Miracle-dz/UniFAR-FTUs huggingface dataset:
A Diphone{based Text-to-speech System for Scottish Gaelic

In this thesis, a diphone{based text{to{speech system for Scottish Gaelic, a language spoken by about 80.000 native speakers in Scotland and Canada, is presented. Text{ to{speech systems convert orthographic text input into speech output. The present system consists of two main parts: an automatic phonetic transcription module which produces an orthophonic transcription of the orthographic input text a speech synthesis module which synthesizes an utterance from its transcription by concatenating and modifying previously recorded speech units. Diphones, speech units that cover two sounds and the transition between them, form the basis of the synthesis module. Duration and intonation are modelled on the basis of simple heuristics. The diphone inventory was designed for the Gaelic of Bayble, Lewis. Scottish Gaelic distinguishes four main phonetic settings: velarised, palatalised, nasalised, and neutral. As the domain of these settings is the syllable, they are di cult to model using diphone{sized units. The development of a text{to{speech system for a minority language presents speci c problems: not only are throrough modern linguistic descriptions rare, but machinereadable resources are also scarce to nonexistent. This complicates not only inventory design, but also the creation of the transcription module. There is rarely enough time and information to build fullyedged machine readable pronunciation lexica. Therefore, this thesis explores to what extent automatic transcription modules, trained on a very small amout of data, can supplement an existing small lexicon. It was found that feedforward arti cial neural networks perform slightly worse on both training and test data than decision trees and signi cantly worse than nearest neighbour{based classi ers. We conclude that nearest neighbour classi ers or, when memory is scarce, decision trees, are the method of choice, since they are easy to train and do not require an extensive search in parameter and initialisation space to nd the best model. i
Itraconazole in chronic pulmonary aspergillosis: In whom, for how long, and at what dose?

309 cavity. CNPA is a semi-invasive form of pulmonary aspergillosis, which occurs in patients with mild forms of immunodeficiency (diabetes, malnutrition, steroid use) or structural lung diseases (COPD, post-tubercular sequelae). It presents as a subacute debilitating respiratory illness progressing over one to three months. The radiological features include cavities with pericavitary infiltrates and slow expansion and formation of new cavities, with or without fungal balls. Several experts identify another indolent form of chronic aspergillosis, namely, complex aspergilloma or chronic cavitary pulmonary aspergillosis (CCPA). [10] CCPA also presents with non-specific respiratory and constitutional symptoms, but has a presentation more indolent than CNPA (over months to years). The radiological manifestations include the presence of slowly expanding cavities with surrounding fibrosis (or rarely consolidation), with or without the presence of one or more fungal balls. In contrast to CNPA, there is little or no invasion of the surrounding lung parenchyma. Many authors do not differentiate between CCPA and CNPA and christen them together as CPA. However, we feel that a differentiation between the two is essential because of the different treatment implications.
The Linked Data Visualization Model

The potential of the semantic data available in the Web is enormous but in most cases it is very difficult for users to explore and use this data. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. We devise a formal Linked Data Visualization model (LDVM), which allows to dynamically connect data with visualizations.
Activities of glutamate dehydrogenase and aspartate and alanine aminotransferases in freshwater snails Helisoma duryi and Lymnaea natalensis exposed to copper

In this paper we investigate the potential of glutamate dehydrogenase (GDH) and aspartate and alanine aminotransferases (AST and ALT) as biomarkers of water pollution due to copper in the freshwater snails Helisoma duryi and Lymnaea natalensis. Snails were dosed with copper(II) ion concentrations of 0.01, 0.1 and 1 mg kg-1 breeding water for a period of 96 h, after which those surviving were shelled. The copper content in the breeding water, in whole snail tissue and in the snail shells was determined at the end of the period of exposure. For enzyme determinations, whole snail tissue was first homogenized and fractionated by centrifugation at 500 g to remove the nuclei. The resulting supernatant was then centrifuged at 10 000 g to give a pellet fraction representing the mitochondrial fraction and a supernatant representing the cytosolic fraction. Copper was very toxic to both snail species at concentrations above 0.2 mg l-1, with only 3% of the Helisoma and 12% of the Lymnaea surviving at concentrations of approximately 1 mg l-1. The copper content in the shells and tissues of snails rose with increasing copper concentration in the breeding water, and was 2.1- to 4.9-fold in snails exposed to copper ion at a dose of 1 mg kg-1 water compared with undosed snails. Similarly, the activities of GDH and AST rose by up to 4.7-fold in the homogenate and the mitochondrial and cytosolic fractions with increasing concentrations of copper. These activities, however, fell at copper concentrations of approximately 1 mg l-1, which coincided with massive death of snails. Mitochondrial ALT disappeared at copper ion concentrations of approximately 0.2 mg l-1 for Lymnaea and 1 mg l-1 for Helisoma, possibly indicating mitochondrial degeneration. These results show that GDH, AST and ALT have the potential to be biomarkers of suplethal copper pollution in these two snail species, since their activities were significantly altered by low copper concentrations.
Early Recognition of Human Activities from First-Person Videos Using Onset Representations

In this paper, we propose a methodology for early recognition of human activities from videos taken with a first-person viewpoint. Early recognition, which is also known as activity prediction, is an ability to infer an ongoing activity at its early stage. We present an algorithm to perform recognition of activities targeted at the camera from streaming videos, making the system to predict intended activities of the interacting person and avoid harmful events before they actually happen. We introduce the novel concept of 'onset' that efficiently summarizes pre-activity observations, and design an approach to consider event history in addition to ongoing video observation for early first-person recognition of activities. We propose to represent onset using cascade histograms of time series gradients, and we describe a novel algorithmic setup to take advantage of onset for early recognition of activities. The experimental results clearly illustrate that the proposed concept of onset enables better/earlier recognition of human activities from first-person videos.
The authentication method in wireless sensor network based on trust model

Existing wireless sensor network are developing rapidly and soon will occupy a dominant place among the data collection and communication. The remote location of the sensors and automatic operation increases their vulnerability to outside intrusions and attacks. Because of out of constant sensor supply the providing of authentication is quite challenging whereas the best protocols is negotiated sensor capabilities. The method of sensor authentication in the wireless sensor networks, which is based on a model of trust, is proposed.
The Structural Basis for the Elastolytic Activity of the 92-kDa and 72-kDa Gelatinases

Several matrix metalloproteinases, including the 92-kDa and 72-kDa gelatinases, macrophage metalloelastase (MME), and matrilysin degrade insoluble elastin. Because elastolytically active MME and matrilysin consist only of a catalytic domain (CD), we speculated that the homologous CDs of the 92-kDa and 72-kDa gelatinases would confer their elastolytic activities. In contrast to the MME CD, the 92 and 72 CDs expressed in Escherichia coli (lacking the internal fibronectin type II-like repeats) had no elastase activity, although both were gelatinolytic and cleaved a thiopeptolide substrate at rates comparable to the full-length gelatinases. To test the role of the fibronectin type II-like repeats in elastolytic activity, we expressed the 92-kDa gelatinase CD with its fibronectin type II-like repeats (92 CD/FN) in yeast. 92 CD/FN degraded insoluble elastin with activity comparable to full-length 92-kDa gelatinase. 92 and 72 CDs lacking the fibronectin type II-like repeats did not bind elastin, whereas the parent enzymes and 92 CD/FN did bind elastin. Furthermore, recombinant 92-kDa fibronectin type II-like repeats inhibited binding of the 92-kDa gelatinase to elastin. We conclude that the 92- and 72-kDa gelatinases require the fibronectin type II-like repeats for elastase activity.
The Arabidopsis PEPR pathway couples local and systemic plant immunity

Recognition of microbial challenges leads to enhanced immunity at both the local and systemic levels. In Arabidopsis, EFR and PEPR1/PEPR2 act as the receptor for the bacterial elongation factor EF‐Tu (elf18 epitope) and for the endogenous PROPEP‐derived Pep epitopes, respectively. The PEPR pathway has been described to mediate defence signalling following microbial recognition. Here we show that PROPEP2/PROPEP3 induction upon pathogen challenges is robust against jasmonate, salicylate, or ethylene dysfunction. Comparative transcriptome profiling between Pep2‐ and elf18‐treated plants points to co‐activation of otherwise antagonistic jasmonate‐ and salicylate‐mediated immune branches as a key output of PEPR signalling. Accordingly, as well as basal defences against hemibiotrophic pathogens, systemic immunity is reduced in pepr1 pepr2 plants. Remarkably, PROPEP2/PROPEP3 induction is essentially restricted to the pathogen challenge sites during pathogen‐induced systemic immunity. Localized Pep application activates genetically separable jasmonate and salicylate branches in systemic leaves without significant PROPEP2/PROPEP3 induction. Our results suggest that local PEPR activation provides a critical step in connecting local to systemic immunity by reinforcing separate defence signalling pathways.
Production of vanillin

PURPOSE: To provide a method for producing vanillin from a natural vanillin precursor in a high yield by a bioconversion process. CONSTITUTION: This method for producing vanillin comprises bringing a bioconversion mixture containing a water-soluble solution of a vanillin precursor into contact with a ferulic acid degrading microorganism in the presence of a mercapto compound and optically an assimilable carbon source. COPYRIGHT: (C)1993,JPO
Noise-robust voice conversion using a small parallel data based on non-negative matrix factorization

This paper presents a novel framework of voice conversion (VC) based on non-negative matrix factorization (NMF) using a small parallel corpus. In our previous work, a VC technique using NMF for noisy environments has been proposed, and it requires parallel exemplars (dictionary), which con sist of the source exemplars and target exemplars, having the same texts uttered by the source and target speakers. The large parallel corpus is used to construct a conversion function in NMF-based VC (in the same way as common GMM-based VC). In this paper, an adaptation matrix in an NMF frame work is introduced to adapt the source dictionary to the target dictionary. This adaptation matrix is estimated using a small parallel speech corpus only. The effectiveness of this method is confirmed by comparing its effectiveness with that of a con ventional NMF-based method and a GMM-based method in a noisy environment.
Automatic Measurement of Traffic State Parameters Based on Computer Vision for Intelligent Transportation Surveillance

Online automatic measurement of traffic state parameters has important significance for intelligent transportation surveillance. The video-based monitoring technology is widely studied today but the existing methods are not satisfactory at processing speed or accuracy, especially for traffic scenes with traffic congestion or complex road environments. Based on technologies of computer vision and pattern recognition, this paper proposes a novel measurement method that can detect multiple parameters of traffic flow and identify vehicle types from video sequence rapidly and accurately by combining feature points detection with foreground temporal-spatial image (FTSI) analysis. In this method, two virtual detection lines (VDLs) are first set in frame images. During working, vehicular feature points are extracted via the upstream-VDL and grouped in unit of vehicle based on their movement differences. Then, FTSI is accumulated from video frames via the downstream-VDL, and adhesive blobs of occlusion vehicles in.
Nonlinear effects of group size on the success of wolves hunting elk

Despite the popular view that social predators live in groups because group hunting facilitates prey capture, the apparent tendency for hunting success to peak at small group sizes suggests that the formation of large groups is unrelated to prey capture. Few empirical studies, however, have tested for nonlinear relationships between hunting success and group size, and none have demonstrated why success trails off after peaking. Here, we use a unique dataset of observations of individually known wolves (Canis lupus) hunting elk (Cervus elaphus) in Yellowstone National Park to show that the relationship between success and group size is indeed nonlinear and that individuals withholding effort (free riding) is why success does not increase across large group sizes. Beyond 4 wolves, hunting success leveled off, and individual performance (a measure of effort) decreased for reasons unrelated to interference from inept hunters, individual age, or size. But performance did drop faster among wolves with an incentive to hold back, i.e., nonbreeders with no dependent offspring, those performing dangerous predatory tasks, i.e., grabbing and restraining prey, and those in groups of proficient hunters. These results suggest that decreasing performance was free riding and that was why success leveled off in groups with >4 wolves that had superficially appeared to be cooperating. This is the first direct evidence that nonlinear trends in group hunting success reflect a switch from cooperation to free riding. It also highlights how hunting success per se is unlikely to promote formation and maintenance of large groups.
Influenza estacional en adultos y niños—Diagnóstico, tratamiento, quimioprofilaxis y control de brotes institucionales: Guías de práctica clínica de la Sociedad de Enfermedades Infecciosas de Estados Unidos de América

Abstract Un Grupo de Expertos de la Sociedad de Enfermedades Infecciosas de los Estados Unidos de América elaboró las guias para el tratamiento de personas infectadas por el virus de la influenza. Estas guias basadas en datos y pruebas cientificas comprenden el diagnóstico, el tratamiento y la quimioprofilaxis con medicamentos antivirales, además de temas relacionados con el control de brotes de influenza estacional (interpandémicas) en ámbitos institucionales. Están destinadas a los médicos de todas las especialidades a cargo de la atención directa de pacientes porque los médicos generales que atienden una gran variedad de casos son los que se enfrentan con la influenza, frecuente en el ámbito comunitario durante la temporada de influenza.
Clinical Significance of Tryptophan Metabolism in the Nontumoral Hemisphere in Patients with Malignant Glioma

α-11C-methyl-l-tryptophan (AMT) PET allows evaluation of brain serotonin synthesis and can also track upregulation of the immunosuppressive kynurenine pathway in tumor tissue. Increased AMT uptake is a hallmark of World Health Organization grade III–IV gliomas. Our recent study also suggested decreased frontal cortical AMT uptake in glioma patients contralateral to the tumor. The clinical significance of extratumoral tryptophan metabolism has not been established. In the present study, we investigated clinical correlates of tryptophan metabolic abnormalities in the nontumoral hemisphere of glioma patients. Methods: Standardized AMT uptake values (SUVs) and the uptake rate constant of AMT (K [mL/g/min], a measure proportional to serotonin synthesis in nontumoral gray matter) were quantified in the frontal and temporal cortex and thalamus in the nontumoral hemisphere in 77 AMT PET scans of 66 patients (41 men, 25 women; mean age ± SD, 55 ± 15 y) with grade III–IV gliomas. These AMT values were determined before treatment in 35 and after treatment in 42 patients and were correlated with clinical variables and survival. Results: AMT uptake in the thalamus showed a moderate age-related increase before treatment (SUV, r = 0.39, P = 0.02) but decrease after treatment (K, r = −0.33, P = 0.057). Women had higher thalamic SUVs before treatment (P = 0.037) and higher thalamic (P = 0.013) and frontal cortical K values (P = 0.023) after treatment. In the posttreatment glioma group, high thalamic SUVs and high thalamocortical SUV ratios were associated with short survival in Cox regression analysis. The thalamocortical ratio remained strongly prognostic (P < 0.01) when clinical predictors, including age, glioma grade, and time since radiotherapy, were entered in the regression model. Long interval between radiotherapy and posttreatment AMT PET as well as high radiation dose affecting the thalamus were associated with lower contralateral thalamic or cortical AMT uptake values. Conclusion: These observations provide evidence for altered tryptophan uptake in contralateral cortical and thalamic brain regions in glioma patients after initial therapy, suggesting treatment effects on the serotonergic system. Low thalamic tryptophan uptake appears to be a strong, independent predictor of long survival in patients with previous glioma treatment.
T Regulatory Cell Adoptive Therapy for Tolerance Induction in Autoimmunity and Transplantation

Host environment is often an overlooked hurdle that needs to be understood in order to have successful therapies without the need for chronic immunosuppression. Many clinical trials for recent onset type 1 diabetic (T1D) patients are utilizing immunomodulation therapies that may favor T regulatory (Treg) expansion and temper T effector (Teff) responses, but their efficacy has been limited in magnitude and duration. Tolerance induction protocols in the transplant setting have also shown to require therapy that favors Treg expansion/stimulation, while inhibiting alloreactive Teff responses (1,2). Our study addressed key questions of how to develop strategies that facilitate long-term engraftment and function of Treg therapeutic infusions.
The Ability of 3D Alginate/Polyvinyl Alcohol Cross-Linked Hybrid Hydrogel to Differentiate Periodontal Ligament Stem Cells Into Osteoblasts

Porous alginate/polyvinyl alcohol hybrid scaﬀolds have been extensively used in cartilage, bone, and dental tissue substitute applications. However, its mechanical and osteogenesis properties are not good enough to meet the requirement for use in hard tissues repair applications. In this study, to achieve the best mechanical and physical properties, we carried out the cross-linking of PVA physically and alginate chemically. Hydroxyapatite nanoparticles (nHA), the important component of hard tissues, was added to the hydrogel to improve its mechanical properties and osteoconductivity. The results showed that the fabricated algi-nate/polyvinyl alcohol-nHA scaﬀold has around 81% interconnected porosity, hydrophilic surface with the contact angle of water on the surface in the range of 38 ± 0.29°, 3.51 MPa compressive strength, and a degradation rate of 71%. The periodontal ligament stem cells (PDLSCs) culture results showed that both fabricated alginate/polyvinyl alcohol hybrid scaﬀolds with and without nHA hadgoodcellattachmentabilityandcouldpromotePDLSCsingrowth. Thereal-timeRT-PCRassayshowedthatthepresenceof nHA inthealginate/polyvinylalcoholhybridscaﬀoldcouldsigniﬁcantlyacceleratetheexpressionof speciﬁcmarkersof pre-andmature osteoblaststagessuchasosteocalcin,alkalinephosphate,andosteopontingenes. Theseresultsshowedthatalginate/polyvinylalco-hol hybrid scaﬀolds with hydroxyapatite nanoparticles can be used in bone and dental substitute applications as osteoconductive and reinforcement components.
Analysis of Some Selected Numerical Methods in Solving Second Degree Non-Linear Equations

Over the years, we have been taught on how to solve equations using various algebraic methods. These methods include the substitution method and the elimination method. Other algebraic methods that can be executed include the quadratic formula and factorization. In Linear Algebra, we learned that solving systems of linear equations can be implemented by using row reduction as an algorithm. However, when these methods are not successful, we use the concept of numerical methods.
Modeling Multivariate Time Series in Economics: From Auto-Regressions to Recurrent Neural Networks

The modeling of multivariate time series in an agnostic manner, without assumptions about underlying theoretical structure is traditionally conducted using Vector Auto-Regressions. They are well suited for linear and state-independent evolution. A more general methodology of Multivariate Recurrent Neural Networks allows to capture non-linear and state-dependent dynamics. This paper takes a range of small- to large-scale Long Short-Term Memory MRNNs and pits them against VARs in an application to US data on GDP growth, inflation, commodity prices, Fed Funds rate and bank reserves. Even in a small-sample regime, MRNN outperforms VAR in forecasting: its out-of-sample predictions are about 20% more accurate. MRNN also fares better in interpretability by means of impulse response functions: for instance, a temporary shock to the Fed Funds rate variable generates system dynamics that are more plausible according to conventional economic theory.
Peroxisome proliferator-activated receptor-gamma C190S mutation causes partial lipodystrophy.

CONTEXT Mutations in PPARG are associated with insulin resistance and familial partial lipodystrophy, a disease characterized by altered distribution of sc fat and symptoms of the metabolic syndrome. The encoded protein, peroxisome proliferator-activated receptor (PPAR)-gamma, plays a pivotal role in regulating lipid and glucose metabolism, the differentiation of adipocytes, and other cellular regulatory processes. OBJECTIVES The objective of the study was to detect a novel PPARG mutation in a kindred with partial lipodystrophy and analyze the functional characteristics of the mutant protein. PATIENTS AND METHODS In three subjects with partial lipodystrophy, one unaffected family member, and 124 unaffected subjects, PPARG was screened for mutations by direct sequencing. Body composition, laboratory abnormalities, and hepatic steatosis were assessed in each affected subject. Transcriptional activity was determined, and EMSA was performed to investigate DNA binding capacity of the mutant protein. RESULTS We identified a PPARG mutation, C190S, causing partial lipodystrophy with metabolic alterations in three affected family members. The mutation was absent in the unaffected family member and unaffected controls. The mutation is located within zinc-finger 2 of the DNA binding domain. C190S PPARgamma has a significantly lower ability to activate a reporter gene than wild-type PPARgamma in absence and presence of rosiglitazone. A dominant-negative effect was not observed. Compared with wild-type PPARgamma, C190S PPARgamma shows a reduced capacity to bind DNA. CONCLUSION Mutation of a zinc-binding amino acid of PPARgamma leads to an altered protein-DNA binding pattern, resulting in a partial loss of function, which in turn is associated with partial lipodystrophy.