Miracle-dz/UniFAR-FTUs huggingface dataset:
Building technology entrepreneurship capabilities, an engineering education perspective

entrepreneurship process. The intense use of these facilities in the educational programs aim to modify the self-efficacy perception of the students regarding the entrepreneurial behavior. The aim of this paper is to provide illustrative examples that can be used as a guide to propose alternative paths to activate technology entrepreneurship. The cases of the engineering programs at two European universities are used to identify the common and specific elements that configure a response to the societal demands to the universities.
Pulmonary hemodynamics in patients with severe COPD

Worsening gas exchange during exercise and exacerbation in COPD contributes to systemic hypoxemia and restricts the quality of life. However, pulmonary hemodynamics under such conditions are not well understood. We performed right heart catheterization in six patients with severe COPD (%FEV1 < 50%) during rest, exercise and exacerbation. Pulmonary artery pressure (Ppa) was a little elevated at rest. The Ppa, as pulmonary artery wedge pressure (Pawp) and cardiac index were significantly increased during bicycle ergometer exercise. In contrast, pulmonary vascular resistance significantly increased during exacerbation accompanied by a slightly increased Ppa. Supplemental oxygen resulted in significant decreases in Ppa and Pawp during exercise and Ppa during exacerbation. These findings suggested that the pathological pulmonary hemodynamics are characterized by significant pulmonary hypertension due to dynamic hyperinflation during exercise and a prominent vasoconstrictive reaction under exacerbation. The principal pathophysiology of the pulmonary circulation between exercise and exacerbation might differ in severe COPD. Supplemental oxygen is beneficial in these situations as reflected by improved pathological pulmonary hypertension.
An Unobtrusive Method for Tracking Network Latency in Online Games

Online games are a very important class of distributed interactive applications. Their success is heavily dependant on the level of consistency that can be maintained between participants communicating in the virtual world. Achieving a high level of consistency usually involves the transmission of a large amount of network traffic. However, if the underlying network connecting participants is unable to process this traffic, then network latency will increase, which will in turn negatively impact on consistency. Many schemes exist which attempt to reduce network traffic, and thus reduce the effect of network latency on the interactive application. However, applications that employ these schemes tend to do so with little knowledge of the underlying network conditions, and assume a worst-case scenario of limited bandwidth. Such an assumption can actually cause these latency reduction schemes to perform sub-optimally, and ironically introduce more inconsistency than they reduce. Hence, it is important that online game applications become aware of network conditions, such as available bandwidth. Existing methods of estimating bandwidth operate by analysing trends in one-way latency, and require that extra data be transmitted between nodes in order to capture the latency trends. Such an approach does not suit online games, as the extra data requirements could increase network latency, and affect the ability of the application to scale to multiple participants. To deal with this issue, this paper proposes a method by which online games can unobtrusively track one-way network latency. This method requires no time-stamping information to be transmitted between participants and operates using data already being transmitted as part of the online game application, meaning that its impact on the network is minimal. NS2 simulations demonstrate that the trends collected by this method can be used to estimate bandwidth under certain conditions.
Augmenting Input Method Language Model with user Location Type Information

Geo-tags from micro-blog posts have been shown to be useful in many data mining applications. This work seeks to find out if the location type derived from these geo-tags can benefit input methods, which attempts to predict the next word a user will input during typing. If a correlation between different location types and a change in word distribution can be found, the location type information can be used to make the input method more accurate. This work queried micro-blog posts from Twitter API and location type of these posts from Google Place API, forming a dataset of around 500k samples. A statistical study on the word distribution found weak support for the assumption. An LSTM based prediction experiment found a 2% edge in the accuracy from language models leveraging location type information when compared to a baseline without that information.
Protein nitration in barley during the defense response against Blumeria graminis f.sp. hordei.

Nitric oxide (NO) affects cell signaling through a wide range of actions. One involves tyrosinenitration, a process by which a nitrite group is added to the ortho-position of Tyr residues forming 3-nitrotyrosine, which may alter protein conformation, structure and catalytic activity. Our research focuses on mechanisms of resistance in barley (Hordeum vulgare) to Blumeria graminis, a biotrophic fungal pathogen that infects epidermal cells. We here show evidence indicating in vivo nitration of proteins in epidermal cells during the defense response. For experiments, we used four different genotypes, Pallas and its near isogenic line P01 carrying the Mla1 conditioning hypersensitive response and the susceptible barley genotype Riso-S and its near isogenic line Riso-R carrying the mlo5 related with papillae formation. Detection of nitrated proteins was carried out by Western Blot assays where proteins were separated by 2-dimensional electrophoresis using isoelectric focusing (IEF) in (3-10) non-lineal pH and SDS-PAGE 10 % polyacrylamide gels. Afterwards, proteins were transfer to nitrocellulose membranes and incubation was carried out with anti-nitro-tyrosine antibodies. Our results show nitration of specific proteins during the defense response in both P01 and Riso-R genotypes that do not appear in the susceptible genotypes nor in the non-inoculated controls.
Evaluation of Pozzolanic Reactivity of Artificial Pozzolans

Pozzolanicity is a very interesting issue regarding building materials, as a way to enhance mortars and concrete durability. This property results from the reaction between calcium hydroxide and silica and alumina based materials. Different types of natural and artificial pozzolans show pozzolanic activities that differ depending on the materials characteristics. Therefore, the study of this property, namely its reactivity with calcium hydroxide, reveals itself to be important in the selection of the type and content of these materials. This paper presents the results of several pozzolanic reactivity methods, applied to different pozzolanic materials. The selected pozzolanic methods include Chapelle method, Fratinni method and Strength Activity Index. Those tests have been applied to evaluate the reactivity of various kinds of artificial pozzolans. The correlation between the test methods are presented and discussed.
Establishing a Language by Annotating a Corpus

In this paper, we show that building a treebank can be used as a way to establish a language. Annotated corpus can be used as tools when arguing that some linguistic data belongs to a separate language (rather than a dialect or variety of another established language). We provide here a case study on a treebank of Naija, a Post-creole spoken in Nigeria which presents us with significant differences from treebanks of English in terms of existing constructions and frequency of several syntactic units.
Traffic Sign Detection on GPU using Color Shape Regular Expressions

Regular expression matching on GPU is state-of-the-art technique for the processing of a huge amount of the text information, for example, in network activity analyzers and intrusion prevention systems. This paper proposes a fast and robust algorithm for traffic sign detection, which is based on color shape regular expressions matching through the image pixels. We consider a fast massively-parallel GPU implementation of the color shape regular expression, using deterministic finite automaton and special case of non-deterministic finite automaton. The performance of the proposed localization algorithm is compared with the Hough transform, which is commonly used for traffic sign recognition.
A reflection on the first 50 years of Water Resources Research

The year 2015 marks the 50th anniversary of Water Resources Research (WRR), which was founded in 1965. More than 15,000 papers have been published in WRR since its inception, and these papers have been cited more than 430,000 times. The history of hydrology and the water sciences are also reflected in WRR, which has served as a premier publication outlet and instigator of scientific growth over the last 50 years. The legacy of WRR provides a strong scientific foundation for the hydrology community to rise to the challenges of sustainable water resources management in a future where dramatic environmental change and increasing human population are expected to stress the world's water resources from local to global scales.
State-space Modelling and Digital Controller Design for DC-DC Converter

The recent development in digital technology offers better platform for easy implementation of advance control algorithm in power converter design making digital control a viable alternative to analogue counterpart. Controller design for power converters has been very challenging due to non-linear characteristics of power switches, the supply voltage variability, load current changes and circuit element variation. This paper presents dynamic averaged state-space modelling of non-ideal dc-dc boost converter with parasitic and digital controller design for boost converter using digital redesign and direct digital design methods. The system was simulated in Matlab/Simulink to investigate the dynamic performance of the two controllers’ transient response, control bandwidth and response to variable supply voltage. The results demonstrated fast transient and wide control bandwidth for tight voltage regulation of variable input voltage.
Relationships between roost preferences, ectoparasite density, and grooming behaviour of neotropical bats

Evidence suggests that behavioural defences, such as habitat selection and grooming behaviour, have evolved in animals in response to the costs associated with ectoparasites. Bat fly and mite densities were compared among wild-caught bats in Belize with different roosting preferences (cavity, foliage, or both), and grooming behaviour was analysed for bat species with high and low ectoparasite density. Ectoparasites of bats were removed using forceps, and bat grooming behaviour was recorded with a camcorder. Because bat flies pupate on the surface of host roosts, bats that use cavity roosts (a sheltered environment for the pupae) were predicted to have higher densities of bat flies than those that use foliage (exposed environment). Cavity-roosting species generally had higher densities of bat flies and mites, although the relationship was more evident for bat flies. The grooming behaviour of bats was predicted to differ among species with high or low ectoparasite densities. Although there was no difference in the frequency of grooming behaviours for individuals with and without bat flies, there were differences in grooming behaviour at the species level. Bat species with high ectoparasite densities scratched more than those with low ectoparasite densities. These results suggest that ectoparasite densities and grooming behaviour are related to roosting preferences in bats.
From Deep Learning to Episodic Memories: Creating Categories of Visual Experiences

This paper presents a cognitively inspired approach for visual scene categorization and abstraction. Our approach uses first-person video from real, dynamic environments to create episode-like memories of video scenes. Videos from newly encountered environments can then be matched to previous episodes and used for prediction. Our process utilizes the final layer of a convolutional neural network (CNN) as a high-level, scene-specific representation which is robust enough to noise to be used with wearable cameras. Inspired by results from cognitive science and neuroscience, we use output maps created by a CNN as a sparse, abstract representation of visual images. These output maps characterize a visual scene in terms of the spatial and temporal distribution of objects in the scene. The system is demonstrated on video taken using Google Glass. When compared with human evaluations the system correctly matches 70% of scene segments. Finally, high-level scene prediction is demonstrated by showing that the system can match scenes using only a few initial segments and can then predict the objects that will appear in the near future. Empirically, object predictions based on the initial scene segments resulted in a 95% match.
Comorbidity: A network perspective

Abstract The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory, in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a radically different conceptualization in terms of a network approach, where comorbidity is hypothesized to arise from direct relations between symptoms of multiple disorders. We propose a method to visualize comorbidity networks and, based on an empirical network for major depression and generalized anxiety, we argue that this approach generates realistic hypotheses about pathways to comorbidity, overlapping symptoms, and diagnostic boundaries, that are not naturally accommodated by latent variable models: Some pathways to comorbidity through the symptom space are more likely than others; those pathways generally have the same direction (i.e., from symptoms of one disorder to symptoms of the other); overlapping symptoms play an important role in comorbidity; and boundaries between diagnostic categories are necessarily fuzzy.
Quantifying the regeneration of bone tissue in biomedical images via Legendre moments

We investigate the use of Legendre moments as biomarkers for an efficient and accurate classification of bone tissue on images coming from stem cell regeneration studies. Regions of either existing bone, cartilage or new bone-forming cells are characterized at tile level to quantify the degree of bone regeneration depending on culture conditions. Legendre moments are analyzed from three different perspectives: (1) their discriminant properties in a wide set of preselected vectors of features based on our clinical and computational experience, providing solutions whose accuracy exceeds 90%. (2) the amount of information to be retained when using Principal Component Analysis (PCA) to reduce the dimensionality of the problem from 2 to 6 dimensions. (3) the use of the (α-β)-k-feature set problem to identify a k = 4 number of features which are more relevant to our analysis from a combinatorial optimization approach. These techniques are compared in terms of computational complexity and classification accuracy to assess the strengths and limitations of the use of Legendre moments for this biomedical image processing application.
Inspiratory muscle training in obstructive lung disease

Key points Dyspnoea is influenced by inspiratory muscle strength and the load placed upon the inspiratory muscles. Dynamic hyperinflation is a major cause of dyspnoea and exercise intolerance in patients with expiratory flow limitation due to its detrimental effect upon inspiratory muscle loading. Specific IMT improves inspiratory muscle strength, reduces dyspnoea and improves exercise tolerance, even in individuals without inspiratory muscle weakness or hyperinflation. Pressure threshold IMT is the most reliable, convenient and commonly used method of IMT, eliciting improvements in a wide range of muscle functional characteristics, including strength, shortening velocity, power and endurance. Inspiratory muscles adhere to the same training principles as other skeletal muscles, with respect to overload, specificity and reversibility. Training loads must exceed 30% of inspiratory muscle strength, with at least once daily training and weekly increases in training load. Programmes should be least 6 weeks in duration, after which frequency can be reduced to two sessions, three times per week. IMT can be implemented as a stand-alone intervention or as part of a comprehensive programme of rehabilitation. Monitored outcomes should include inspiratory muscle strength, an index of dyspnoea (e.g. BDI/TDI and/or Borg CR-10) and exercise tolerance (e.g. 6MWD). Educational aims To provide an overview of the role of respiratory muscle function in the genesis of dyspnoea. To describe the response of inspiratory muscles to different types of training stimuli. To offer guidance on the implementation and monitoring of IMT. Summary Dyspnoea is strongly influenced by respiratory muscle function. Patients with obstructive lung disease become hyperinflated and experience an associated functional deficit in inspiratory muscle function, as well as a concomitant increase in the work of breathing. These changes result in a heightened sense of respiratory effort and a propensity for inspiratory muscle fatigue. There is now convincing evidence that specific inspiratory muscle training (IMT) improves respiratory muscle function, reduces dyspnoea and improves exercise tolerance. This review will describe the two most commonly implemented methods of IMT, and the specific functional adaptations that are elicited by each. It will also describe successful, evidence-based implementation and monitoring of the most commonly used method of IMT.
Adaptive Control Of Flexible Spacecraft Using TwoReference Models

A new form of adaptive attitude control system is developed for spacecraft comprising attitude sensors and torque actuators collocated on a rigid centrebody having attached flexible appendages with negligible natural damping, the dynamics parameters and order being unknown. Better overall active modal damping is achieved than attainable with conventional fixed-gain PD controllers. This initial investigation focusses on single-axis control without inter-axis coupling. First, the method of local replacement of characteristic polynomials is employed to determine, using the root locus, the derivative feedback gain of a PD controller yielding the maximum damping of each mode separately, the proportional gain being fixed. Considerable gain adjustment from mode to mode is found to be necessary, leading to the development of an adaptive control law. This is based on the novel use of two reference models to estimate separately the level of flexural motion and the mean pointing error This information is used to continuously adjust the derivative feedback gain. The simulation results, which include realistic first order sensor and actuator lags, demonstrate a much improved performance over a fixed-gain controller
Exocrine pancreas development and trypsin expression in cultured European sea bass (Dicentrarchus labrax) larvae.

The ontogenesis and formation stages of exocrine pancreas in European sea bass (D. labrax) larvae were investigated from hatching to 40 days after hatching (DAH). Histological and enzymatical techniques were used to explain the functional development of the pancreas in D. labrax with the expression of trypsinogen activity. The incipient pancreas appeared as a lamination of the dorsal wall of the digestive tract. It was observed that the primary visible indication of exocrine cell differentiation was polarization. The first zymogen granules and pancreas with exocrine polyhedral cells appeared on 6 DAH and became abundant as a compact structure located dorsal and slightly posterior to the liver. At the same time, firstly, anus and then mouth were opened, and total lengths of larvae were determined as 3.47±0.26 mm. Until larval metamorphosis, the pancreas became diffuse, spreading throughout the mesentery enclosure, the stomach, the upper intestine and the pyloric caeca. On the other hand, zymogen granules were more numerous and larger, and a greater quantity of material was carried by the ducts, indicating an increased cellular activity. The specific activity of trypsin was determined as early as after hatching (42.54±6.8 mU/mg protein-1) at 4.28±0.2 mm total length of larvae and increased immediately during the following days especially after exogenous feeding. The highest tryptic activity was detected on 30 DAH as 122.45±11.76 mU/mg protein-1. It is concluded that exocrine pancreas organogenesis is the main critical step of the zymogen granules and trypsin activity is present as early as after hatching and continuously increasing with larval period of D. labrax.
Impedance estimation of a finite absorber based on spherical array measurements

A method to characterize the surface impedance of materials is presented. The estimation is based on pressure measurements with a spherical microphone array. These measurements are used to reconstruct the sound pressure and particle velocity on the sample’s surface, from which the material’s impedance is inferred. The accuracy of the reconstruction is improved by using compressive sensing, where the wave field is represented with only a few components, ideally an incident and a reflected wave. However, at low frequencies, diffraction from the edges contributes considerably to the sound field. This leads to a deterioration of the impedance estimation, which is clearly visible in initial experimental results. The proposed methodology makes it possible to characterize the edge effect, and subsequently compensate for it in the processing, emulating measurements on an infinite sample.
The Efficacy of Oral Chlorhexidine as an Oral Hygiene Measure in Reducing the Incidence of Ventilator-Associated Pneumonia : Integrative Review

Implementation of standardised oral hygiene protocols could potentially minimise the occurrence of ventilatorassociated pneumonia (VAP) among critically ill patients. However, inclusion of the topical application of oral chlorhexidine as an effective oral antiseptic in such protocols and VAP guidelines remains controversial and questionable, due to inconstancy in the current evidential findings. The aim is to investigate the efficacy of oral chlorhexidine in reducing the incidence of VAP among mechanically ventilated patients in different critical care settings. A comprehensive electronic and manual literature search was conducted utilising different databases, including Cinahl, Medline, PubMed, Google Scholar and Scopus, and using related keywords to identify the relevant primary research sources published in English since 2005. Data were extracted and summarised in tables and then were critically appraised using validated tools. When the relevant studies were analysed, they were grouped based on two main themes and varied subthemes. One of these is the patient population, including those admitted to mixed or general ICU and those who had undergone cardiac surgery. The second theme is the chlorhexidine type, in which solution and gel were investigated at varied concentration using different frequencies. Topical application of chlorhexidine may have the potential benefit of reducing VAP incidence; however, no recommendation can be made regarding the best type or optimal concentration that can be used. Thus, a large-scale randomised control trial to investigate further the effectiveness of its routine use among mixed ICU patients and to demonstrate the optimal form, as well as concentration and frequency, is required.