3D quantitative prediction can be summarized as finding the combination parts of favorable metallogenic information based on the 3D geological models and cubic block models. Based on metallogenic prediction theory, relying on 3D visualization technology, 3D database technology and statistical calculations, this paper established the technical processes of 3D quantitative prediction and evaluation of deep mineral resources which including 3D geological modeling, prospecting model establishing, mineralization favorable information analysis and 3D quantitative prediction and evaluation.The favorable metallogenic information analysis and extraction which implemented based on 3D cubic block models extended the prospecting method from 2D to 3D space, and realized the visualization of deep quantitative geological information from the 3D point of view. The method of using 3D spatial exploration flag variable to realize 3D prediction of deep concealed ore provides a new way of prospecting prediction study of deep mineral resources.
The purposes of this paper are to develop a multi-parametric protocol, which can evaluate the voice objectively and quantitatively,and to investigate its correlation with the perceptual analysis.The voice samples were collected from 83 patients with dysphonia and 40 subjects with normal voices. All the subjects were women. The objective parameters, including fundamental frequency (F0), jitter, Shimmer, fundamental frequency standard deviation (F0SD), fundamental frequency tremor, amplitude tremor, normalized noise energy (NNE), harmonic-to-noise ratio(HNR), signal-to-noise ratio(SNR) and maximal phonatory time (MPT), which were measured mainly on a sustained vowel /a/, were recorded on a software named Dr. Speech for Windows. According to the G component of the GRBAS, the voice was graded from 0 for normal to 3 for severe dysphonia.Using the discriminate analysis, a five parameters protocol (MPT, jitter, NNE, HNR and shimmer) was developed and it showed that this protocol allowed 79.8% concordance with jury classification.The voice objective analysis should be multi-parameters. Our multi-parameters evaluation protocol is able to reflect the result of perceptual analysis.
Background: There is still no clear experimental data on the relationship between the intelligibility of Chinese vocal lyrics and different pitch.Aims/Objective: This study aims at investigating the intelligibility of Chinese sung words at different pitch.Material and methods: A word list is created and sung by eight singers at five different pitches (C5, F4, bB4, bE5, and bA5). The intelligibility of the words is tested by listeners with and without music background.Results: The average intelligibility score in the music-listeners is 84.9% (SD = 9.5%). The score at five pitches (from low to high) is 93%, 91.7%, 89.7%, 83.1%, and 67.1%, respectively. The average score is 77.4% (SD = 10.7%) in the non-music listeners. The average score is 87%, 86%, 79.8%, 76.8%, and 57.5% at five pitches, respectively. The ratio of unidentified sung words is 19.3% (SD, 4.3%) in female singers and 11.9% (SD = 1.5%) in male singers.Conclusions: The intelligibility of Chinese sung words declines gradually with increase in pitch, and the extent of decreases gradually elevating. Generally, the identified ratio of words sung by male singers is higher than that of female singers. The listeners who had no musical background have a lower intelligibility score than those with experience.
Blocking Fibroblast Growth Factor Receptor 1 (FGFR1) is an attractive therapeutic option for treatment of cancer subtypes with amplification and over-expression of FGFR1. Selective targeting of FGFR1 can be achieved using an antibody-based approach, as small molecule inhibitors may not discriminate between FGFR1, 2, 3 and 4 due to their highly homologous kinase domain. However, development of classical bivalent FGFR1 directed antibodies has failed due to non-tolerated body weight decreases in preclinical species. M6123 is a novel IgG-like monovalent FGFR1 specific binder with enhanced Antibody-Dependent Cellular Cytotoxicity (ADCC) effector function and inhibits tumor growth significantly in FGFR1-dependent human xenograft models without reduced body weight in tumor-bearing mice. Toxicology studies reported here characterized the safety profile of M6123 in mouse, rat, and monkey. There were significant differences among animal species under similar M6123 exposure levels. Rats showed metastatic mineralization with an imbalance in serum phosphate at low doses, while mineralization was not found in mice or monkeys, even though hyperphosphatemia was detected in mice. Subtle differences in calcium/phosphate homoeostasis feedback loops may trigger the susceptibility to mineralization among animal species; nevertheless, the exact mechanism remains unknown. Monkeys showed marked, but reversible, decreases in peripheral blood NK cells and neutrophils. The latter was associated with considerably increased neutrophilic infiltrates in the liver sinusoids and red pulp of the spleen. These effects in monkeys are likely related to the enhanced ADCC activity of M6123. Overall, M6123 showed a superior safety profile in animals compared to bivalent FGFR1 antagonists or pan-FGFR inhibitors.
Big data has already occupied a lot in the information society. The application of big data to intelligent agriculture is the core development direction for maximizing the utilization of agricultural data information, and the deep learning method can more effectively extract abstract information from big data and convert it into useful knowledge, thus supporting the development of intelligent agriculture from different dimensions. In this paper, a CNN-RNN model is constructed based on cloud computing technology, and the parallel neural network model divided by training set is adopted to design the batch gradient descent algorithm based on deep unsupervised learning and BP algorithm based on Map-Reduce. An experiment verifies the feasibility of deep unsupervised learning neural network based on cloud computing and verifies that the optimize algorithm proposed in this paper can better increase the training efficiency of neural network.
Nous proposons un bilan methodologique fonde sur differentes experiences effectuees dans notre groupe de travail sur l'evaluation des troubles de la voix. Un premier axe d'etude a mis en parallele un jugement perceptif de la qualite vocale de 449 participants (incluant 391 patients dysphoniques) avec des mesures instrumentales acoustique et aerodynamique effectuees sur le meme groupe. Les resultats montrent que la combinaison de 7 parametres instrumentaux permettent de classer 82 % des participants dans le meme groupe que le jugement perceptif. Le deuxieme axe d'etude, complementaire, concerne l'adaptation de techniques de Reconnaissance Automatique du Locuteur a la categorisation des dysphonies. Le systeme developpe pour cette tâche est fonde sur une approche a base de GMM. Les experiences conduites sur 80 voix de femmes ont fourni des resultats plus que prometteurs et ont souligne l'interet d'une telle approche originale. Nous profiterons de la multiplicite de ces moyens experimentaux pour faire un point methodologique qui pointe des differences fondamentales entre ces approches complementaires (montante vs descendante, globale vs analytique). Nous discuterons aussi d'aspects theoriques notamment sur les relations entre mesures physiques et mecanismes de perception, considerations qui sont souvent mises de cote du fait de la course a la performance.
This paper describes two comparative studies of voice quality assessment based on complementary approaches. The first study was undertaken on 449 speakers (including 391 dysphonic patients) whose voice quality was evaluated in parallel by a perceptual judgment and objective measurements on acoustic and aerodynamic data. Results showed that a nonlinear combination of 7 parameters allowed the classification of 82% voice samples in the same grade as the jury. The second study relates to the adaptation of Automatic Speaker Recognition (ASR) techniques to pathological voice assessment. The system designed for this particular task relies on a GMM based approach, which is the state-of-the-art for ASR. Experiments conducted on 80 female voices provide promising results, underlining the interest of such an approach. We benefit from the multiplicity of theses techniques to evaluate the methodological situation which points fundamental differences between these complementary approaches (bottom-up vs. top-down, global vs. analytic). We also discuss some theoretical aspects about relationship between acoustic measurement and perceptual mechanisms which are often forgotten in the performance race.
Atacicept, a soluble recombinant fusion protein of the human immunoglobulin (Ig) G(1) Fc and the extracellular domain of the human transmembrane activator and calcium modulator and cyclophylin ligand interactor receptor, acts as an antagonist of both B lymphocyte stimulator and a proliferating-inducing ligand. Here we determined the nonclinical safety, pharmacokinetics and pharmacodynamics of atacicept in mice and cynomolgus monkeys. Subcutaneous atacicept treatment (twice weekly in cynomolgus monkeys, three times weekly in mice) was generally safe and well tolerated safe and well tolerated with dosing up to 10 mg/kg every other day for up to 39 weeks or up to 80 mg/kg when dosed for 4 weeks. At a dose of 1 mg/kg subcutaneous (sc) bioavailability of atacicept in mice and monkeys was 76 and 92%, with a mean serum t(1/2) of 44 and 179 h, respectively. In accord with its anticipated mechanism of action, repeated administration of atacicept decreased serum IgG concentrations up to 50%, IgM concentrations >99%, and circulating mature B-cell concentrations up to 60%. These effects were dose-related but reversible, as determined in a 25-week follow-up period. Microscopically, B cells numbers were reduced in the follicular marginal zone of the spleen and the mantle surrounding germinal centers of the lymph nodes. These data confirm the preclinical safety and the pharmacological activity of atacicept and support its clinical development.
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