Miracle-dz/UniFAR-FTUs huggingface dataset:
Strongly dense representations of surface groups.

The notion of a strongly dense subgroup was introduced by Breuillard, Green, Guralnick and Tao: a subgroup Γ of a semi-simple Q algebraic group G is called strongly dense if every pair of non-commuting elements generate a Zariski dense subgroup. Amongst other things Breuillard et alii prove that there exist strongly dense free subgroups in G ( R ), and ask whether or not a Zariski dense subgroup of G ( R ) always contains a strongly dense free subgroup. In this paper we answer this for many surface subgroups of SL(3 , R ).
REAL-WORLD DESIGN TEAM ACTIVITY: WHAT IS POETRY FOR?

Shared understanding is often the ultimate goal driving any communication exchange. In an industry-based context where multi-disciplinary design teams are commercially employed to deliver timely and concrete outcomes, establishing a common understanding amongst team members is imperative for achieving the deliver timely and concrete outcomes. One of the challenges faced by Multi-disciplinary design teams is the clear communication of discipline-specific information to colleagues who may not share the same technical or procedural frame of reference. It is not uncommon for senders of expert-specific messages to find that intended recipients do not comprehend the message’s original meaning. In such instances where a message fails to create common knowledge, a sender might choose to renew and re-communicate it by employing language from another domain as a strategy for generating greater clarity and alignment amongst team members. In this negotiated understanding, technical language may be replaced by figurative or poetic language as a way of overcoming previous gaps in transmission and comprehension of design thinking. While linguistic concepts such as analogy and metaphor are often associated with literary domains, this paper explores the ways in which messages that were previously constrained by the precision of technical terminology might be transformed into a more effective medium by the use of connotative and creative language in design contexts.
In vitro evaluation of anti-schistosomal properties of diethyledithiocarbamate sodium salt loaded with chitosan- nanoparticles

Biologically active agents show several biomedical applications. Non-chitosan loaded diethyldithiocarbamate (DDC) was previously found to have anti-schistosomal activity. The present work aimed to prepare DDC-Chitosan-Na-nanoparticles (DDC-Chitosan-NaNPs), and to investigate it’s in vitro anti-schistosomal activity with slow release approach and as well as its mortality % against both concentrations and exposure time. NPs were prepared by suspension cross linking method, in which 0.16 g chitosan were dissolved in 16 ml 2% acetic acid solution (ratio 1% wt/v.). Then after, 0.1g DDC-Na salt was added to the chitosan solution and 3.2 ml of glutaraldehyde as a cross linking agent was added into the mixture dropwise. NPs were washed several times with ethanol 70%, dried under vacuum, prepared for chemical characterization and biological assessment. Our data showed that the slow release of DDC-chitosan-NPs resulted in mortality effects on Schistosomal worms in vitro when applied with small dose for longer time. These data compared to those of prazoquantil (PZQ) as a reference drug showed that administration of DDC loaded with chitosan-NPs was more effective on the mortality of Schistosoma worms. In conclusion, DDC-Chitosan-NPs have lethal effects on S. mansoni worms in vitro by a unique mode of action in a way of concentration and exposure time dependent. Also we recommend that the development of DDC as a local, cheaper and more effective agent against S. mansoni worms. Article history: Received: Jun 1, 2019 Revised: Jul 4, 2019 Accepted: Aug 10, 2019
Botnet: Evolution, Life Cycle, Architecture and Detection Techniques

Botnet has become thorn for the Internet and the cyber security. Botnets are network of zombies controlled by botherder for their malicious and nefarious activities. These activities include distributed denial of service (DDoS) attack, click fraud, phishing, spamming, malware dissemination, traffic sniffing etc. The botnets are capable of bringing down the whole network within seconds. A number of techniques have been developed to detect the botnet and dismantle them but attackers have shown that they are always ahead of these detection techniques. This paper discusses the evolution of botnet, life cycle of botnet, its architecture and detection techniques. There are numerous detection techniques proposed by researchers that are reviewed on the basis of various parameters in this work. In spite of having such vast amount of detection techniques botnet can’t be tackled because of the dynamic nature of the Internet. The war against botnet can be seen as cat and mouse which is never-ending.
Multi-Stage Classier Design

In many classication systems, sensing modalities have dierent acquisition costs. It is often unnecessary to use every modality to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where the full data is available for training, but for a test example, measurements in a new modality can be acquired at each stage for an additional cost. We seek decision rules to reduce the average measurement acquisition cost. We formulate an empirical risk minimization problem (ERM) for a multi-stage reject classier, wherein the stage k classier either classies a sample using only the measurements acquired so far or rejects it to the next stage where more attributes can be acquired for a cost. To solve the ERM problem, we factorize the cost function into classication and rejection decisions. We then transform reject decisions into a binary classication problem. We construct stage-by-stage global surrogate risk, develop an iterative algorithm in the boosting framework and present convergence results. We test our work on synthetic, medical and explosives detection datasets. Our results demonstrate that substantial cost reduction without a signicant sacrice in accuracy is achievable.
Microwire sensors based on optical fibre tapers

This dissertation explores the study and development of fiber optic devices based on tapers. The main objective is to understand the tapers’ behavior when subjected to mechanical stress. Initially, a brief synthesis of the advances in the area of fiber sensors based on this technology is performed, including aspects related to taper profiles, fabrication, and the theoretical model of taper strain distribution. The dissertation can be divided into two scientific parts. The first part is the application of two sensors based on conventional fibers, one using a singlemode-multimode-singlemode fiber structure and the other using long period gratings. Intermodal interference is the basis of the first structure. A taper is fabricated in the multimode region in order to obtain a reduction in the number of guided modes. The second structure consists of a long period grating written in a taper. These two types of sensors are characterized in strain and temperature. The second part of the dissertation is dedicated to the study of tapers in microstructured optical fibers, specifically in suspended core fibers. Two fibers with different geometry, namely with a suspended core of three or four holes, are studied. The first fiber has a high birefringence due to its triangular geometry and the second one is multimode due to the size of its core and the index difference between core and air cladding. Initially some modal simulations are performed for each geometry. While the triangular-core fiber is studied in a fiber loop mirror configuration, the other is analyzed in transmission as an intermodal interferometer. Obtaining nanometric cores by fabricating tapers in microstructured optical fibers is achieved. Both sensors are characterized in strain and temperature. Some suggestions of future lines of investigation about sensor technology based on tapers are presented.
Active pro-vaccine and anti-vaccine groups: Their group identities and attitudes toward science

Vaccine rejection is a problem severely impacting the global society, especially considering the COVID-19 outbreak. The need to understand the psychological mechanisms underlying the active involvement of the pro-vaccine and anti-vaccine movements is therefore very important both from a theoretical and practical perspective. This paper investigates the group identities of people with positive and negative attitudes towards vaccination, and their attitudes toward general science. A targeted sample study of 192 pro-vaccine and 156 anti-vaccine group members showed that the group identity of pro-vaccine individuals is higher than of anti-vaccine individuals. and that both pro-vaccine and anti-vaccine individuals had a positive attitude toward science. Results are discussed in context of the heterogeneity of motivations causing vaccine rejection and the relation between active involvement in online discussion and group identity.
Compact substrate integrated waveguide filter using dual‐plane resonant cells

A dual‐plane resonant cell wideband bandpass filter is proposed and designed on substrate integrated waveguide (SIW) cavities using U‐shape slots and H‐shape fractal defected ground structure (DGS). The U‐shape slots etched on the top meta layer of the SIW cavity are used to constitute a multiple‐mode resonator and the H‐shape fractal DGS etched on the bottom metal layer can greatly improve the filter performance while keeping the overall size of the filter circuit to be much compact. The proposed filter can lead to a size reduction of approximately one‐third compared with the traditional SIW filters only using U‐shape slots on the top metal plate of the SIW cavity. The filter has been fabricated and experimentally measured. The measured data are in good agreement with the simulated results. The measured 3 dB bandwidth is from 7.15 to 11.25 GHz, representing a fractional bandwidth of 44.6% at a center frequency of 9.2 GHz. Within the passband, the measured return loss performance is quite good (below −22dB), and the insertion loss is measured to be 1.05 dB, including the loss from two SMA connectors. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:111–114, 2016
Estimated incidence and case fatality rate of traumatic brain injury among children (0–18 years) in Sub-Saharan Africa. A systematic review and meta-analysis

Introduction Studies from Sub-Saharan Africa (SSA) countries have reported on the incidence and case fatality rate of children with Traumatic Brain Injury (TBI). However, there is lack of a general epidemiologic description of the phenomenon in this sub-region underpinning the need for an accurate and reliable estimate of incidence and outcome of children (0–18 years) with TBI. This study therefore, extensively reviewed data to reliably estimate incidence, case fatality rate of children with TBI and its mechanism of injury in SSA. Methods Electronic databases were systematically searched in English via Medline (PubMed), Google Scholar, and Africa Journal Online (AJOL). Two independent authors performed an initial screening of studies based on the details found in their titles and abstracts. Studies were assessed for quality/risk of bias using the modified Newcastle-Ottawa Scale (NOS). The pooled case fatality rate and incidence were estimated using DerSimonian and Laird random-effects model (REM). A sub-group and sensitivity analyses were performed. Publication bias was checked by the funnel plot and Egger’s test. Furthermore, trim and fill analysis was used to adjust for publication bias using Duval and Tweedie’s method. Results Thirteen (13) hospital-based articles involving a total of 40685 participants met the inclusion criteria. The pooled case fatality rate for all the included studies in SSA was 8.0%; [95% CI: 3.0%-13.0%], and the approximate case fatality rate was adjusted to 8.2%, [95% CI:3.4%-13.0%], after the trim-and-fill analysis was used to correct for publication bias. A sub-group analysis of sub-region revealed that case fatality rate was 8% [95% CI: 2.0%-13.0%] in East Africa, 1.0% [95% CI: 0.1% -3.0%] in Southern Africa and 18.0% [95% CI: 6.0%-29.0%] in west Africa. The pooled incidence proportion of TBI was 18% [95% CI: 2.0%-33.0%]. The current review showed that Road Traffic Accident (RTA) was the predominant cause of children’s TBI in SSA. It ranged from 19.1% in South Africa to 79.1% in Togo. Conclusion TBI affects 18% of children aged 0 to 18 years, with almost one-tenth dying in SSA. The most common causes of TBI among this population in SSA were RTA and falls. TBI incidence and case fatality rate of people aged 0–18 years could be significantly reduced if novel policies focusing on reducing RTA and falls are introduced and implemented in SSA.
Detailed analysis of Ethereum network on transaction behavior, community structure and link prediction

Ethereum, the second-largest cryptocurrency after Bitcoin, has attracted wide attention in the last few years and accumulated significant transaction records. However, the underlying Ethereum network structure is still relatively unexplored. Also, very few attempts have been made to perform link predictability on the Ethereum transactions network. This paper presents a Detailed Analysis of the Ethereum Network on Transaction Behavior, Community Structure, and Link Prediction (DANET) framework to investigate various valuable aspects of the Ethereum network. Specifically, we explore the change in wealth distribution and accumulation on Ethereum Featured Transactional Network (EFTN) and further study its community structure. We further hunt for a suitable link predictability model on EFTN by employing state-of-the-art Variational Graph Auto-Encoders. The link prediction experimental results demonstrate the superiority of outstanding prediction accuracy on Ethereum networks. Moreover, the statistic usages of the Ethereum network are visualized and summarized through the experiments allowing us to formulate conjectures on the current use of this technology and future development.
Novel loss functions for ensemble-based medical image classification

Medical images commonly exhibit multiple abnormalities. Predicting them requires multi-class classifiers whose training and desired reliable performance can be affected by a combination of factors, such as, dataset size, data source, distribution, and the loss function used to train deep neural networks. Currently, the cross-entropy loss remains the de-facto loss function for training deep learning classifiers. This loss function, however, asserts equal learning from all classes, leading to a bias toward the majority class. Although the choice of the loss function impacts model performance, to the best of our knowledge, we observed that no literature exists that performs a comprehensive analysis and selection of an appropriate loss function toward the classification task under study. In this work, we benchmark various state-of-the-art loss functions, critically analyze model performance, and propose improved loss functions for a multi-class classification task. We select a pediatric chest X-ray (CXR) dataset that includes images with no abnormality (normal), and those exhibiting manifestations consistent with bacterial and viral pneumonia. We construct prediction-level and model-level ensembles to improve classification performance. Our results show that compared to the individual models and the state-of-the-art literature, the weighted averaging of the predictions for top-3 and top-5 model-level ensembles delivered significantly superior classification performance (p < 0.05) in terms of MCC (0.9068, 95% confidence interval (0.8839, 0.9297)) metric. Finally, we performed localization studies to interpret model behavior and confirm that the individual models and ensembles learned task-specific features and highlighted disease-specific regions of interest. The code is available at https://github.com/sivaramakrishnan-rajaraman/multiloss_ensemble_models.
Cultural differences in social support seeking: The mediating role of empathic concern

Prior research has found that East Asians are less willing than Westerners to seek social support in times of need. What factors account for this cultural difference? Whereas previous research has examined the mediating effect of relational concern, we predicted that empathic concern, which refers to feeling sympathy and concern for people in need and varies by individuals from different cultures, would promote support seeking. We tested the prediction in two studies. In Study 1, European Canadians reported higher empathic concern and a higher frequency of support seeking, compared to the Japanese participants. As predicted, cultural differences in social support seeking were influenced by empathic concern. In Study 2, both empathic concern and relational concern mediated cultural differences in support seeking. Japanese with lower empathic concern but higher relational concern were more reluctant than European Americans to seek social support during stressful times. Finally, loneliness, which was more prevalent among the Japanese than among the European Americans, was partially explained by social support seeking.
Roadblocks in Chagas disease care in endemic and nonendemic countries: Argentina, Colombia, Spain, and the United States. The NET-Heart project

Background Chagas disease (CD) is endemic in Latin America; however, its spread to nontropical areas has raised global interest in this condition. Barriers in access to early diagnosis and treatment of both acute and chronic infection and their complications have led to an increasing disease burden outside of Latin America. Our goal was to identify those barriers and to perform an additional analysis of them based on the Inter American Society of Cardiology (SIAC) and the World Heart Federation (WHF) Chagas Roadmap, at a country level in Argentina, Colombia, Spain, and the United States, which serve as representatives of endemic and nonendemic countries. Methodology and principal findings This is a nonsystematic review of articles published in indexed journals from 1955 to 2021 and of gray literature (local health organizations guidelines, local policies, blogs, and media). We classified barriers to access care as (i) existing difficulties limiting healthcare access; (ii) lack of awareness about CD and its complications; (iii) poor transmission control (vectorial and nonvectorial); (iv) scarce availability of antitrypanosomal drugs; and (v) cultural beliefs and stigma. Region-specific barriers may limit the implementation of roadmaps and require the application of tailored strategies to improve access to appropriate care. Conclusions Multiple barriers negatively impact the prognosis of CD. Identification of these roadblocks both nationally and globally is important to guide development of appropriate policies and public health programs to reduce the global burden of this disease.
A Survey on Analysing Students Learning Experiences by Extracting Data from Social Media (Social Forums)

There are various online networking sites such as Facebook, twitter where students casually discuss their educational experiences, their opinions, emotions, and concerns about the learning process. Information from such open environment can give valuable knowledge for opinions, emotions and help the educational organizations to get insight into students' educational life. Analysing down such data, on the other hand, can be challenging therefore a qualitative research and significant data mining process needs to be done. Sentiment classification can be done using NLP (Natural Language Processing). For a social network that provides micro blogging services such as twitter, the incoming tweets can be classified into News, Opinions, Events, Deals and private Messages based on authors information available in the tweets. This approach is similar to Tweetstand, which classifies the tweets into news and non-news. Even for e-commerce applications virtual customer environments can be created using social networking sites. Since the data is ever growing, using data mining techniques can get difficult, hence we can use data analysis tools.
Non-compliance with Australian Stock Exchange Recommendations on Board Independence

This research investigates the relationship between corporate governance structure and attributes and the quality of reported earnings in a sample of Indonesian firms. The findings of our research reveals that both concentrated and family ownership are associated with lower earnings quality. In addition we find that independent members of a board committee act as an effective monitoring mechanism to oversee the accounting and financial reports processes of a company.
8 Coating Nanomagnetic Particles for Biomedical Applications

Magnetic particles with dimensions ranging from the nanometer to the micrometer scales are being used in an increasing number of medical applications, since the mid-1970s. The most important properties of magnetic particles for clinical diagnostics and medical therapies are clearly nontoxicity, biocompatiblilty, injectability, and high-level accumulation in the target tissue or specific organ, being strictly and spatially confined to the planned region of the internal body (Ito et al., 2005). The unique feature of NMPs to be guided by an external magnetic field has been used in magnetic resonance imaging (MRI), tissue repair, hyperthermia, drug delivery, and in cell separation (Duguet et al., 2006; Gupta & Gupta, 2005; Gupta et al., 2007; Mccarthy et al., 2007). For these biomedical applications, magnetic particles exhibiting superparamagnetic behavior at room temperature are preferred because they do not retain any magnetism after removal of the magnetic field. For NMPs, this behavior can be explained by their extraordinarily reduced sizes (Mørup et al., 1976; Pfannes, 1997). The magnetization relaxation depends on KV/kT (Gupta & Gupta, 2005; Gupta et al., 2007) in which K is the particle anisotropy constant, V is particle volume, k is Boltzmann’s constant and T is temperature. At a certain reduced size (volume), KV becomes comparable to the thermal energy kT. As a result, the magnetization of the particle fluctuates rapidly from one direction to another due to the thermal agitation, leaving no net magnetic moment. At this magnetic stage, the particle is said to be superparamagnetic (Xu & Sun, 2007). Fig. 1 shows a magnetization curve obtained by Andrade et al for a NMPs with particle size of 7 nm (Andrade et al., 2009). This shows that a particle can be magnetized under an external magnetic field (H), reaching a maximum moment (M) when the field is strong enough. However, there is no remnant magnetic moment, i.e. without an external magnetic field, the net moment of the particle is randomized to zero. Therefore, these superparamagnetic nanoparticles are very useful for biomedical applications as they are not subject to strong magnetic interactions in the dispersion and are readily stabilized in physiological conditions (Gupta & Gupta, 2005; Neuberger et al., 2005; Sonvico et al., 2005).
FOOTBALL (SOCCER) PLAYERS KINEMATICS AT DIFFERENT DEVELOPMENT LEVELS. PART TWO - RESULTS AND CONCLUSIONS

The paper presents description of a match play of soccer players at different development levels – Junior, Olympic and Senior Teams. Also different formations were taken into account. Video analysis of the whole match using a picture of the entire pitch was utilised. Kinematics of play differed. Juniors played similar to Olympic players but less intense comparing to senior players. They covered shorter distance, at lower mean velocity. Defenders covered shorter distance with the lowest mean velocity.