Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration and virtual reality exploration of biomedical data with CmPI and VANTED

Abstract Modelling and analysis of metabolic processes is an established research field in Computational Systems Biology and Medicine. There are many different approaches for modelling as well as for visualization, but often these methods ignore the subcellular localization of proteins, enzymes and transporters involved in the metabolic processes. Over the recent years, we developed two tools: CELLmicrocosmos 4 PathwayIntegration (CmPI) and VANTED. CmPI is used to analyse, visualize and explore potential subcellular localizations in a cell environment. CmPI provides import capabilities for metabolic pathways and simple visualization of directed networks showing the enzyme-compound relationships inside this environment in 2D as well as 3D. VANTED allows to analyse and visualize biological networks, to integrate data into these networks and simulate their dynamics. Here, we will discuss future perspectives of these approaches and how to extend the capabilities of CmPI's localization method to provide a) complex modelling, visualization and exploration of metabolic networks in combination with -omics data, and b) immersive analytics of the spatially distributed networks using different Virtual Reality-based technologies. We discuss the prototypic integration of CmPI with VANTED and the large display visualization framework Omegalib in combination with a semi-immersive monitor zSpace™ and CAVE2™.
Analysis of the catalytic specificity of cytochrome P450 enzymes through site‐directed mutagenesis

The way in which structural diversity encodes the capacity of individual P450 enzymes to metabolize multiple, structurally distinct substrates remains largely unknown. The tools of molecular biology provide a means of identifying amino acid residues among closely related P450s that are determinants of their distinct catalytic properties. Work in our laboratory has identified two substrate specificity‐determining segments of the amino acid sequences of subfamily 2C P450s. A pattern has emerged from this work, and that of others, which suggests a model for the structural basis of P450 catalytic diversity. —Johnson, E. F. ; Kronbach, T. ; Hsu, M. ‐H. Analysis of the catalytic specificity of cytochrome P450 enzymes through site‐directed mutagenesis. FASEB J. 6: 700‐705; 1992.
Tetramer-Guided Epitope Mapping: Rapid Identification and Characterization of Immunodominant CD4+ T Cell Epitopes from Complex Antigens1

T cell responses to Ags involve recognition of selected peptide epitopes contained within the antigenic protein. In this report, we describe a new approach for direct identification of CD4+ T cell epitopes of complex Ags that uses human class II tetramers to identify reactive cells. With a panel of 60 overlapping peptides covering the entire sequence of the VP16 protein, a major Ag for HSV-2, we generated a panel of class II MHC tetramers loaded with peptide pools that were used to stain peripheral lymphocytes of an HSV-2 infected individual. With this approach, we identified four new DRA1*0101/DRB1*0401- and two DRA1*0101/DRB1*0404-restricted, VP16-specific epitopes. By using tetramers to sort individual cells, we easily obtained a large number of clones specific to these epitopes. Although DRA1*0101/DRB1*0401 and DRA1*0101/DRB1*0404 are structurally very similar, nonoverlapping VP16 epitopes were identified, illustrating high selectivity of individual allele polymorphisms within common MHC variants. This rapid approach to detecting CD4+ T cell epitopes from complex Ags can be applied to any known Ag that gives a T cell response.
Progress with formalization in medical informatics?

The prevailing view of medical informatics as a primarily subservient discipline in health care is challenged. Developments in both general informatics and medical informatics are described to identify desirable properties of modeling languages and tools needed to solve key problems in the application field. For progress in medical informatics, it is considered essential to develop far more formal modeling languages, modeling techniques, and tools. A major aim of this development should be to expel ambiguity from concepts essential to medicine, positioning medical informatics "at the heart of health care. "
UWB delay profile models for residential and commercial indoor environments

We present models for the ultrawideband (UWB) channel delay profile in indoor environments, based on the processing of two large sets of measured data. Both measurement sets are for a center frequency of 5 GHz, but the bandwidths are very different-1.25 GHz and 6 GHz. We model both line-of-sight (LOS) and nonline-of-sight (NLOS) paths, and do so for both single-family homes and commercial buildings. Also, we consider both the profile at a receiver point, which we call the multipath intensity profile (MIP), and the locally spatially averaged profile, which we call the power delay profile (PDP). For both cases, we find that the profile for NLOS paths can be modeled as a decaying exponential times a noise-like variation with lognormal statistics and that, for LOS paths, the profile has the same form plus a strong component at the minimum delay. The model consists of statistical descriptions of the parameters of these functions, including the effects of transmit-receive (T--R) distance and of variations from building to building. We show simulation results for a few cases to demonstrate that the model accurately predicts key properties of the measured channels, such as the distribution of rms delay spread.
Recovery processing for high availability stream processing systems in local area networks

In this paper, we investigate recovery processing for stream processing systems with high availability in local area networks (LANs) in which not so many resources are available. We focus on a simple high availability distributed stream processing system model where each processing node in a query network has a backup node. We discuss pros and cons of several approaches to recovery processing from single-node fail-stop failures in the system model running in LANs with limited resources. In particular, we compare the approaches in terms of suitability to LANs, recovery cost and throughput. Some results of simulation in which recovery approaches were compared in terms of recovery cost and throughput are shown.
Myths and Tragedies in their Ancient Greek Contexts

ABBREVIATIONS LIST OF ILLUSTRATIONS INTRODUCTION PART I: THEMES IN MYTH 1. Imaginary Greek Mountains 2. Wolves and Werewolves in Greek Thought 3. Mythological Names: The Case of melas 4. The Myth of Talos: Vulnerability, ichor, and Boundary-Crossing 5. Movement and Stillness: Versions of Medea PART II: MYTHS IN TRAGEDY 6. Tragedy and Greek Myth 7. Time, Space, and Ideology: Tragic Myths and the Athenian Polis 8. Bafflement in Greek Tragedy 9. Blindness and Limits: Sophokles and the Logic of Myth 10. Euripides Alkestis: Five Aspects of an Interpretation 11. Feminized Males in Bakchai: The Importance of Discrimination ENVOI DETAILS OF ORIGINAL PUBLICATION BIBLIOGRAPHY INDEX
A surface impedance boundary condition approach to the FDTD modeling of graphene

Graphene is a promising material for many applications, and electromagnetic modeling for graphene is needed to aid the design of graphene based devices. We present an approach for the finite-difference time-domain (FDTD) simulation of graphene improving on accuracy and computational efficiency. This is accomplished using a surface impedance boundary conditions (SIBC) to model graphene as a surface, eliminating the need to simulate the interior of the material. The vector-fitting technique is used in conjunction with FDTD to achieve accurate response over a broad range of frequencies.
Apoptotic Pathways Tumor Cell Vaccines: Dependence on Tumors Enhances the Efficacy of Peripheral into Central Nervous System a Secrete IFN-Delivery of Dendritic Cells Engineered to

We tested whether modulation of the CNS-tumor microenvironment by delivery of IFN- (cid:1) -transduced dendritic cells (DCs: DC-IFN- (cid:1) ) would enhance the therapeutic efﬁcacy of peripheral vaccinations with cytokine-gene transduced tumor cells. Mice bearing intracranial GL261 glioma or MCA205 sarcoma received peripheral immunizations with corresponding irradiated tumor cells engineered to express IL-4 or GM-CSFs, respectively, as well as intratumoral delivery of DC-IFN- (cid:1) . This regimen prolonged survival of the animals and induced tumor-speciﬁc CTLs that expressed TRAIL, which in concert with perforin and Fas ligand (FasL) was involved in the tumor-speciﬁc CTL activity of these cells. The in vivo antitumor activity associated with this approach was abrogated by administration of neutralizing mAbs against TRAIL or FasL and was not observed in perforin (cid:2) / (cid:2) , IFN- (cid:3) (cid:2) / (cid:2) , or FasL (cid:2) / (cid:2) mice. Transduction of the tumor cells with antiapoptotic protein cellular FLIP rendered the gene-modiﬁed cells resistant to TRAIL- or FasL-mediated apoptosis and to CTL killing activity in vitro. Furthermore, the combination therapeutic regimen was ineffective in an intracranial cellular FLIP-transduced MCA205 brain tumor model. These results suggest that the combination of intratumoral delivery of DC-IFN- (cid:1) and peripheral immunization with cytokine-gene transduced tumor cells may be an effective therapy for brain tumors that are sensitive to apoptotic signaling pathways. The Journal of Immunology, 2005, 175: 2730–2740.
Buddhist Thought: A Complete Introduction to the Indian Tradition

Buddhist Thought guides the reader towards a richer understanding of the central concepts of classical Indian Buddhist thought, from the time of Buddha, to the latest scholarly perspectives and controversies. Abstract and complex ideas are made understandable by the authors' lucid style. Of particular interest is the up-to-date survey of Buddhist Tantra in India, a branch of Buddhism where strictly controlled sexual activity can play a part in the religious path. Williams' discussion of this controversial practice as well as of many other subjects makes Buddhist Thought crucial reading for all interested in Buddhism.
Improving the Performance of Text Categorization using N-gram Kernels

Kernel Methods are known for their robustness in handling large feature space and are widely used as an alternative to external feature extraction based methods in tasks such as classification and regression. This work follows the approach of using different string kernels such as n-gram kernels and gappy-n-gram kernels on text classification. It studies how kernel concatenation and feature combination affects the classification accuracy of the system. It also explores how the kernel combination algorithms work on the system. The kernels are implemented as rational kernels, which satisfies the Mercer’s Theorem ensuring the kernel matrices to be positive definite symmetric. The rational kernels are computed with a general algorithm of composition of weighted transducers which help in dealing with variable length sequences. These kernels are then used with SVM formulating efficient classifier for text categorization. Both one-stage and two stage algorithms are applied for kernel combination which were successful in achieving better system performance compared to that given by individual kernels.
Explorer Multiplicative LSTM for sequence modelling

The “CNN-RNN” design pattern is increasingly widely applied in a variety of image annotation tasks including multi-label classification and captioning. Existing models use the weakly semantic CNN hidden layer or its transform as the image embedding that provides the interface between the CNN and RNN. This leaves the RNN overstretched with two jobs: predicting the visual concepts and modelling their correlations for generating structured annotation output. Importantly this makes the end-to-end training of the CNN and RNN slow and ineffective due to the difficulty of back propagating gradients through the RNN to train the CNN. We propose a simple modification to the design pattern that makes learning more effective and efficient. Specifically, we propose to use a semantically regularised embedding layer as the interface between the CNN and RNN. Regularising the interface can partially or completely decouple the learning problems, allowing each to be more effectively trained and jointly training much more efficient. Extensive experiments show that state-of-the art performance is achieved on multi-label classification as well as image captioning.
Pyrosequencing of Tagged 16S rRNA Gene Amplicons for Rapid Deciphering of the Microbiomes of Fermented Foods Such as Pearl Millet Slurries

ABSTRACT Pearl millet slurries, mixed with groundnuts or not, were chosen as a model to investigate the feasibility of obtaining a rapid overview of community structure and population dynamics of fermented foods using pyrosequencing of tagged 16S rRNA gene amplicons. From 14 fermented samples collected either in a traditional small-scale processing unit in Burkina Faso or at laboratory scale, 137,469 sequences of bacterial 16S rRNA gene amplicons were characterized. Except for a few Proteobacteria, almost all the bacterial sequences were attributed to cultivable bacteria. This approach enabled 80.7% of the sequences to be attributed to a family and 70% to a genus but did not enable identification to the species level. The bacterial sequences were assigned to four phyla, with Firmicutes representing the highest diversity, followed by Proteobacteria, Actinobacteria, and Bacteroidetes, which were found only in the slurries prepared in traditional production units. Most of the Firmicutes were lactic acid bacteria, mainly represented by members of the Lactobacillus, Pediococcus, Leuconostoc, and Weissella genera, whose ratio varied from the onset to the end of the fermentation. The other bacteria present at the beginning of fermentation were generally no longer detected at the end, which is consistent with already-known patterns in the microbial ecology of fermented foods. In conclusion, this method seems very promising for rapid and preliminary microbial characterization in many samples of an unknown food sample, by determining numerous nucleic sequences simultaneously without the need for cloning and cultivation-dependent methods.
The Resurrection of Jesus and Spiritual (Trans)Formation

What does Paul envision as the basis for the spiritual (transformation of the believer? Several key passages in the Pauline epistles reveal that Paul envisions a vibrant connection between the resurrection of Jesus and the expected character qualities and behaviors of those who are in Christ. In examining this connection between resurrection and Christian maturation, three distinct, though interrelated, emphases may be identified: 1) identification with Jesus in his resurrection, 2) submission to the lordship of Jesus and the expectations of his kingdom, and 3) hope in the future resurrection of those who are “in Christ. ” While these form the “ground” for spiritual (trans)formation, Paul further offers a model for applying this resurrection identification in the “here and now” life of the believer.
PLANEJAMENTO, MONTAGEM E APLICAÇÃO DE MODELOS DIDÁTICOS PARA ABORDAGEM DE BIOLOGIA CELULAR E MOLECULAR NO ENSINO MÉDIO POR GRADUANDOS DE CIÊNCIAS BIOLÓGICAS

Este artigo relata o processo de construcao e aplicacao de modelos de baixo custo na area debiologia celular e molecular. O carater microscopico das estruturas estudadas nos conteudosdestas disciplinas torna a abordagem de ensino muitas vezes abstrata, dificultando o processode aprendizagem. Ao mesmo tempo, a falta de laboratorios ou equipamentos em muitasescolas compromete o ensino destas disciplinas. Neste contexto, estudantes do curso deciencias biologicas da Universidade Federal de Alfenas (Unifal-MG) desenvolveram e aplicaramsete modelos em alunos do ensino medio, como material didatico de apoio para a disciplinaBiologia. Os resultados foram bastante positivos tanto para os estudantes do ensino medio,quanto para a equipe de graduandos.
The power-saving approach by critical section detections of multi-cores embedded systems

The use of multi-threading and multi-cores leads to performance improvements of embedded systems. On the other hand, the power consumption increases due to the use of more processors. The energy wastages could be critical in embedded systems with limited resources. Therefore, the issues of performance and power-saving are important for multithreaded applications which are executed on multi-cores embedded systems. The dynamic CPU frequency leveling which is based on critical section detections is proposed in this paper. Based on this approach, the energy wastages are reduced significantly with the maintenances of performance at the same time. The results indicate the battery life of multi-cores embedded systems can be extended by proposed power-saving approach effectively.
IndoWordNet Conversion to Web Ontology Language (OWL)

WordNet plays a significant role in Linked Open Data (LOD) cloud. It has numerous application ranging from ontology annotation to ontology mapping. IndoWordNet is a linked WordNet connecting 18 Indian language WordNets with Hindi as a source WordNet. The Hindi WordNet was initially developed by linking it to English WordNet. In this paper, we present a data representation of IndoWordNet in Web Ontology Language (OWL). The schema of Princeton WordNet has been enhanced to support the representation of IndoWordNet. This IndoWordNet representation in OWL format is now available to link other web resources. This representation is implemented for eight Indian languages.
Image processing for three-dimensional scans generated by time-of-flight range cameras

Time-of-flight (TOF) full-field range cameras use a correlative imaging technique to generate three-dimensional measurements of the environment. Though reliable and cheap they have the disadvantage of high measurement noise and errors that limit the practical use of these cameras in industrial applications. We show how some of these limitations can be overcome with standard image processing techniques specially adapted to TOF camera data. Additional information in the multimodal images recorded in this setting, and not available in standard image processing settings, can be used to improve reduction of measurement noise. Three extensions of standard techniques, wavelet thresholding, adaptive smoothing on a clustering based image segmentation, and an extended anisotropic diffusion filtering, make use of this information and are compared on synthetic data and on data acquired from two different off-the-shelf TOF cameras. Of these methods, the adapted anisotropic diffusion technique gives best results, and is implementable to perform in real time using current graphics processing unit (GPU) hardware. Like traditional anisotropic diffusion, it requires some parameter adaptation to the scene characteristics, but allows for low visualization delay and improved visualization of moving objects by avoiding long averaging periods when compared to traditional TOF image denoising.
Research on the hydrodynamic characteristic of a vertical axis propeller

This paper presents a new vertical axis propeller, which combines the turbine with the rudder and can generate thrust in all directions. It describes the modelling of the vertical axis propeller and presents the results of simulations under various conditions. The two-dimensional (2D) simulations investigate the influence of parameters such as advance coefficient, blade number and spacing distance between two propellers on the hydrodynamic performance. The three-dimensional (3D) simulations study the distribution of the pressure forced on the blades and the consequences. The simulation results indicate that the vertical axis propeller yields very good performance under a variety of initial conditions. It is also demonstrated that, by optimizing the parameters of the propeller, the vertical axis propeller proves capable of achieving a high power coefficient. This work constitutes a preliminary step towards the development of an advanced concept of vertical axis propeller.
Three‐dimensional pancreas organogenesis models

A rediscovery of three‐dimensional culture has led to the development of organ biogenesis, homeostasis and disease models applicable to human tissues. The so‐called organoids that have recently flourished serve as valuable models bridging between cell lines or primary cells grown on the bottom of culture plates and experiments performed in vivo. Though not recapitulating all aspects of organ physiology, the miniature organs generated in a dish are useful models emerging for the pancreas, starting from embryonic progenitors, adult cells, tumour cells and stem cells. This review focusses on the currently available systems and their relevance to the study of the pancreas, of β‐cells and of several pancreatic diseases including diabetes. We discuss the expected future developments for studying human pancreas development and function, for developing diabetes models and for producing therapeutic cells.
Perioperative nutrition management as an important component of surgical capacity in low‐ and middle‐income countries

Needs for surgical care are growing in low‐ and middle‐income countries. Existing surgical care capacity indicators, focusing on the availability of equipment, personnel, and operation and anaesthetic skills, are not intended to evaluate perioperative nutrition management, which influences surgical outcomes. In this narrative review, we describe the prevalence of malnutrition and its clinical consequences among surgical patients in low‐ and middle‐income countries, suggest potential measures to improve nutrition management and discuss the necessity of considering nutrition management as a component of surgical care capacity.
PAMPAS: Privacy-Aware Mobile Participatory Sensing Using Secure Probes

Mobile participatory sensing could be used in many applications such as vehicular traffic monitoring, pollution tracking, or even health surveying. However, its success depends on finding a solution for querying large numbers of users which protects user location privacy and works in real-time. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in mobile participatory sensing. In PAMPAS, mobile devices enhanced with secure hardware, called secure probes (SPs), perform distributed query processing, while preventing users from accessing other users' data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. In addition to its novel system architecture, PAMPAS also proposes two new protocols for privacy-aware location-based aggregation and adaptive spatial partitioning of SPs that work efficiently on resource-constrained SPs. Our experimental results and security analysis demonstrate that these protocols are able to collect the data, aggregate them, and share statistics or derived models in real-time, without any location privacy leakage.