Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving RNN-T ASR Accuracy Using Untranscribed Context Audio

We present a new training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to benefit from longer audio streams as input, while only requiring partial transcriptions of such streams during training. We show that this extension of the acoustic context during training and inference can lead to word error rate reductions of more than 6% in a realistic production setting. We investigate its effect on acoustically challenging data containing background speech and present data points which indicate that this approach helps the network learn both speaker and environment adaptation. Finally, we visualize RNN-T loss gradients with respect to the input features in order to illustrate the ability of a long short-term memory (LSTM) based ASR encoder to exploit long-term context.
Seismic Facies Analysis: A Deep Domain Adaptation Approach

Deep neural networks (DNNs) can learn accurately from large quantities of labeled input data, but often fail to do so when labelled data are scarce. DNNs sometimes fail to generalize ontest data sampled from different input distributions. Unsupervised Deep Domain Adaptation (DDA) techniques have been proven useful when no labels are available, and when distribution shifts are observed in the target domain (TD). In the present study, experiments are performed on seismic images of the F3 block 3D dataset from offshore Netherlands (source domain; SD) and Penobscot 3D survey data from Canada (target domain; TD). Three geological classes from SD and TD that have similar reflection patterns are considered. A deep neural network architecture named EarthAdaptNet (EAN) is proposed to semantically segment the seismic images when few classes have data scarcity, and we use a transposed residual unit to replace the traditional dilated convolution in the decoder block. The EAN achieved a pixel-level accuracy >84% and an accuracy of ~70% for the minority classes, showing improved performance compared to existing architectures. In addition, we introduce the CORAL (Correlation Alignment) method to the EAN to create an unsupervised deep domain adaptation network (EAN-DDA) for the classification of seismic reflections from F3 and Penobscot, to demonstrate possible approaches when labelled data are unavailable. Maximum class accuracy achieved was ~99% for class 2 of Penobscot, with an overall accuracy>50%. Taken together, the EAN-DDA has the potential to classify target domain seismic facies classes with high accuracy.
A spectral method algorithm for numerical simulations of gravitational fields

A numerical study of the Einstein field equations, based on the 3 + 1 foliation of the spacetime, is presented. A pseudo-spectral technique has been employed for simulations in vacuum, within two different formalisms, namely the Arnowitt–Deser–Misner (ADM) and the conformal Baumgarte–Shapiro–Shibata–Nakamura (BSSN) approach. The numerical code is based on the Fourier decomposition, accompanied by different filtering techniques. The role of the dealiasing, as well as the influence of the filter type, has been investigated. The algorithms have been stabilized via a novel procedure that controls self-consistently the regularity of the solutions. The accuracy of the model has been validated through standard testbeds, revealing that the filtered pseudo-spectral technique is among the most accurate approaches. Finally, the procedure has been stressed via black hole dynamics and a new strategy, based on hyperviscous dissipation that suppresses spurious boundary problems, has been proposed. The model represents a valid tool of investigation, particularly suitable for the inspection of small scale nonlinear phenomena in gravitational dynamics.
Continuous Pruning of Deep Convolutional Networks Using Selective Weight Decay

During the last decade, deep convolutional networks have become the reference for many machine learning tasks, especially in computer vision. However, large computational needs make them hard to deploy on resource-constrained hardware. Pruning has emerged as a standard way to compress such large networks. Yet, the severe perturbation caused by most pruning approaches is thought to hinder their efficacy. Drawing inspiration from Lagrangian Smoothing, we introduce a new technique, Selective Weight Decay (SWD), which achieves continuous pruning throughout training. Our approach deviates significantly from most methods of the literature as it relies on a principle that can be applied in many different ways, for any problem, network or pruning structure. We show that SWD compares favorably to other approaches in terms of performance/parameters ratio on the CIFAR-10 and ImageNet ILSVRC2012 datasets. On CIFAR-10 and unstructured pruning, with a parameters target of 0.1%, SWD attains a Top-1 accuracy of 81.32% while the reference method only reaches 27.78%. On CIFAR-10 and structured pruning, with a parameters target of 2.5%, the reference technique drops at 10% (random guess) while SWD maintains the Top-1 accuracy at 93.22%. On the ImageNet ILSVRC2012 dataset with unstructured pruning, for a parameters targer of 2.5%, SWD attains 84.6% Top-5 accuracy instead of the 77.07% reached by the reference.
The Swan: Data-driven Inference of Stellar Surface Gravities for Cool Stars from Photometric Light Curves

Stellar light curves are well known to encode physical stellar properties. Precise, automated, and computationally inexpensive methods to derive physical parameters from light curves are needed to cope with the large influx of these data from space-based missions such as Kepler and TESS. Here we present a new methodology that we call “The Swan,” a fast, generalizable, and effective approach for deriving stellar surface gravity ( ) for main-sequence, subgiant, and red giant stars from Kepler light curves using local linear regression on the full frequency content of Kepler long-cadence power spectra. With this inexpensive data-driven approach, we recover to a precision of ∼0.02 dex for 13,822 stars with seismic values between 0.2 and 4.4 dex and ∼0.11 dex for 4646 stars with Gaia-derived values between 2.3 and 4.6 dex. We further develop a signal-to-noise metric and find that granulation is difficult to detect in many cool main-sequence stars (T eff ≲ 5500 K), in particular K dwarfs. By combining our measurements with Gaia radii, we derive empirical masses for 4646 subgiant and main-sequence stars with a median precision of ∼7%. Finally, we demonstrate that our method can be used to recover to a similar mean absolute deviation precision for a TESS baseline of 27 days. Our methodology can be readily applied to photometric time series observations to infer stellar surface gravities to high precision across evolutionary states.
New non-perturbative de Sitter vacua in $\alpha'$-complete cosmology

The $\alpha'$-complete cosmology developed by Hohm and Zwiebach classifies the ${\rm O}(d,d;{\mathbb R})$ invariant theories involving metric, $b$-field and dilaton that only depend on time, to all orders in $\alpha'$. Some of these theories feature non-perturbative isotropic de Sitter vacua in the string frame, generated by the infinite number of higher-derivatives of ${\rm O}(d,d;{\mathbb R})$ multiplets. Extending the isotropic ansatz, we construct stable and unstable non-perturbative de Sitter solutions in the string and Einstein frames. The generalized equations of motion admit new solutions, including anisotropic $d+1$-dimensional metrics and non-vanishing $b$-field. In particular, we find dS$_{n+1}\times T^{d-n}$ geometries with constant dilaton, and also metrics with bounded scale factors in the spatial dimensions with non-trivial $b$-field. We discuss the stability and non-perturbative character of the solutions, as well as possible applications.
ACTION OF FROST AND DEICING CHEMICALS - BASIC PHENOMENA AND TESTING

Three modifications of pore water are distinguished: Structured, prestructured and bulk. Water uptake by condensation and suction is outlined. A classification of pore sizes is given on this basis. The freeze thaw behaviour of the modifications is described. The influence of deicing chemicals is summarised. The basic prerequisites of a test procedure are derived from these considerations. The results with respect to precision, reproducibility, independence of testing institute and calibration to practical behaviour are shown. (A) For the covering abstract see IRRD 887310.
Antecedents of job satisfaction: A study of telecom sector

This study is based on the assumption that “a happy worker is a productive worker”. The research was conducted to identify the significance of those factors that lead towards job satisfaction and commitment of employees working in the telecom sector of Pakistan. The associations among pay and benefits, performance appraisal system, career development and management, supervision and collegiality and open communication (independent variables) were investigated with job satisfaction (dependent variable). The relationship between job satisfaction (dependent variable) and job commitment (outcome) was also hypothesized. Through questionnaire survey responses from 221 employees working at managerial and non-managerial positions were collected, which showed the significant association of supervision and collegiality and open communication on job satisfaction. Furthermore, job satisfaction was also found highly correlated and dependent upon job commitment. Managerial implications and conclusions are presented based upon these results.
Chemical and Electrochemical Characterisation of Oxide/Hydroxide Impurities in the Electrolyte for Magnesium Production

This work is part of a research program where the aim is to develop anelectroanalytical technique to determine the amount of dissolved oxide and hydroxide in industrial Mg electrolytes. The systems studied were mixtures of MgCl2 and NaCl, ranging from pure MgCl2 to melts containing 10 mole % MgCl2 / 90 mole % NaCl. To these melts, additions of MgO and MgOHCl were done at temperatures ranging from 475 to 850°C. Voltammetric measurements were performed before and after addition of MgO or MgOHCl and melt samples were taken for analysis. The quenched melt samples wereanalysed by carbothermal reduction analysis and the acid consumption method to obtain the O2- and OH- contents in the samples. Linear sweep voltammetry was performed with a sweep rate of 200 mV/sec in two potential regions to detect the concentration of dissolved MgOHCl and MgO. The experiments were performed inside a glove box having water and oxygen contents of, respectively, <1 ppm and <2 ppm. The results indicate that the rate of decomposition of MgOHCl increases with increasing temperature, as expected. In melts with high content of NaCl the underpotential deposition of sodium has a large influence on the uncertainty in the reading of the current density of MgOHCl reduction. Linear relations between MgO and MgOHCl concentrations and the peak current densities for the electrochemical reactions of the dissolved MgO and MgOHCl species in the melt, respectively, were observed. The diffusion coefficients of MgO and MgOHCl in the different melts were calculated. The diffusion coefficients decrease with increasing content of MgCl2. For MgOHCl the diffusion coefficient decreases from 5.6*10-5 cm2/sec in 20 mole % MgCl2 / 80 mole % NaCl to 2.1*10-5 cm2/sec in pure MgCl2, both measurements done at 800°C. For MgO the diffusion coefficient decreases from 6*10-5 cm2/sec in 41.5 mole % MgCl2 / 58.5 mole % NaCl to 0.8*10-5 cm2/sec in pure MgCl2, both measurements done at 730°C. The results show that it is possible to use cyclic voltammetry for quantitative analysis of MgOHCl in MgCl2 based melts.
Time-dependent mechanics of living cells

Cells sense and generate both internal and external forces. They resist and transmit these forces to the cell interior or to other cells. Moreover a variety of cellular responses are excited and influenced by transducing mechanical stimulations into chemical signals that lead to changes in cellular behaviour. The cytoplasm represents the largest part of the cell by volume and hence its rheology sets the maximum rate at which any cellular shape change can occur. To date, the cytoplasm has generally been modelled as a single-phase viscoelastic material; however, recent experimental evidence suggests that its rheology can be described more effectively using a poroelastic formulation in which the cytoplasm is considered to be a biphasic system constituted of a porous elastic solid meshwork (cytoskeleton, organelles, macromolecules) bathing in an interstitial fluid (cytosol). In this framework, a single parameter, the poroelastic diffusion constant p D , sets cellular rheology scaling as ~ 2 / p D Ex m with E the elastic modulus, x the hydraulic pore size, and m the cytosolic viscosity. Though this poroelastic view of the cell is a conceptually attractive model, direct supporting evidence has been lacking. In this work, such evidence is presented and the concept of a poroelastic cell is validated to explain cellular rheology at physiologically relevant time-scales. In this work, the functional form of stress relaxation in response to rapid application of a localised force by atomic force microscopy microindentation is examined in detail and it is shown that at short time-scales cellular relaxations are poroelastic. Then, p D is measured in cells by fitting experimental stress relaxation curves to the theoretical model. VI Next, using indentation tests in conjunction with osmotic perturbations, the validity of the predicted scaling of p D with pore size is qualitatively verified. Using chemical and genetic perturbations, it is shown that cytoplasmic rheology depends strongly on the integrity of the actin cytoskeleton but not on microtubules or intermediate filaments. Finally, comparison of scaling of viscoelastic and poroelastic models suggests that shorttime scale viscoelasticity might be due to water redistribution within the cytoplasm and a simple scaling relating cytoplasmic viscosity to cellular microstructure is provided.
Do Investors Care About Auditor Dismissals and Resignations? What Drives the Response?

SUMMARY: This paper uses market response tests to document key factors that help explain why investors find some auditor change announcements informative and others not. We find that the key drivers of investor response relate more to economic fundamentals than to the auditor change attributes in mandated auditor change disclosures. Investors react most negatively to resignation announcements (and much less for dismissals), and this response increases for companies with prior securities litigation and higher bankruptcy risk. Once we control for these factors, mandated auditor change disclosures other than an indication of resignation, while significant, have only limited ability to explain the price drop around an auditor change announcement.
Congruences between abelian pseudomeasures

Following Deligne and Ribet (`Values of abelian $L$-functions at negative integers over totally real fields.' Invent. Math. 59 (1980), 227-286) we prove that the `torsion congruences' (as introduced in our paper `Non-abelian pseudomeasures and congruences between abelian Iwasawa $L$-functions.' To appear in Pure and Applied Mathematics Quarterly) hold and so reduce the `main conjecture' of equivariant Iwasawa theory to the integrality of the logarithmic pseudomeasure.
Characterization of the G-protein coupling domains of the 5-HT1A receptor

The 5-HT1A receptor is expressed pre-synaptically as the primary somatodendritic autoreceptor on serotonergic raphe neurons, and post-synaptically in several brain regions. However, many of the 5-HTlA-mediated signaling pathways initially identified in non-neuronal cells transfected with the receptor have not been extensively studied in neuronal models. Our first study focused on signaling of the 5HT1A autoreceptor in RN46A cells, a model of serotonergic raphe neurons that express endogenous 5-HT1A receptors. We found that in RN46A cells stably transfected with the wild-type 5-HT1A receptor, 5-HT1A receptor activation coupled to Gai-mediated inhibition of forskolin-induced cAMP formation, Gpy-mediated increase in [Ca2+]i, and induced a novel inhibition of phospho-p42/p44-mitogen activated protein kinase (MAPK) that was also GPy-dependent. The activity of 5-HT1A receptors containing mutations of PKC sites in the second (i2: T149A) or third intracellular loop (i3: T229A/S253G/T343A) was also tested. The signaling of the 5-HT1A i3 mutant was similar to the 5-HT1A wild-type receptor while the i2 and quadmple (i2/i3) mutants, which both comprise the T149A substitution, failed to couple to GPy-mediated increase in [Ca2+|i or inhibition of MAPK, but did couple to Gai-mediated inhibition of cAMP. Thus, the i2 domain of the 5-HT1A autoreceptor is crucial for coupling to GPy-mediated signaling. Based on these findings and previous studies performed in our lab, we wanted to investigate the structure-function relationship of the T 149 amino acid and adjacent residues in the coupling of G-proteins, in particular GPy subunits, to the 5-HT1A
Food habits of the lane snapper, Lutjanus synagris (Perciformes: Lutjanidae), in the north zone of the Colombian Caribbean

This work describes the food habits of Lutjanus synagris by means of stomach content analysis, considering the trophic spectrum in general as well as by sex and size, the ecological aspects of the preys, their spatial distribution, and the relationship of the diet with the habitat conditions. In the analysis of 148 stomachs 45.3% were found to be full and 54.7% empty. The most representative preys (%N) were: Portunus spp. (27.3 %; n = 44) and Squilla intermedia (10.6%; n = 17), whereas the gravimetric analysis (%P) showed the heaviest preys to be Gastropoda (31.8%; 51.74 g) and Farfantepenaeus spp. (17.5%; 28.52 g). The frequency of occurrence (%FO) showed that Portunus spp. (25.4%; 17 stomachs) and S. intermedia (10.5%; 7 stomachs) were the most frequent preys. According to the IRI (%), Portunus spp. (43.01%) and Gastropoda (13.38%) were the most representative categories. The diet of L. synagris was found to consist of four types of main preys: Portunidae (837.06), Gastropod (260.29), Squillidae (234.66), and Penaeidae (218.05); and two types of secondary preys: Sicyoniidae (126.35) and Trichiuridae (75.64); with all others being incidental preys. The spatial distribution of the breadth of the trophic niche and the size of L. synagris allowed us to identify two zones. The first, between Riohacha and Dibulla, had the highest niche breadth values (0.64-1.00), denoting generalist predators, and the smallest specimens of L. synagris. The second zone, between Riohacha and Punta Gallinas, had the lowest niche breath values (0.00-0.23), indicating a high degree of dietary specialization, and the largest-sized individuals.
Growth, History, or Institutions? What Explains State Fragility in Sub-Saharan Africa

We explore the determinants of state fragility in sub-Saharan Africa. Controlling for a wide range of economic, demographic, geographic and istitutional regressors, we find that institutions, and in particular the civil liberties index and the number of revolutions, are the main determinants of fragility, even taking into account their potential endogeneity. Economic factors such as income growth and investment display a non robust impact after controlling for omitted variables and reverse causality. Colonial variables reflecting the history of the region display a marginal impact on fragility once institutions are accounted for.
Switching and Finite Automata Theory: Frontmatter

Understand the structure, behavior, and limitations of logic machines with this thoroughly updated third edition. Many new topics are included, such as CMOS gates, logic synthesis, logic design for emerging nanotechnologies, digital system testing, and asynchronous circuit design, to bring students up-to-speed with modern developments. The intuitive examples and minimal formalism of the previous edition are retained, giving students a text that is logical and easy to follow, yet rigorous. Kohavi and Jha begin with the basics, and then cover combinational logic design and testing, before moving on to more advanced topics in finite-state machine design and testing. Theory is made easier to understand with 200 illustrative examples, and students can test their understanding with over 350 end-of-chapter review questions.
Adequate Patient Characterization in COPD: Reasons to Go Beyond GOLD Classification.

The Global Initiative for Chronic Obstructive Lung Disease (GOLD) serves as a guide to treat and manage dif- ferent severity classes of patients with COPD. It was suggested that the five categories of FEV1 % predicted (GOLD 0-4), can be applied for selecting different therapeutic approaches. However, validation of these selective properties is very poor. To determine the relevance of the GOLD staging system for estimating the severity of clinical problems, GOLD 2 (n=70) and GOLD 3 (n=65) patients were drawn from a prospective cohort of patients with COPD and evaluated cross- sectionally by a newly developed Nijmegen Integral Assessment Framework (NIAF). The NIAF is a detailed assessment of a wide range of aspects of health status (HS). Significant, though small, differences were found in Static Lung Vol- umes, Exercise Capacity, Subjective Pulmonary Complaints, Subjective Impairment, and Health-Related QoL, besides Airflow of course. Moreover, overlap between scores of these five HS sub-domains was substantial, indicating small clinical relevance for discernment. No significant differences were found in nine other aspects of HS. It is concluded that GOLD stages do not discriminate in any aspect of HS other than airflow obstruction, and therefore do not help the clini- cian in deciding which treatment modalities are appropriate.
CARINA oxygen data in the Atlantic Ocean

Abstract. In the CARINA (Carbon dioxide in the Atlantic Ocean) project, a new dataset with many previously unpublished hydrographic data from the Atlantic, Arctic and Southern Ocean was assembled and subjected to careful quality control (QC) procedures. Here, we present the dissolved oxygen measurements in the Atlantic region of the dataset and describe in detail the secondary QC procedures that aim to ensure that the data are internally consistent. This is achieved by a cross-over analysis, i.e. the comparison of deep ocean data at places that were sampled by different cruises at different times. Initial adjustments to the individual cruises were then determined by an inverse procedure that computes a set of adjustments that requires the minimum amount of adjustment and at the same time reduces the offsets in an optimal manner. The initial adjustments were then reviewed by the CARINA members, and only those that passed the following two criteria were adopted: (i) the region is not subject to substantial temporal variability, and (ii) the adjustment must be based on at least three stations from each cruise. No adjustment was recommended for cruises that did not fit these criteria. The final CARINA-Oxygen dataset has 103414 oxygen samples from 9491 stations obtained during 98 cruises covering three decades. The sampling density of the oxygen data is particularly good in the North Atlantic north of about 40° N especially after 1987. In contrast, the sample density in the South Atlantic is much lower. Some cruises appear to have poor data quality, and were subsequently omitted from the adjusted dataset. Of the data included in the adjusted dataset, 20% were adjusted with a mean adjustment of 2%. Due to the achieved internal consistency, the resulting product is well suited to produce an improved climatology or to study long-term changes in the oxygen content of the ocean. However, the adjusted dataset is not necessarily better suited than the unadjusted data to address questions that require a high level of accuracy, such as the computation of the saturation state.