Miracle-dz/UniFAR-FTUs huggingface dataset:
Endocardial Energy Harvesting by Electromagnetic Induction

Objective: cardiac pacemakers require regular medical follow-ups to ensure proper functioning. However, device replacements due to battery depletion are common and account for ∼25% of all implantation procedures. Furthermore, conventional pacemakers require pacemaker leads which are prone to fractures, dislocations or isolation defects. The ensuing surgical interventions increase risks for the patients and costs that need to be avoided. Methods: in this study, we present a method to harvest energy from endocardial heart motions. We developed a novel generator, which converts the heart's mechanical into electrical energy by electromagnetic induction. A mathematical model has been introduced to identify design parameters strongly related to the energy conversion efficiency of heart motions and fit the geometrical constraints for a miniaturized transcatheter deployable device. The implemented final design was tested on the bench and in vivo. Results : the mathematical model proved an accurate method to estimate the harvested energy. For three previously recorded heart motions, the model predicted a mean output power of 14.5, 41.9, and 16.9 μW. During an animal experiment, the implanted device harvested a mean output power of 0.78 and 1.7 μW at a heart rate of 84 and 160 bpm, respectively. Conclusion: harvesting kinetic energy from endocardial motions seems feasible. Implanted at an energetically favorable location, such systems might become a welcome alternative to extend the lifetime of cardiac implantable electronic device. Significance: the presented endocardial energy harvesting concept has the potential to turn pacemakers into battery- and leadless systems and thereby eliminate two major drawbacks of contemporary systems.
Human L-Ficolin (Ficolin-2) and Its Clinical Significance

Human L-ficolin (P35, ficolin-2) is synthesised in the liver and secreted into the bloodstream where it is one of the major pattern recognition molecules of plasma/serum. Like other ficolins, it consists of a collagen-like tail region linked to a fibrinogen-related globular head; a basic triplet subunit arises via a collagen-like triple helix, and this then forms higher multimers (typically a 12-mer, Mr 400K). Unlike other ficolins, it has a complex set of binding sites arranged within an internal cleft enabling it to recognise a variety of molecular patterns including acetylated sugars and certain 1,3-β-glucans. It is one of the few molecules known to activate the lectin pathway of complement. Recently, some disease association studies (at either the DNA or protein level) have implicated L-ficolin in innate immunity, where it might cooperate with pentraxins and collectins. Emerging lines of evidence point to a role for L-ficolin in respiratory immunity, where its affinity for Pseudomonas aeruginosa could be significant.
Follow‐up of 30 Klinefelter males treated with testosterone

Thirty Klinefelter males treated with testosterone were studied by a follow‐up examination carried out an average of 3.6 years after treatment began. The age of the men averaged 25.5 years at the time of the follow‐up. Seventy‐seven per cent of the men were judged to have benefited from testosterone treatment. They showed better mood, less irritability, more energy and drive, less tiredness, more endurance and strength, less need for sleep, better concentration ability and better relations with others during testosterone treatment. The beneficial effects of testosterone persisted in some of the men after cessation of treatment. The findings show that Klinefelter males given testosterone for the first time as adults can benefit from such treatment, even though it is preferable to start treatment at the age of 11–12 years.
The Staphylococci and Staphylococcal Pathogenesis

Over the past 30 years, the scientific literature has been rife with articles that have chronicled the enduring threat and changing nature of Staphylococcus aureus as a leading cause of infectious morbidity and mortality to humans (Sheagren, 1984; Archer, 1998; Lowy, 1998; Otto, 2010). The most current surveys indicate that S. aureus is responsible for almost 500,000 hospitalizations and 30,000 deaths annually in the USA (Klein et al., 2007). At the turn of the twentieth century, the major threat was hospital-associated strains of methicillin resistant S. aureus (HA-MRSA) that are resistant to multiple antibiotics, and reports that some had acquired high level vancomycin resistance (Pearson, 2002; Weigel et al., 2003) seemed to assure the inevitable proliferation of strains that are resistant to all antibiotics. Although this crisis has not yet materialized, we have instead experienced the sudden emergence and global dissemination of hyper-virulent strains of community acquired MRSA (CA-MRSA). Another unexpected threat was the emergence of CA-MRSA in animal adapted strains of S. aureus, and their zoonotic transmission to humans. Conversely, some livestock-associated strains have undergone a recent evolutionary transition from human to animal hosts. Amidst this backdrop of newly emergent strains, common clonal types of HA-MRSA and methicillin susceptible S. aureus (MSSA) persist in their threat to health care, and attempts to lessen the impact through vaccine development have thus far been unsuccessful. In this Special Topics issue, recent advances in Staphylococcal research are captured in a collection of research, review, opinion, and methods articles, which we have assigned to the general themes of vaccine development, virulence, and immune evasion, metabolic activity in response to host environment, methods development, and comparative genomics and genome evolution.
Clustering Web Usage Data using Concept Hierarchy and Self Organizing Map

Clustering Web Usage data is one of the important tasks of Web Usage Mining, which helps to find Web user clusters and Web page clusters. Web user clusters establish groups of users exhibiting similar browsing patterns and Web page clusters provide useful knowledge to personalized Web services. Different types of clustering algorithms such as partition based, distance based, density based, grid based, hierarchical and fuzzy clustering algorithms are used to find clusters from Web usage data.These clustering algorithms require more space and time forlargerWeb server log files. K-Means algorithm has been one of the most widely used algorithms for clustering Web usage data due to its computational performance. Although K-Means algorithm is relatively fast and efficient compared to other clustering algorithms, it has some major drawbacks. The number of clusters must be specified in advance. The initial cluster centroids are selected randomly. Clustering result depends on the selection of randomly selected initial cluster centroids and different runs on the same input data might produce different results. KMeans algorithm is sensitive to noisy data and outliers. Recent studies have supported the use of neural networks such as Adaptive Resonance Theory (ART) and Self Organizing Maps (SOM) for real world data mining problems. Among the architectures and algorithms suggested for neural networks, the SOM has special property of effectively creating spatially organized internal representations of various features of input data and their abstractions. In this paper we propose a framework for finding useful information from Web Usage Data that uses SOM. First we have constructed the sessions using concept hierarchy and link information. Then SOM is used to cluster the sessions. We provide experimental results to show the benefits of using concept hierarchy for synaptic weights and clustering Web usage data using SOM. In this paper, we have considered the server log files of the Website www.enggresources. com for overall study and analysis.
Two different views about software complexity

The aim of this work is to analyse the several metrics used in software engineering to assess the complexity of software products. First we discuss the differences between the complexity of the problem and the complexity of the solution (implementation) setting up several metrics that can be used in measuring both of above aspects. We define what is the difference in complexity between a problem and a solution. Next we describe the software development process as a series of successive transformations. The first model constructed is the requirements document and the last model is the code, which represents the particular solution. Then we analyse the relation between complexity, effort and efficiency and we will describe some metrics, which can be used to measure them. We notice that conventional software metrics doesn't reflect the all aspects of problem/solution complexity. It is shown that no single metric alone could measure all the complexity aspects of the product. Finally we describe the metrics used in the complexity fields like algorithmic complexity, logical complexity, information theory, Shannon entropy, statistical complexity, grammatical complexity, etc. We compare each one with others and show that the last ones are suitable for measuring the global aspect of complexity in the software problem/solution. We conclude that it is possible to use complexity metrics used in complex systems in software engineering with some advantages. 1. Complexity of the problem and it’s solutions . According to the Many Lehman software process definition,[19] a solution of a problem is an operational model obtained from a set of transformations applied to the initial model of that problem. So behind each solution there is a problem. However the complexity of the problem differs from the complexity of the solution. Complex solutions may exist for simple problems. In this paper we will use the following definitions: [9] [5] [16] [17] [18] [31] The complexity of a problem is the amount of resources required for an optimal solution of the problem . The complexity of a solution is the amount of resources required for that solution of the problem . In order to evaluate the complexity of a solution several types of metrics are frequently used: [9] [5] ? Algorithmic Complexity Is required to reflect the algorithmic complexity in each solution. There are two types of metrics in this class: one is the complexity based on the algorithmic efficiency, the other is the complexity on the structure of the algorithm. Cognitive Complexity Is required to reflect the amount of effort needed to understand the problem. In order to assess problem complexity [8], metrics of Computational Complexity are used.
Analysis of visual perceptual patterns on screen using eyetracker technology

According to current researches, individual differences in eye movement patterns may be related to different ways of text processing, to comprehension difficulties, etc. They also depend on the nature of the text. Particular question is how reading takes place in case of using figurative (visual) language, e.g. in case of metaphors, irony, or fixed phrases (phraseologisms). Based on other researches, it is evident that the development level of executive functions of each individual is strongly tied to their sociocultural background, especially to the parenting style of their family; on the other hand, differences in executive function significantly affect a person's performance at school. The notable part for the aim of this paper, however, is the direct link between executive functions and eye movement, i.e. on the basis of eye tracking it is possible to make direct, unaltered conclusions on executive functions [1]. Electronic screens on laptop and tablet computers and smartphones are being used for reading text, often while multitasking [14]. The question arises whether reading from a screen is as effective as the reading from textbooks. One of the aims of the paper is to verify the visual patterns of information retrieval from screen for problem comprehension and solving using eyetracking technology.
Interfacial damage on fatigue-loaded textile–rubber composites

To reach admissible lifetime expectancy, unidirectional textile–rubber composites must show a strong interface. Usually, it is achieved by coating the textile with Resorcinol–Formaldehyde–Latex (RFL). To evaluate fatigue impact on interfacial properties, composites with or without RFL are tested at different numbers of loading cycles and characterized through peel tests, dynamic mechanical analysis (DMA), scanning electron microscopy and energy-dispersive X-rays, and nanoindentation. For composites with RFL, the results indicate two main mechanisms for damaging: propagation of pre-existing fibrillar microcracks at the rubber/RFL interface completed by adhesive debondings at the RFL/textile interface. At first, the propagation of fibrillar microcracks is correlated with decrease of global composite peeling resistance and contribution of interphase to DMA damping. Then, RFL/textile debondings become critical. They are highlighted with a change of peeling failure surface and could be explained by RFL hardening, highlighted by nanoindentation. This questions the choice for RFL as a sustainable adhesive for composites under fatigue loading. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41346.
Use of in vivo-induced antigen technology (IVIAT) to identify genes uniquely expressed during human infection with Vibrio cholerae

In vivo-induced antigen technology is a method to identify proteins expressed by pathogenic bacteria during human infection. Sera from 10 patients convalescing from cholera infection in Bangladesh were pooled, adsorbed against in vitro-grown El Tor Vibrio cholerae O1, and used to probe a genomic expression library in Escherichia coli constructed from El Tor V. cholerae O1 strain N16961. We identified 38 positive clones in the screen, encoding pili (PilA and TcpA), cell membrane proteins (PilQ, MshO, MshP, and CapK), methyl-accepting chemotaxis proteins, chemotaxis and motility proteins (CheA and CheR), a quorum-sensing protein (LuxP), and four hypothetical proteins. Analysis of immune responses to purified PilA and TcpA in individual patients demonstrated that the majority seroconverted to these proteins, confirming results with pooled sera. These results suggest that PilA and its outer membrane secretin, PilQ, are expressed during human infection and may be involved in colonization of the gastrointestinal tract. These results also demonstrate substantial immune responses to TcpA in patients infected with El Tor V. cholerae O1. In vivo-induced antigen technology provides a simple method for identifying microbial proteins expressed during human infection, but not during in vitro growth.
Anisotropic Change of Liquid‐Crystal Domains by Polarized Infrared Pulse Laser Irradiation for a Columnar Mesophase

The infrared photoinduced alignment change of liquid‐crystal domains was investigated for a hexagonal columnar mesophase of a liquid‐crystalline triphenylene derivative. A uniform and anisotropic alignment change of domains was observed when a polarized infrared (IR) light corresponding to the wavelength of the aromatic C–C stretching absorption band of the triphenylene core was used to irradiate the sample. The relationship between the aligned azimuthal angle of the columnar axis and the polarization of the IR incident irradiation was investigated. IR absorption dichroism is induced as a result of the reorientation of triphenylene core. Texture observation and polarizing microscope FTIR spectra show that a change of the molecular alignment occurred and that the direction of columns depends on the polarization angle of the IR light used for irradiation. The mechanism of the alignment change in a columnar liquid crystal film by IR irradiation is also discussed. The technique could provide a novel technology to control the columnar alignment of highly viscous liquid crystals.
Knowledge management system in falling risk for physiotherapy care of elderly

This paper describes the elderly healthcare research project affected by a fall. The decision support system is proposed as knowledge management method, including knowledge engineering to acquiring the expert's heuristically diagnostic knowledge and sharing this knowledge to the physiotherapist in the form of tool and application at the right time. This paper outlines a Knowledge Management System (KMS) to diagnose falling patterns in elderly people using Motion Capture Technology. The idea is to integrate an appropriate procedure including case based reasoning and motion capture to provide a decision support system. The diagnosis information derived from the process of KMS helps support the physiotherapist to determine serious falling risks in the elderly and recommend guidelines for medical treatment. The evaluation result shows an efficient performance with 80.95% of precision when using the Assumption Attribute category criteria with K NNR =3. Furthermore, the result of KMS-EUCS shows a high satisfaction from the users with 97.50% of satisfaction in a community of practice scenario. This can confirm the successful of KMS approach within the falling risk screening procedure.
Relation Between Putative Transmitter Phenotypes and Connectivity of Subplate Neurons During Cerebral Cortical Development

During development, the earliest generated neurons of the mammalian telencephalon reside in a region of the white matter, the subplate, just beneath the cortical plate. Neurons in the subplate are only transiently present in the telencephalon: shortly after birth in the cat the majority have disappeared. During their brief life, however, subplate neurons mature; they extend long‐distance and local projections, and express immunoreactivity for GABA and several neuropeptides. In the present study we examined the relation between possible transmitter phenotypes of subplate neurons and their connectivity. To do so, we used a double‐label technique in which immunohistochemistry for neuropeptide Y (NPY), somatostatin (SRIF) or calbindin (CaBP) was combined with retrograde tracing. Experiments were performed in neonatal cats and in ferret kits at equivalent postconceptional ages, times when subplate neurons are numerous. Subplate neurons immunoreactive for neuropeptides and CaBP could be double‐labelled by an injection of retrograde tracer either into the cortical plate or the white matter, indicating that this particular subset of subplate neurons can make local circuit projections. In contrast, peptide or CaBP immunoreactive subplate neurons could never be retrogradely labelled from a tracer injection into the thalamus. Taken together, these observations indicate that subplate neurons immunoreactive for NPY, SRIF and CaBP are likely to be interneurons exclusively. On the other hand, subplate neurons with long‐distance projections to the thalamus or the contralateral hemisphere could be labelled by the retrograde transport of D‐[3H]aspartate, suggesting that at least some projection subplate neurons might use an excitatory amino acid as a neurotransmitter. These results indicate that there is a defined relationship between the putative transmitter phenotypes of subplate neurons and their patterns of projection. Interneurons of the subplate express peptidergic properties while projection neurons to the thalamus may use an excitatory amino acid. Thus, these basic organizational features of the transient subplate are reminiscent of those found in the adult cortical layers.
Learning on graphs using Orthonormal Representation is Statistically Consistent

Existing research [4] suggests that embedding graphs on a unit sphere can be beneficial in learning labels on the vertices of a graph. However the choice of optimal embedding remains an open issue. Orthonormal representation of graphs, a class of embeddings over the unit sphere, was introduced by Lovasz [2]. In this paper, we show that there exists orthonormal representations which are statistically consistent over a large class of graphs, including power law and random graphs. This result is achieved by extending the notion of consistency designed in the inductive setting to graph transduction. As part of the analysis, we explicitly derive relationships between the Rademacher complexity measure and structural properties of graphs, such as the chromatic number. We further show the fraction of vertices of a graph G, on n nodes, that need to be labelled for the learning algorithm to be consistent, also known as labelled sample complexity, is Ω (ϑ(G)/n)1/4 where ϑ(G) is the famous Lovysz ϑ function of the graph. This, for the first time, relates labelled sample complexity to graph connectivity properties, such as the density of graphs. In the multiview setting, whenever individual views are expressed by a graph, it is a well known heuristic that a convex combination of Laplacians [7] tend to improve accuracy. The analysis presented here easily extends to Multiple graph transduction, and helps develop a sound statistical understanding of the heuristic, previously unavailable.
Landmark-based consonant voicing detection on multilingual corpora

This study tests the hypothesis that distinctive feature classifiers anchored at phonetic landmarks can be transferred cross-lingually without loss of accuracy. Three consonant voicing classifiers were developed: (1) manually selected acoustic features anchored at a phonetic landmark, (2) MFCCs (either averaged across the segment or anchored at the landmark), and (3) acoustic features computed using a convolutional neural network (CNN). All detectors are trained on English data (TIMIT) and tested on English, Turkish, and Spanish (performance measured using F1 and accuracy). Experiments demonstrate that manual features outperform all MFCC classifiers, while CNN features outperform both. MFCC-based classifiers suffer an overall error rate increase of up to 96.1% when generalized from English to other languages. Manual features suffer only an up to 35.2% relative error rate increase, and CNN features actually perform the best on Turkish and Spanish, demonstrating that features capable of representing long-term spectral dynamics (CNN and landmark-based features) are able to generalize cross-lingually with little or no loss of accuracy.This study tests the hypothesis that distinctive feature classifiers anchored at phonetic landmarks can be transferred cross-lingually without loss of accuracy. Three consonant voicing classifiers were developed: (1) manually selected acoustic features anchored at a phonetic landmark, (2) MFCCs (either averaged across the segment or anchored at the landmark), and (3) acoustic features computed using a convolutional neural network (CNN). All detectors are trained on English data (TIMIT) and tested on English, Turkish, and Spanish (performance measured using F1 and accuracy). Experiments demonstrate that manual features outperform all MFCC classifiers, while CNN features outperform both. MFCC-based classifiers suffer an overall error rate increase of up to 96.1% when generalized from English to other languages. Manual features suffer only an up to 35.2% relative error rate increase, and CNN features actually perform the best on Turkish and Spanish, demonstrating that features capable of representing long-te.
Taxing capital income: a bad idea

Under a narrow set of assumptions, Chamley (1986) established that the optimal tax rate on capital income is eventually zero. This study examines and extends that result by relaxing Chamley’s assumptions, one by one, to see if the result still holds. It does. This study unifies the work of other researchers, who have confirmed the result independently using different types of models and approaches. This study uses just one type of model (discrete time) and just one approach (primal). Chamley’s result holds when agents are heterogeneous rather than identical, the economy’s growth rate is endogenous rather than exogenous, the economy is open rather than closed, and agents live in overlapping generations rather than forever. (With this last assumption, the result holds under stricter conditions than with the others.)