Miracle-dz/UniFAR-FTUs huggingface dataset:
The Scattering Matrix Approach for the Quantum Black Hole an Overview

If one assumes the validity of conventional quantum field theory in the vicinity of the horizon of a black hole, one does not find a quantum mechanical description of the entire black hole that even remotely resembles that of conventional forms of matter; in contrast with matter made out of ordinary particles one finds that, even if embedded in a finite volume, a black hole would be predicted to have a strictly continuous spectrum. Dissatisfied with such a result, which indeed hinges on assumptions concerning the horizon that may well be wrong, various investigators have now tried to formulate alternative approaches to the problem of " quantizing " the black hole. We here review the approach based on the assumption of quantum mechanical purity and unitarity as a starting point, as has been advocated by the present author for some time, concentrating on the physics of the states that should live on a black hole horizon. The approach is shown to be powerful in not only producing promising models for the quantum black hole, but also new insights concerning the dynamics of physical degrees of freedom in ordinary flat space-time.
Atmospheric N Deposition Increases Bacterial Laccase-Like Multicopper Oxidases: Implications for Organic Matter Decay

ABSTRACT Anthropogenic release of biologically available nitrogen (N) has increased dramatically over the last 150 years, which can alter the processes controlling carbon (C) storage in terrestrial ecosystems. In a northern hardwood forest ecosystem located in Michigan in the United States, nearly 20 years of experimentally increased atmospheric N deposition has reduced forest floor decay and increased soil C storage. This change occurred concomitantly with compositional changes in Basidiomycete fungi and in Actinobacteria, as well as the downregulation of fungal lignocelluloytic genes. Recently, laccase-like multicopper oxidases (LMCOs) have been discovered among bacteria which can oxidize β-O-4 linkages in phenolic compounds (e.g., lignin and humic compounds), resulting in the production of dissolved organic carbon (DOC). Here, we examined how nearly 2 decades of experimental N deposition has affected the abundance and composition of saprotrophic bacteria possessing LMCO genes. In our experiment, LMCO genes were more abundant in the forest floor under experimental N deposition whereas the abundances of bacteria and fungi were unchanged. Experimental N deposition also led to less-diverse, significantly altered bacterial and LMCO gene assemblages, with taxa implicated in organic matter decay (i.e., Actinobacteria, Proteobacteria) accounting for the majority of compositional changes. These results suggest that experimental N deposition favors bacteria in the forest floor that harbor the LMCO gene and represents a plausible mechanism by which anthropogenic N deposition has reduced decomposition, increased soil C storage, and accelerated phenolic DOC production in our field experiment. Our observations suggest that future rates of atmospheric N deposition could fundamentally alter the physiological potential of soil microbial communities.
Experiments with Semantic Enrichment for Event Classification in Tweets

Twitter has become key for bringing awareness about real-world events, but the identification of event related posts goes beyond filtering keywords. Semantic enrichment using knowledge sources such as the Linked Open Data (LOD) cloud, has been proposed to deal with the poor textual contents of tweets for event classification. However, each work considers a particular type of event, underlined by specific assumptions according to the application purpose. In a search for an approach that suits different types of events, in this paper we identify different types of semantic features, and propose a process for semantic enrichment that involves the mapping of textual tokens into semantic concepts, the extraction of corresponding semantic properties from the LOD cloud, and their interpolation for event classification. We evaluate the contribution of each type of semantic feature using different tweet datasets representing events of distinct natures, and knowledge extracted from DBPedia.
Prognostic Value and Link to Atrial Fibrillation of Soluble Klotho and FGF23 in Hemodialysis Patients

Deranged calcium-phosphate metabolism contributes to the burden of morbidity and mortality in dialysis patients. This study aimed to assess the association of the phosphaturic hormone fibroblast growth factor 23 (FGF23) and soluble Klotho with all-cause mortality. We measured soluble Klotho and FGF23 levels at enrolment and two weeks later in 239 prevalent hemodialysis patients. The primary hypothesis was that low Klotho and high FGF23 are associated with increased mortality. The association between Klotho and atrial fibrillation (AF) at baseline was explored as secondary outcome. AF was defined as presence of paroxysmal, persistent or permanent AF. During a median follow-up of 924 days, 59 (25%) patients died from any cause. Lower Klotho levels were not associated with mortality in a multivariable adjusted analysis when examined either on a continuous scale (HR 1.25 per SD increase, 95% CI 0.84–1.86) or in tertiles, with tertile 1 as the reference category (HR for tertile two 0.65, 95% CI 0.26–1.64; HR for tertile three 2.18, 95% CI 0.91–2.23). Higher Klotho levels were associated with the absence of AF in a muItivariable logistic regression analysis (OR 0.66 per SD increase, 95% CI 0.41–1.00). Higher FGF23 levels were associated with mortality risk in a multivariable adjusted analysis when examined either on a continuous scale (HR 1.45 per SD increase, 95% CI 1.05–1.99) or in tertiles, with the tertile 1 as the reference category (HR for tertile two 1.63, 95% CI 0.64–4.14; HR for tertile three 3.91, 95% CI 1.28–12.20). FGF23 but not Klotho levels are associated with mortality in hemodialysis patients. Klotho may be protective against AF.
Distributed Medium Access Control with SDMA Support for WLANs

With simultaneous multi-user transmissions, spatial division multiple access (SDMA) provides substantial throughput gain over the single user transmission. However, its implementation in WLANs with contention-based IEEE 802.11 MAC remains challenging. Problems such as coordinating and synchronizing the multiple users need to be solved in a distributed way. In this paper, we propose a distributed MAC protocol for WLANs with SDMA support. A dual-mode CTS responding mechanism is designed to accomplish the channel estimation and user synchronization required for SDMA. We analytically study the throughput performance of the proposed MAC, and dynamic parameter adjustment is designed to enhance the protocol efficiency. In addition, the proposed MAC protocol does not rely on specific physical layer realizations, and can work on legacy IEEE 802.11 equipment with slight software updates. Simulation results show that the proposed MAC outperforms IEEE 802.11 significantly, and that the dynamic parameter adjustment can effectively track the load variation in the network.
Use of Selective Capture of Transcribed Sequences To Identify Genes Preferentially Expressed by Streptococcus suis upon Interaction with Porcine Brain Microvascular Endothelial Cells

ABSTRACT By using the selective capture of transcribed sequences (SCOTS) approach, we identified 28 genes preferentially expressed by the major swine pathogen and zoonotic agent Streptococcus suis upon interaction with porcine brain microvascular endothelial cells. Several of these genes may be considered new S. suis candidate virulence factors. Results from this study demonstrate the suitability of SCOTS for the elucidation of gene expression in streptococcal species and may contribute to a better understanding of the pathogenesis of S. suis infections.
TransBooster: boosting the performance of wide-coverage machine translation systems

We propose the design, implementation and evaluation of a novel and modular approach to boost the translation performance of existing, wide-coverage, freely available machine translation systems based on reliable and fast automatic decomposition of the translation input and corresponding composition of translation output. We provide details of our method, and experimental results compared to the MT systems SYSTRAN and Logomedia. While many avenues for further experimentation remain, to date we fall just behind the baseline systems on the full 800-sentence testset, but in certain cases our method causes the translation quality obtained via the MT systems to improve.
Combinatory Categorial Grammars: Generative Power and Relationship to Linear Context-Free Rewriting Systems

Recent results have established that there is a family of languages that is exactly the class of languages generated by three independently developed grammar formalisms: Tree Adjoining Grammars, Head Grammars, and Linear Indexed Grammars. In this paper we show that Combinatory Categorial Grammars also generates the same class of languages. We discuss the structural descriptions produced by Combinatory Categorial Grammars and compare them to those of grammar formalisms in the class of Linear Context-Free Rewriting Systems. We also discuss certain extensions of Combinatory Categorial Grammars and their effect on the weak generative capacity.
A stochastic roadmap method to model protein structural transitions

SUMMARY Evidence is emerging that the role of protein structure in disease needs to be rethought. Sequence mutations in proteins are often found to affect the rate at which a protein switches between structures. Modeling structural transitions in wildtype and variant proteins is central to understanding the molecular basis of disease. This paper investigates an efficient algorithmic realization of the stochastic roadmap simulation framework to model structural transitions in wildtype and variants of proteins implicated in human disorders. Our results indicate that the algorithm is able to extract useful information on the impact of mutations on protein structure and function.
Optimize real-valued RBM with Bidirectional Autoencoder

Deep learning increasingly attracted attention after the fast training method of Restricted Boltzmann Machine(RBM) is proposed[1]. Many researches directly constructed deep architecture with stack RBMs to learn the representation of the data, few studied the optimization method to get good RBM parameters. Here proposes a new optimization method for real-valued RBM by minimizing the reconstructed error. Firstly, build and initialize Bidirectional Autoencoder(Bi-Ae). Secondly, minimize the cost function with Stochastic Gradient Descent (SGD) to get the parameters. Thirdly, convert the Bi-AE into RBM with the most suitable parameters. Experiments are executed on the MNIST dataset. Compared with PSO and likelihood maximum optimization methods, the reconstructed errors of the proposed method is 4.02% smaller than the result from error[1], which is advanced.
Originalia. Spiritualität im Präparierkurs

Der Kursus der Makroskopischen Anatomie ist ein wesentlicher Bestandteil des vorklinischen Medizinstudiums. Der Präparierkurs beinhaltet aber mehr als die reine Präparation: Schon immer haben wichtige, implizite Inhalte den Kurs begleitet. Spiritualität – im Sinne des Erkenntnisgewinns über sich selbst angesichts existentieller Fragen – beginnt eine Rolle zu spielen, wenn Studierende durch die Begegnung mit dem Leichnam über die Endlichkeit des Lebens reflektieren. Eine Begleitung des Präparierkurses, die diese übergeordneten Inhalte und auch die persönliche Entwicklung der Studierenden berücksichtigt, scheint uns sinnvoll und fruchtbar.
A Semi-Supervised Ensemble Learning Method for Finding Discriminative Motifs and its Application

Finding discriminative motifs has recently received much attention in bio- medicine as such motifs allow us to characterize in distinguishing two different classes of sequences. It is common in biomedical applications that the quantity of labeled se- quences is very limited while a large number of unlabeled sequences is usually available. The current methods of discriminative motif finding are powerful and effective with large labeled datasets, but they do not function well on small labeled datasets. In this paper, we present a semi-supervised ensemble method for finding discriminative motifs which is based on the SLUPC algorithm, a separate-and-conquer searching method to discover motifs of type 'discriminative one occurrence per sequence'. The proposed method, named E-SLUPC (Ensemble SLUPC), uses SLUPC to search discriminative motifs from an extended labeled dataset that contains labeled data and unlabeled data with predicted labels. Strong discriminative and frequent motifs characterizing two out- come classes of hepatitis C virus treatment (sustained viral response and non-sustained viral response) were detected and analyzed. Furthermore, the experimental evaluation shows that our method can function considerably well in the common context of med- ical research when the labeled data is usually difficult to obtain.
Image classification using tensor representation

We propose a new approach to exploit the different discriminability of image features at different scales simultaneously. By modifying the Bag-of-words model, we represent an image as a matrix whose elements are the occurrences of a set of codewords within different scale ranges. In this way, we can represent an image collection using a 3rd-order tensor. Then a new classification method, tensor-pLSA, which is an extension of Probabilistic Latent Semantic Analysis (pLSA), is introduced to classify these images based on this tensor representation. Finally, we compare the tensor representation with the original matrix representation to show the effectiveness of our approach.
Morale and Teacher Separation and Retention in Bureau of Indian Affairs Schools.

Factors that differentiate between first-year teachers whu remain for a second year and those who resign after 1 year of employment with the Bureau of Indian Affairs (BIA) schools were investigated in this 1969-70 study of BIA teachers working from the BIA area office in Gallup, New Mexico (n=78), and Aberdeen, South Dakota (n=(49). Data were collected by means of questionnaires and structured interviews. Analysis of questionnaire and interview data focused on isolating items, such as recruitment procedures, that discriminated between teachers who resigned and those who remained. Additional analyses isolated personal, sociological, and ecological variables related to teacher mobility. Findings included (1) that the BIA schools had a teacher separation rate of 36%; (2) that those individuals who had the most incongruency in areas related to their work environments were most likely to terminate employment, and (3) that termination of employment was also related to dominant career patterns. Copies of the instruments are appended. A related documer# is ED 047 857. (PS) L , . Grant OEG-0-9-460531-4562(010) TEACHER SEPARATION AND RETENTION IN BUREAU OF INDIAN AFFAIRS SCHOOLS DEPARTMENT OF HEALTH, EDUCATION 8, WELFARE OFFICE OF EDUCATION THIS DOCUMENT HAS BEEN REPROOUCED EXACTLY AS RECEIVED FROM THE PERSON OR ORGANIZATION ORIGINATING IT. POINTS OF VIEW OR OPINIONS STATED 00 NOT NECESSARILY REPRESENT OFFICIAL OFFICE OF EDUCATION POSITION OR POLICY. George Letchworth University of Oklahoma Norman, Oklahoma January 15, 1972 Pj y The research reported herein was performed pursuant to a grant with the Office of Education, U. S. Department of -ealth, Education, and Welfare. Contractors undertaking such projec s under Government' sponsorship are encouraged to express freely _air professional judgment in the conduct.of the project. Points of view or opinions stated do not, therefore, necessarily represent official Office of Education position or policy. U. S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE Office of Education Bureau of Research
Principles of appendage design in robots and animals determining terradynamic performance on flowable ground

Natural substrates like sand, soil, leaf litter and snow vary widely in penetration resistance. To search for principles of appendage design in robots and animals that permit high performance on such flowable ground, we developed a ground control technique by which the penetration resistance of a dry granular substrate could be widely and rapidly varied. The approach was embodied in a device consisting of an air fluidized bed trackway in which a gentle upward flow of air through the granular material resulted in a decreased penetration resistance. As the volumetric air flow, Q ? > , increased to the fluidization transition, the penetration resistance decreased to zero. Using a bio-inspired hexapedal robot as a physical model, we systematically studied how locomotor performance (average forward speed, v x ? > ) varied with ground penetration resistance and robot leg frequency. Average robot speed decreased with increasing Q ? > , and decreased more rapidly for increasing leg frequency, &ohgr; ? > . A universal scaling model revealed that the leg penetration ratio (foot pressure relative to penetration force per unit area per depth and leg length) determined v x ? > for all ground penetration resistances and robot leg frequencies. To extend our result to include continuous variation of locomotor foot pressure, we used a resistive force theory based terradynamic approach to perform numerical simulations. The terradynamic model successfully predicted locomotor performance for low resistance granular states. Despite variation in morphology and gait, the performance of running lizards, geckos and crabs on flowable ground was also influenced by the leg penetration ratio. In summary, appendage designs which reduce foot pressure can passively maintain minimal leg penetration ratio as the ground weakens, and consequently permits maintenance of effective locomotion over a range of terradynamically challenging surfaces.
Fast Neighborhood Subgraph Pairwise Distance Kernel

We introduce a novel graph kernel called the Neighborhood Subgraph Pairwise Distance Kernel. The kernel decomposes a graph into all pairs of neighborhood subgraphs of small radius at increasing distances. We show that using a fast graph invariant we obtain significant speed-ups in the Gram matrix computation. Finally, we test the novel kernel on a wide range of chemoinformatics tasks, from antiviral to anticarcinogenic to toxicological activity prediction, and observe competitive performance when compared against several recent graph kernel methods.
Dereplicating and Spatial Mapping of Secondary Metabolites from Fungal Cultures in Situ

Ambient ionization mass spectrometry techniques have recently become prevalent in natural product research due to their ability to examine secondary metabolites in situ. These techniques retain invaluable spatial and temporal details that are lost through traditional extraction processes. However, most ambient ionization techniques do not collect mutually supportive data, such as chromatographic retention times and/or UV/vis spectra, and this can limit the ability to identify certain metabolites, such as differentiating isomers. To overcome this, the droplet–liquid microjunction–surface sampling probe (droplet–LMJ–SSP) was coupled with UPLC–PDA–HRMS–MS/MS, thus providing separation, retention times, MS data, and UV/vis data used in traditional dereplication protocols. By capturing these mutually supportive data, the identity of secondary metabolites can be confidently and rapidly assigned in situ. Using the droplet–LMJ–SSP, a protocol was constructed to analyze the secondary metabolite profile of fungal cultures without any sample preparation. The results demonstrate that fungal cultures can be dereplicated from the Petri dish, thus identifying secondary metabolites, including isomers, and confirming them against reference standards. Furthermore, heat maps, similar to mass spectrometry imaging, can be used to ascertain the location and relative concentration of secondary metabolites directly on the surface and/or surroundings of a fungal culture.
Hubble Space Telescope ultraviolet spectroscopy of blazars: emission-line properties and black hole masses

The ultraviolet (UV) spectra of 16 blazars (<z) ≃ 1) from the archives of the Hubble Space Telescope Faint Object Spectrograph have been analysed in order to study in a systematic way the properties of their broad UV emission lines. We find that the luminosities of the most prominent and intense lines, Lyα and C IV λ1549, are similar to those of normal radio-loud quasars at comparable redshifts. However, the equivalent widths of blazar lines are significantly smaller than those of radio-loud quasars. Therefore, while the intrinsic broad-line region luminosity of blazars appears to be indistinguishable from that of radio-loud quasars, their continuum must be comparatively higher, most probably due to relativistic beaming. We have combined the UV luminosities of the debeamed continuum with the emitting gas velocity to derive estimates of the masses of the central supermassive black holes. The size of the broad-line region was computed in two ways: (1) via an empirical relationship between UV continuum luminosity and broad-line region size, and (2) through the external photon density required by blazar models to reproduce the inverse Compton components observed at γ-rays. The second method yields significantly different results from the first method, suggesting that it provides only a very rough estimate or a lower limit on the size of the broad-line region. We find that the average mass of the central black holes in blazars is ∼2.8 x 10 8 M ○. , with a large dispersion, comparable to those computed for other radio-loud active galactic nuclei.
Morphological variation in the adult hard palate and posterior pharyngeal wall.

PURPOSE Adult human vocal tracts display considerable morphological variation across individuals, but the nature and extent of this variation has not been extensively studied for many vocal tract structures. There exists a need to analyze morphological variation and, even more basically, to develop a methodology for morphological analysis of the vocal tract. Such analysis will facilitate fundamental characterization of the speech production system, with broad implications from modeling to explaining interspeaker variability. METHOD A data-driven methodology to automatically analyze the extent and variety of morphological variation is proposed and applied to a diverse subject pool of 36 adults. Analysis is focused on two key aspects of vocal tract structure: the midsagittal shape of the hard palate and the posterior pharyngeal wall. Result Palatal morphology varies widely in its degree of concavity but also in anteriority and sharpness. Pharyngeal wall morphology, by contrast, varies mostly in terms of concavity alone. The distribution of morphological characteristics is complex, and analysis suggests that certain variations may be categorical in nature. CONCLUSION Major modes of morphological variation are identified, including their relative magnitude, distribution, and categorical nature. Implications of these findings for speech articulation strategies and speech acoustics are discussed.