
Integrating Rule-based Entity Masking into Image Captioning

Given an image, generating its natural language description (i.e., caption) is a well studied problem. Approaches proposed to address this problem usually rely on image features that are diﬃcult to interpret. Particularly, these image features are subdivided into global and local features, where global features are extracted from the global representation of the image, while local features are extracted from the objects detected locally in an image. Although, local features extract rich visual information from the image, existing models generate captions in a blackbox manner and humans have diﬃculty interpreting which local objects the caption is aimed to represent. Hence in this paper, we propose a novel framework for the image captioning with an explicit object (e.g., knowledge graph entity) selection process while still maintaining its end-to-end training ability. The model ﬁrst explicitly selects which local entities to include in the caption according to a human-interpretable mask, then generate proper captions by attending to selected entities. Experiments conducted on the MSCOCO dataset demonstrate that our method achieves good performance in terms of the caption quality and diversity with a more interpretable generating process than previous counterparts.
CORRELATION BETWEEN THE WAIST CIRCUMFERENCE, DIASTOLIC BLOOD PRESSURE AND INSULIN RESISTANCE IN NON-OBESE YOUNG ADULTS.

Context The metabolic syndrome is a profound, systemic impairment of the metabolism of lipids, carbohydrates and branched amino-acids, affecting specially obese people. Recently, many studies outlined the presence of the metabolic syndrome, also in non obese persons. Objective and design To assess the relationship between insulin resistance and the cardiovascular component of the metabolic syndrome in a group of young, non obese subjects using a cross sectional study. Subjects and methods We enrolled 103 subjects with body mass index < 30 Kg/m2, without metabolic syndrome to whom fasting glucose, triglycerides, high density lipoprotein cholesterol, insulinemia, waist circumference and arterial pressure were recorded in a cross-sectional approach. Insulin resistance was evaluated using the homeostasis model assessment for insulin (HOMA-IR) index. Statistic data processing included Pearson relation and multiple regression (backward method), using the SPSS version 21 software. Results A significant relationship between waist circumference, diastolic blood pressure and HOMA-IR is found. High value of HOMA-IR (>2.6) was more frequently in men (p=0.011). The incidence of the 2 metabolic components mentioned above was higher in the high value HOMA-IR group: 33% vs. 7% in women and 50% vs. 4% in men. Multiple regression showed a strong correlation between HOMA-IR and waist circumference (p<0.001) and diastolic blood pressure (p=0.008) that was maintained inside the women group (p=0.016 and p=0.032, respectively). In men, HOMA-IR correlated with waist circumference (p=0.031). Conclusion We found a significant interdepen-dence between waist circumference, diastolic blood pressure and HOMA-IR. Based on our results, we consider that lifestyle intervention should start as soon as abnormal waist circumference is recorded.
Deep Recognition-by-Tracking in a Robot Environment

—In the past few years, the number of robots being deployed in society has been continuously increasing. Robots are coming to family houses as personal assistants in domestic tasks and entertainers (e.g. toys) as well as in elderly care, handicap assistance, and nursing centers. The new generation of service robots have now to interact with humans in uncertain environments. For this, the robot needs to localize, engage and identify the target subject. The identiﬁcation of the target could be done in different ways. Image-based face recognition is one example. It is a well-studied problem and state-of-the-art solutions achieve remarkable performance. However, most of the proposed solutions are not adapt to the robot environment. In this work, we explore a new approach to the problem of online person recognition. We present the Recognition-by-Tracking framework that uses pedestrian tracking in order to accumulate evidence about the face identities what leads to more accurate predictions.
Impact of preoperative education program on parental anxiety: A pilot project

Background: Hospitalization and surgery are stressful experiences for children and their parents. Parents are disturbed and anxious when their child is hospitalized and waiting for a surgery. Objective: To assess the impact of preoperative education program on parental anxiety. Materials and Methods: A quasi-experimental study with a time-series design was conducted in a selected hospital. Using purposive sampling technique, 12 parents of children undergoing surgery were selected as study participants and were segregated into two groups–experimental and control groups – with six participants in each group. The experimental group received preoperative education program, whereas the control group received routine care. Parental anxiety was measured using state trait anxiety inventory on admission, prior to shifting the child to the operation theatre (OT), 6 h, 24 h, and 48 h after the surgery, respectively. Results: The mean anxiety score of parents were less in the experimental group compared to the control group after the intervention. A significant change was observed in the mean score of parental anxiety over the period of time in the experimental group (F(4,20)= 58.628, P = 0.001). The calculated t-value was significant at the time points, that is, from admission to prior to shifting the child to the OT (P = 0.001), from admission to 6 h after the surgery (P = 0.000), from admission to 24 h after the surgery (P = 0.001), and from admission to 48 h after the surgery (P = 0.004) between the groups. Conclusion: The preoperative education program has shown to be effective in reducing parental anxiety and can be effectively used in pediatric surgical units to support the parents.
Route Alternating Multipath AODV

— This paper addresses the problem of multipath routing in MANET networks. The multipath routing enables the construction and the use of multiple paths to route traffic between a pair of source and destination nodes. It has advantages such as fault tolerance, uniform load distribution across the network, aggregate bandwidth and QoS improvement in indicators such as throughput, delay and loss. In this context, we propose the Route Alternating Multipath AODV protocol (RAM-AODV) to make the multipath routing with minimal overhead. The protocol allows us to limit the maximum number of paths to be determined and performs maintenance of those. The protocol is evaluated through simulations in Network Simulator 3 (NS-3), showing that it is a promising solution for MANET networks.
Coordinated Engagements

We study the nature of and outcomes from coordinated engagements by a prominent international network of long-term shareholders cooperating to influence firms on environmental and social issues. A two-tier engagement strategy, combining lead investors with supporting investors, is effective in successfully achieving the stated engagement goals and is followed by improved target performance. An investor is more likely to lead the collaborative dialogue when the investor’s stake in and exposure to the target firm are higher, and when the target is domestic. Success rates are elevated when lead investors are domestic, and when the investor coalition is capable and influential.
A Convergent Reactive Collision Avoidance Approach using Fast Marching Methods

—This work presents a novel way of using Fast Marching Methods for reactive collision avoidance. A new controller is proposed, proving convergence to the goal position as well as convergence of the path to the gradient lines of the navigation function. In addition, proof of obstacle avoidance is also shown, taking into account the robot’s dynamic and kinematic constraints. It is assumed the robot is using a distance measuring sensor and an implementation is made such that the robot is aware of its visibility limits. To the best of our knowledge, this is the ﬁrst convergent solution to guarantee obstacle avoidance not only in a pre-established map, but also in dynamic environments, where new static obstacles may appear. When compared to a convergent Dynamic Window Approach implementation, this controller shows improved stability, with no oscillations near obstacles and narrow passages.
ON EXTREMAL PROBLEMS IN BMOA TYPE ANALYTIC SPACES IN BOUNDED STRONGLY PSEUDOCONVEX DOMAINS WITH SMOOTH BOUNDARY AND IN TUBULAR DOMAINS OVER SYMMETRIC CONES

We provide some new sharp results on extremal problems in new BMOA type spaces in the unit disk and then in bounded pseudoconvex domains with smooth boundary and tubular domains over symmetric cones using so called double Bergman representation formula. These generalize a known one dimensional result to higher dimension in various directions. 2010 Mathematics Subject Classification: Primary 32A10, Secondary 32A07.
Development of a Hill-Type Muscle Model With Fatigue for the Calculation of the Redundant Muscle Forces using Multibody Dynamics

The aim of this work is to develop a versatile muscle model and robustly implement it in an existent multibody system dynamics code with natural coordinates. Two different models are included: the first is a Hill-type muscle model that simulates the functioning of the contractile structures both in forward and in inverse dynamic analysis; the second is a dynamic muscular fatigue model that considers the force production history of each muscle and estimates its fitness level using a threecompartment theory approach and a physiological muscle recruitment hierarchy. The existent equations of motion formulation is rearranged to include the referred models using the Newton’s method approach. This allows, in a forward dynamics perspective, for the calculation of the system’s motion that results from a pattern of given muscle activations, or, in an inverse dynamics perspective, for the computation of the muscle activations that are required to produce a prescribed articular movement. In both perspectives the system presents a redundant nature that is overcome in the latter case using an SQP optimization algorithm. The methodologies and models are applied to several case studies to evaluate their robustness and accuracy. An upper extremity model with seven muscles is designed to evidence the effectiveness of the implementation of a muscle fatigue model in a multibody system. A second model, encompassing the lower extremity musculoskeletal apparatus with twelve muscles, is proposed for the exclusive calculation of muscle activations. The results are presented and conclusions are discussed. The work concludes with a perspective of possible future developments.