Miracle-dz/UniFAR-FTUs huggingface dataset:
SENCA: A Multilayered Codon Model to Study the Origins and Dynamics of Codon Usage

Gene sequences are the target of evolution operating at different levels, including the nucleotide, codon, and amino acid levels. Disentangling the impact of those different levels on gene sequences requires developing a probabilistic model with three layers. Here we present SENCA (site evolution of nucleotides, codons, and amino acids), a codon substitution model that separately describes 1) nucleotide processes which apply on all sites of a sequence such as the mutational bias, 2) preferences between synonymous codons, and 3) preferences among amino acids. We argue that most synonymous substitutions are not neutral and that SENCA provides more accurate estimates of selection compared with more classical codon sequence models. We study the forces that drive the genomic content evolution, intraspecifically in the core genome of 21 prokaryotes and interspecifically for five Enterobacteria. We retrieve the existence of a universal mutational bias toward AT, and that taking into account selection on synonymous codon usage has consequences on the measurement of selection on nonsynonymous substitutions. We also confirm that codon usage bias is mostly driven by selection on preferred codons. We propose new summary statistics to measure the relative importance of the different evolutionary processes acting on sequences.
SynCAM, a Synaptic Adhesion Molecule That Drives Synapse Assembly

Synapses, the junctions between nerve cells through which they communicate, are formed by the coordinated assembly and tight attachment of pre- and postsynaptic specializations. We now show that SynCAM is a brain-specific, immunoglobulin domain–containing protein that binds to intracellular PDZ-domain proteins and functions as a homophilic cell adhesion molecule at the synapse. Expression of the isolated cytoplasmic tail of SynCAM in neurons inhibited synapse assembly. Conversely, expression of full-length SynCAM in nonneuronal cells induced synapse formation by cocultured hippocampal neurons with normal release properties. Glutamatergic synaptic transmission was reconstituted in these nonneuronal cells by coexpressing glutamate receptors with SynCAM, which suggests that a single type of adhesion molecule and glutamate receptor are sufficient for a functional postsynaptic response.
Platelets Direct Monocyte Differentiation Into Epithelioid-Like Multinucleated Giant Foam Cells With Suppressive Capacity Upon Mycobacterial Stimulation

Background. Epithelioid, foam, and multinucleated giant cells (MNGCs) are characteristics of tuberculosis granulomas, yet the precise genesis and functions of these transformed macrophages are unclear. We evaluated the role of platelets as drivers of macrophage transformation in mycobacterial infection. Methods. We employed flow cytometry and microscopy to assess cellular phenotype and phagocytosis. Immune assays allowed quantification of cytokines and chemokines, whereas gene microarray technology was applied to estimate global transcriptome alterations. Immunohistochemical investigations of tuberculosis granulomas substantiated our findings at the site of infection. Results. Monocytes differentiated in presence of platelets (MP-Macs) acquired a foamy, epithelioid appearance and gave rise to MNGCs (MP-MNGCs). MP-Macs up-regulated activation markers, phagocytosed mycobacteria, and released abundant interleukin 10. Upon extended culture, MP-Macs shared transcriptional features with epithelioid cells and M2 macrophages and up-regulated CXCL5 transcripts. In line with this, CXCL5 concentrations were significantly increased in airways of active tuberculosis patients. The platelet-specific CD42b antigen was detected in MP-Macs, likewise in macrophages, MNGCs, and epithelioid cells within tuberculosis granulomas, along with the platelet aggregation-inducing factor PDPN. Conclusions. Platelets drive macrophage differentiation into MNGCs with characteristics of epithelioid, foam, and giant cells observed in tuberculosis granulomas. Our data define platelets as novel participants in tuberculosis pathogenesis.
Understanding Student Purpose Types and Student Perceptions of the Influences Shaping Them

Abstract The authors undertook a qualitative study involving a national sample of 75 college students to discover what factors influenced their purpose development. They found that students generally fit into four different purpose types: the Purposeless, the Self-Achievers, the Relationalists, and the Transcendents. Moreover, these different purpose types were motivated toward deeper purpose development by different influences, interactions with mentors, and ideological beliefs. These findings may prove helpful for student life professionals and faculty alike who are creating a common language to discuss purpose across their campuses.
Regularization for Partial Multichannel Equalization for Speech Dereverberation

Acoustic multichannel equalization techniques such as the multiple-input/output inverse theorem (MINT), which aim to equalize the room impulse responses (RIRs) between the source and the microphone array, are known to be highly sensitive to RIR estimation errors. To increase robustness, it has been proposed to incorporate regularization in order to decrease the energy of the equalization filters. In addition, more robust partial multichannel equalization techniques such as relaxed multichannel least-squares (RMCLS) and channel shortening (CS) have recently been proposed. In this paper, we propose a partial multichannel equalization technique based on MINT (P-MINT) which aims to shorten the RIR. Furthermore, we investigate the effectiveness of incorporating regularization to further increase the robustness of P-MINT and the aforementioned partial multichannel equalization techniques, i.e., RMCLS and CS. In addition, we introduce an automatic non-intrusive procedure for determining the regularization parameter based on the L-curve. Simulation results using measured RIRs show that incorporating regularization in P-MINT yields a significant performance improvement in the presence of RIR estimation errors, whereas a smaller performance improvement is observed when incorporating regularization in RMCLS and CS. Furthermore, it is shown that the intrusively regularized P-MINT technique outperforms all other investigated intrusively regularized multichannel equalization techniques in terms of perceptual speech quality (PESQ). Finally, it is shown that the automatic non-intrusive regularization parameter in regularized P-MINT leads to a very similar performance as the intrusively determined optimal regularization parameter, making regularized P-MINT a robust, perceptually advantageous, and practically applicable multichannel equalization technique for speech dereverberation.
Multilingual Wikipedia , Summarization , and Information Trustworthiness

Wikipedia is used as a corpus for a variety of text processing applications. It is especially popular for information selection tasks, such as summarization feature identification, answer generation/verification, etc. Many Wikipedia entries (about people, events, locations, etc.) have descriptions in several languages. Often Wikipedia entry descriptions created in different languages exhibit differences in length and content. In this paper we show that the pattern of information overlap across the descriptions written in different languages for the same Wikipedia entry fits well the pyramid summary framework, i.e., some information facts are covered in the Wikipedia entry descriptions in many languages, while others are covered in a handful number of descriptions. This phenomenon leads to a natural summarization algorithm which we present in this paper. According to our evaluation, the generated summaries have a high level of user satisfaction. Moreover, the discovered pyramid structure of Wikipedia entry descriptions can be used for Wikipedia information trustworthiness verification.
Journal of Cardiovascular Magnetic Resonance Open Access Myocardial First-pass Perfusion Cardiovascular Magnetic Resonance: History, Theory, and Current State of the Art

In less than two decades, first-pass perfusion cardiovascular magnetic resonance (CMR) has undergone a wide range of changes with the development and availability of improved hardware, software, and contrast agents, in concert with a better understanding of the mechanisms of contrast enhancement. The following review provides a perspective of the historical development of first-pass CMR, the developments in pulse sequence design and contrast agents, the relevant animal models used in early preclinical studies, the mechanism of artifacts, the differences between 1.5T and 3T scanning, and the relevant clinical applications and protocols. This comprehensive overview includes a summary of the past clinical performance of first-pass perfusion CMR and current clinical applications using state-of-the-art methodologies.
Automatic DTM Generation from Three-Line-Scanner (TLS) Images

PREFACE It was in the year 1971 at the Photogrammetric Week in Karlsruhe, Germany when the first author was captured by a stimulating presentation of Kennert Torlegard on the topic of Digital Terrain Models. From these early days of DTM research on we have come a long way towards a better understanding of data acquisition, processing, modeling and interpolation requirements. Much has been invested lately into the automated generation of DTMs from images, but despite this fact the problem is not solved yet in a satisfactory fashion. Our contribution aims at providing a further step towards the improvement of image matching algorithms and as such is to be seen in the tradition of the very early work of Prof. Torlegard on DTMs.
Where We Stand at Probabilistic Reasoning

Bayes-Nets are a suitable means for probabilistic inference. Such nets are very restricted concerning the communication language with the user, however. MinREnt-inference in a conditional environment is a powerful counterpart to this concept. Here conditional expressions of high complexity instead of mere potential tables in a directed acyclic graph, permit rich communication between system and user. This is true as well for knowledge acquisition as for query and response. For any such step of probabilistic reasoning, processed information is measurable in the information theoretical unit [bit]. The expert-system-shell SPIRIT is a professional tool for such inference and allows realworld (decision-)models with umpteen variables and hundreds
Telomerase activity in human gynaecological malignancies.

AIM: To evaluate whether increased telomerase activity can be clinically useful for detecting malignant cells in a variety of gynaecological specimens. METHODS: Telomerase activity was examined in frozen tissue samples of histologically confirmed lesions of the endometrium, ovary, and cervix. It was also assessed in exfoliated cells in cervical smears from patients with premalignant and malignant lesions and in ascitic fluid obtained from cases with malignant or non-malignant ovarian tumours. RESULTS: Solid tissues from carcinomas were telomerase positive in all specimens of endometrial (6/6) and cervical (6/6) origin, and in almost all from the ovary (12/13). Normal tissues from the cervix (0/5) and the ovary (0/5) were telomerase negative, but samples from normal endometrium were found to show telomerase activity, possibly due to the cyclical regenerative nature of this tissue. Conversely, dissociated cells in cervical smears from preneoplastic and frankly neoplastic lesions rarely showed detectable telomerase activity. Thus smears from patients with malignant tumours were only positive in one of two patients, whereas those from CIN-2 (0/5) and CIN-3 (1/17) lesions and from normal (0/10) samples were almost all negative. Telomerase activity was also scarcely detectable in cells obtained from ascitic fluid from patients with ovarian tumours. CONCLUSIONS: As in many other organs, telomerase activity is increased in solid tissue specimens from malignant tumours of the female reproductive tract, but it is not yet a reliable indicator of the presence of exfoliated cancerous or precancerous cells in clinical specimens from such lesions. Interpretation should be guarded until more extensive studies have been conducted. The data on solid tissues presented here confirm that activation of this enzyme is a major hallmark of the neoplastic process.
Getting Started with Neural Models for Semantic Matching in Web Search

The vocabulary mismatch problem is a long-standing problem in information retrieval. Semantic matching holds the promise of solving the problem. Recent advances in language technology have given rise to unsupervised neural models for learning representations of words as well as bigger textual units. Such representations enable powerful semantic matching methods. This survey is meant as an introduction to the use of neural models for semantic matching. To remain focused we limit ourselves to web search. We detail the required background and terminology, a taxonomy grouping the rapidly growing body of work in the area, and then survey work on neural models for semantic matching in the context of three tasks: query suggestion, ad retrieval, and document retrieval. We include a section on resources and best practices that we believe will help readers who are new to the area. We conclude with an assessment of the state-of-the-art and suggestions for future work.
Critical analysis of HPL performance under different process distribution patterns

High Performance Linpack (HPL) benchmark is a standard tool to measure the performance of High Performance Computing Clusters (HPCC). There are several parameters which can be optimized to maximize performance delivered by HPCC. HPL provides many such parameters for evaluation of performance. P & Q are two such values which determine the distribution pattern of processes for executing HPL. In this paper HPL runs with different values of P and Q have been carried out for three different values of N while keeping the block size (NB) constant. Value of N represents the problem size of task being executed. Results obtained are included in tables and are also depicted in form of graph and are analytically discussed. These results also provide the basis for deeper analytical approaches for HPCC performance evaluations. This critical analysis also reveals that maximum performance is delivered if the task is evenly distributed over all the available cores and nodes in the HPCC.
Morphological Analysis of the Dravidian Language Family

The Dravidian languages are one of the most widely spoken language families in the world, yet there are very few annotated resources available to NLP researchers. To remedy this, we create DravMorph, a corpus annotated for morphological segmentation and part-of-speech. Additionally, we exploit novel features and higher-order models to set state-of-the-art results on these corpora on both tasks, beating techniques proposed in the literature by as much as 4 points in segmentation F1.
Centralized vulnerability database for organization specific automated vulnerabilities discovery and supervision

Software Vulnerabilities have been a major concern for enterprises for evaluating vulnerabilities of their software products. For assessing vulnerabilities there are various sites to look upon and search for exposures related to various software products. When vulnerability is detected and exposed on vulnerability database; discovery, analysis and redressal through manual intervention is too moderate, tedious and might not be viable. The purpose of this research is to suggest a method for creation of an effective process of gathering vulnerability information from various vulnerability databases, making it organization specific, classifying and ordering for easy accessibility to the system administrators. Integration of existing open vulnerabilities databases permits to build the likelihood of discovery of vulnerable software and hardware that are utilized as a part of software systems and enhance the quality of security analysis. This will ease the job of system administrator from scanning all vulnerability databases manually and save their time and effort.
Navigation on Self-Organized Networks

On a locally finite point set, a navigation defines a path through the point set from a point to an other. The set of paths leading to a given point defines a tree, the navigation tree. In this article, we analyze the properties of the navigation tree when the point set is a Poisson point process on Rd. We examine the distribution of stable functionals, the local weak convergence of the navigation tree, the asymptotic average of a functional along a path, the shape of the navigation tree and its topological ends. We illustrate our work in the small world graphs, and new results are established. This work is motivated by applications in computational geometry and in self-organizing networks.
Long-term psychosocial impact reported by childhood critical illness survivors: a systematic review

Aim To undertake a qualitative systematic review that explores psychological and social impact, reported directly from children and adolescents at least 6 months after their critical illness. Background Significant advances in critical care have reduced mortality from childhood critical illness, with the majority of patients being discharged alive. However, it is widely reported that surviving critical illness can be traumatic for both children and their family. Despite a growing body of literature in this field, the psychological and social impact of life threatening critical illness on child and adolescent survivors, more than 6 months post event, remains under-reported. Data sources Searches of six online databases were conducted up to February 2012. Review methods Predetermined criteria were used to select studies. Methodological quality was assessed using a standardized checklist. An adapted version of the thematic synthesis approach was applied to extract, code and synthesize data. Findings Three studies met the inclusion criteria, which were all of moderate methodological quality. Initial coding and synthesis of data resulted in five descriptive themes: confusion and uncertainty, other people's narratives, focus on former self and normality, social isolation and loss of identity, and transition and transformation. Further synthesis culminated in three analytical themes that conceptualize the childhood survivors' psychological and social journey following critical illness. Conclusions Critical illness in childhood can expose survivors to a complex trajectory of recovery, with enduring psychosocial adversity manifesting in the long term. Nurses and other health professionals must be aware and support the potential multifaceted psychosocial needs that may arise. Parents and families are identified as fundamental in shaping psychological and social well-being of survivors. Therefore intensive care nurses must take opportunities to raise parents' awareness of the journey of survival and provide appropriate support. Further empirical research is warranted to explore the deficits identified with the existing literature.
Towards Wide-angle Micro Vision Sensors

Achieving computer vision on micro-scale devices is a challenge. On these platforms, the power and mass constraints are severe enough for even the most common computations (matrix manipulations, convolution, etc.) to be difficult. This paper proposes and analyzes a class of miniature vision sensors that can help overcome these constraints. These sensors reduce power requirements through template-based optical convolution, and they enable a wide field-of-view within a small form through a refractive optical design. We describe the trade-offs between the field of view, volume, and mass of these sensors and we provide analytic tools to navigate the design space. We demonstrate milli-scale prototypes for computer vision tasks such as locating edges, tracking targets, and detecting faces. Finally, we utilize photolithographic fabrication tools to further miniaturize the optical designs and demonstrate fiducial detection onboard a small autonomous air vehicle.
The human pathogen Pseudomonas aeruginosa utilizes conserved virulence pathways to infect the social amoeba Dictyostelium discoideum

Genetically accessible host models are useful for studying microbial pathogenesis because they offer the means to identify novel strategies that pathogens use to evade immune mechanisms, cause cellular injury, and induce disease. We have developed conditions under which the human pathogen Pseudomonas aeruginosa infects Dictyostelium discoideum, a genetically tractable eukaryotic organism. When D. discoideum is plated on nutrient agar plates with different P. aeruginosa strains, the bacteria form lawns on these plates with amoebae embedded in them. Virulent P. aeruginosa strains kill these amoebae and leave an intact bacterial lawn. A number of P. aeruginosa mutants have been identified that are avirulent in this assay. Amoebae feed on these bacteria and form plaques in their bacterial lawns. One avirulent mutant strain carries an insertional mutation in the lasR gene. LasR is a transcription factor that controls a number of virulence genes in a density-dependent fashion. Another class of avirulent P. aeruginosa mutants is defective in type III secretion. One mutant lacks the PscJ protein, a structural component of the secretion apparatus, suggesting that cytotoxins are injected into the D. discoideum cell. One of these cytotoxins is ExoU, and exoU mutants are avirulent toward D. discoideum. Complementation of the lasR and exoU mutations restores virulence. Therefore, P. aeruginosa uses conserved virulence pathways to kill D. discoideum.
Energy-Efficient Management of Virtual Machines in Eucalyptus

In this paper, an approach for improving the energy efficiency of infrastructure-as-a-service clouds is presented. The approach is based on performing live migrations of virtual machines to save energy. In contrast to related work, the energy costs of live migrations including their pre- and post-processing phases are taken into account, and the approach has been implemented in the Eucalyptus open-source cloud computing system by efficiently combining a multi-layered file system and distributed replication block devices. To evaluate the proposed approach, several short- and long-term tests based on virtual machine workloads produced with common operating system benchmarks, web-server emulations as well as different MapReduce applications have been conducted. The results indicate that energy savings of up to 16 percent can be achieved in a productive Eucalyptus environment.
D-branes in PP-Waves and Massive Theories on Worldsheet with Boundary

We investigate the supersymmetric D-brane configurations in the pp-wave backgrounds proposed by Maldacena and Maoz. We study the surviving supersymmetry in a D-brane configuration from the worldvolume point of view. When we restrict ourselves to the background with = (2,2) supersymmetry and no holomorphic Killing vector term, there are two types of supersymmetric D-branes: A-type and B-type. An A-type brane is wrapped on a special lagrangian submanifold, and the imaginary part of the superpotential should be constant on its worldvolume. On the other hand, a B-type brane is wrapped on a complex submanifold, and the superpotential should be constant on its worldvolume. The results are almost consistent with the worldsheet theory in the lightcone gauge. The inclusion of gauge fields is also discussed and found BPS D-branes with the gauge field excitations. Furthermore, we consider the backgrounds with holomorphic Killing vector terms and = (1,1) supersymmetric backgrounds.