Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing Speaker Verification Embedding Extractors and Back-Ends Under Language and Channel Mismatch

In this paper, we analyze the behavior and performance of speaker embeddings and the back-end scoring model under domain and language mismatch. We present our findings regarding ResNet-based speaker embedding architectures and show that reduced temporal stride yields improved performance. We then consider a PLDA back-end and show how a combination of small speaker subspace, language-dependent PLDA mixture, and nuisance-attribute projection can have a drastic impact on the performance of the system. Besides, we present an efficient way of scoring and fusing class posterior logit vectors recently shown to perform well for speaker verification task. The experiments are performed using the NIST SRE 2021 setup.
Fast Algorithm for Maximal k-plex Enumeration

Finding all maximal k -plexes on networks is a fundamental research problem in graph analysis due to many important applications, such as community detection, biological graph analysis, and so on. A k -plex is a subgraph in which every vertex is adjacent to all but at most k vertices within the subgraph. In this paper, we study the problem of enumerating all large maximal k -plexes of a graph and develop several new and efﬁcient techniques to solve the problem. Speciﬁcally, we ﬁrst propose several novel upper-bounding techniques to prune unnecessary computations during the enumeration procedure. We show that the proposed upper bounds can be computed in linear time. Then, we develop a new branch-and-bound algorithm with a carefully-designed pivot re-selection strategy to enumerate all k -plexes, which outputs all k -plexes in O ( n 2 γ nk ) time theoretically, where n is the number of vertices of the graph and γ k is strictly smaller than 2. Finally, extensive experimental results indicate that the proposed algorithm can achieve up to 2 × to 100 × speedup over the state-of-the-art algorithm on most real-world benchmark graphs.
How do noise tails impact on deep ReLU networks?

This paper investigates the stability of deep ReLU neural networks for nonparametric regression under the assumption that the noise has only a finite p-th moment. We unveil how the optimal rate of convergence depends on p, the degree of smoothness and the intrinsic dimension in a class of nonparametric regression functions with hierarchical composition structure when both the adaptive Huber loss and deep ReLU neural networks are used. This optimal rate of convergence cannot be obtained by the ordinary least squares but can be achieved by the Huber loss with a properly chosen parameter that adapts to the sample size, smoothness, and moment parameters. A concentration inequality for the adaptive Huber ReLU neural network estimators with allowable optimization errors is also derived. To establish a matching lower bound within the class of neural network estimators using the Huber loss, we employ a different strategy from the traditional route: constructing a deep ReLU network estimator that has a better empirical loss than the true function and the difference between these two functions furnishes a low bound. This step is related to the Huberization bias, yet more critically to the approximability of deep ReLU networks. As a result, we also contribute some new results on the approximation theory of deep ReLU neural networks.
Scalable, Highly Crystalline, 2D Semiconductor Atomic Layer Deposition Process for High Performance Electronic Applications

This work demonstrates a large area process for atomically thin 2D semiconductors to unlock the technological upscale required for their commercial uptake. The new atomic layer deposition (ALD) and conversion technique yields large area performance uniformity and tunability. Like graphene, 2D Transition Metal Dichalcogenides (TMDCs) are prone to upscaling challenges limiting their commercial uptake. They are challenging to grow uniformly on large substrates and to transfer on alternative substrates while they often lack in large area electrical performance uniformity. The scalable ALD process of this work enables uniform growth of 2D TMDCs on large area with independent control of layer thickness, stoichiometry and crystallinity while allowing chemical free transfers to application substrates. Field effect transistors (FETs) fabricated on flexible substrates using the process present a field effect mobility of up to 55 cm2/Vs, subthreshold slope down to 80 mV/dec and on/off ratios of 107. Additionally, non‐volatile memory transistors using ferroelectric FETs (FeFETs) operating at 5 V with on/off ratio of 107 and a memory window of 3.25 V are demonstrated. These FeFETs demonstrate state‐of‐the‐art performance with multiple state switching, suitable for one‐transistor non‐volatile memory and for synaptic transistors revealing the applicability of the process to flexible neuromorphic applications.
Convergence Error Analysis of Reflected Gradient Langevin Dynamics for Globally Optimizing Non-Convex Constrained Problems

Gradient Langevin dynamics and a variety of its variants have attracted increasing attention owing to their convergence towards the global optimal solution, initially in the unconstrained convex framework while recently even in convex constrained non-convex problems. In the present work, we extend those frameworks to non-convex problems on a non-convex feasible region with a global optimization algorithm built upon reflected gradient Langevin dynamics and derive its convergence rates. By effectively making use of its reflection at the boundary in combination with the probabilistic representation for the Poisson equation with the Neumann boundary condition, we present promising convergence rates, particularly faster than the existing one for convex constrained non-convex problems.
Learning to Reduce False Positives in Analytic Bug Detectors

Due to increasingly complex software design and rapid iterative development, code defects and security vulnerabilities are prevalent in modern software. In response, programmers rely on static analysis tools to regularly scan their codebases and find potential bugs. In order to maximize coverage, however, these tools generally tend to report a significant number of false positives, requiring developers to manually verify each warning. To address this problem, we propose a Transformer-based learning approach to identify false positive bug warnings. We demonstrate that our models can improve the precision of static analysis by 17.5%. In addition, we validated the generalizability of this approach across two major bug types: null dereference and resource leak.
Non-Abelian Toda lattice and analogs of Painlevé III equation

In integrable models, stationary equations for higher symmetries serve as one of the main sources of reductions consistent with dynamics. We apply this method to the non-Abelian two-dimensional Toda lattice. It is shown that already the stationary equation of the simplest higher flow gives a non-trivial non-autonomous constraint that reduces the Toda lattice to a non-Abelian analog of pumped Maxwell–Bloch equations. The Toda lattice itself is interpreted as an auto-Bäcklund transformation acting on the solutions of this system. Further self-similar reduction leads to non-Abelian analogs of the Painlevé III equation.
Massless multifold Hopf semimetals

Three-dimensional topological semimetals exhibit linear energy band crossing points that act as monopoles of Berry curvature. Here, an alternative class of semimetals is introduced, featuring linear $N$-fold crossing points each of which acts as a source of a \emph{Berry dipole}. We construct continuum and lattice models for such \emph{massless multifold Hopf semimetals (MMHSs)} with $N=3,4,5$ bands and study nontrivial effects of a Berry dipole crossing: (i) A Landau level spectrum that is strongly tunable by the orientation of the magnetic field relative to the dipole axis. (ii) An anomalous Hall conductivity that is an odd function of the Fermi level. (iii) Weak-field dissipative magnetoconductivities that resemble the chiral anomaly, chiral magnetic and magnetochiral effects familiar from a pair of coupled Weyl nodes, but that are even functions of the Fermi level. By gapping out MMHSs, multiband Hopf insulators with Hopf numbers as high as $\mathcal{N}_\text{Hopf}=10$ are obtained, providing a fertile playground to explore delicate topology.
On Bloch norm and Bohr phenomenon for harmonic Bloch functions on simply connected domains

For α ∈ (0 , ∞ ) , let B H , Ω ( α ) denote the class of α -Bloch mappings on a proper simply connected domain Ω ⊆ C . In this article, we introduce the class B ∗H , Ω ( α ) of harmonic α -Bloch-type mappings on a proper simply connected domain Ω ⊆ C and study several interesting properties of the classes B H , Ω ( α ) and B ∗H , Ω ( α ) when Ω is proper simply connected domain and the shifted disk Ω γ containing D , where and 0 ≤ γ < 1 . We establish the Landau’s theorem for the harmonic Bloch space B H , Ω γ ( α ) on the shifted disk Ω γ . For f ∈ B H , Ω ( α ) (respectively B ∗ H , Ω ( α ) ) of the form f ( z ) = h ( z )+ g ( z ) = (cid:80) ∞ n =0 a n z n + (cid:80) ∞ n =1 b n z n in D with Bloch norm || f || H , Ω ,α ≤ 1 (respec-tively || f || ∗H , Ω ,α ≤ 1 ), we deﬁne the Bloch-Bohr radius for the class B H , Ω ( α ) (respectively B ∗H , Ω ( α ) ) to be the largest radius r Ω ,f ∈ (0 , 1) such that (cid:80) ∞ n =0 ( | a n | + | b n | ) r n ≤ 1 for r ≤ r Ω ,α and for all f ∈ B H , Ω ( α ) (respectively B ∗H , Ω ( α ) ). We also investigate Bloch-Bohr radius for the classes B H , Ω ( α ) and B ∗H , Ω ( α ) on simply connected domain Ω containing D .
The Role Of Probiotics In The Treatment Of Helicobacter Pylori-Caused Gastritis

Helicobacter pylori are a typical bacterium that affects a portion of the population in the world. Probiotics in combination with antibiotics to treat gastritis caused by Helicobacter pylori is an effective treatment that has fewer negative effects than antibiotics alone. In comparison to using antibiotics alone, probiotics plus antibiotic supplementation eliminate gastritis caused by H pylori. Antibiotic-based H. pylori treatment is only about seventy percent successful, and it comes with a slew of side effects. As a result, probiotics combined with antibiotics have a completely inhibiting effect on H. pylori caused by gastritis. Probiotics are beneficial in reducing H. pylori-related stomach discomfort, according to several in vivo investigations. Human studies looked at the efficacy of antibiotics and probiotics in combination, and the results showed that probiotics improved H. pylori gastritis reduction and inhibited H. pylori settlement. Despite this, no study has been able to show that probiotics alone are capable of eliminating H. pylori. Probiotics used in conjunction with antibiotics can reduce the antagonistic qualities induced by H. pylori abolition antibiotic activity, and hence have beneficial properties in H. pylori-infected people. Long-term intake of diets containing probiotic strains improves antibiotic action of H. pylori infection in humans, mostly by lowering the risk of antibiotic-related diseases.
A Stochastic Approach to Cavitation Inception Prediction

A novel methodology for the prediction of cavitation inception based on a probabilistic approach is presented along with a limited validation. The simulation of a cavitating flow is a challenging and evolving area of investigation, complicated by the requirement of accurately solving a complex multiphase flow. However, for many practical applications the prediction of conditions for which cavitation will not occur is just as important. A reliable, physics-based method to predict the likelihood of cavitation events, based on well-established single-phase computation methods, will be a valuable tool. The proposed method uses probability distribution functions (pdf) of pressure fluctuations derived from isotropic homogeneous turbulence (IHT) simulations to characterize the sub-grid pressure of a CFD computation. Probabilistic description of the pressure in the computational cell is then used to estimate the cavitation potential of the flow. Additionally, a simple model of a vortex is used to deterministically correct sub-grid underestimation of the pressure drop at the core of resolved vortices, which is a further improvement to the probabilistic correction implemented.
Characterization of Bacteriophage Targeting Bacillus licheniformis in Milk Processes and Thermal Stability of Bacteriophage During HTST Pasteurization

Characterization of Bacteriophages Targeting Bacillus licheniformis in Milk Processes and Thermal Stability of Bacteriophage During HTST Pasteurization Jeremy Robert Arbon Department of Nutrition, Dietetics, and Food Science, BYU Master of Science An array of Bacillus licheniformis strains were isolated from a commercial powdered milk process. Bacteriophages exhibiting activity against B. licheniformis were isolated from cattle manure and effluent samples destined for a lagoon at a dairy farm. After sequencing, 8 of the 10 phages were found to be novel and genetically differentiated. Transmission electron scanning microscopy (TSEM) was performed. All bacteriophages were of the family Herelleviridae with contractile tail sheaths ranging from 80μm to 150μm and, surprisingly, survived a common fluid milk processing treatment used to inactivate vegetative cells. The survival of the phage after high temperature short time pasteurization of 73°C for 20 s shows that the use of bacteriophages in milk to control B. licheniformis could be applied as a potential quality control, retarding the germination of spores and reduction of final spore counts in products with long run times such as dairy powders.
Study of support vector machine based adaptive Kalman filtering

As the accuracy will decrease or even divergence problems will occur while the theoretical statistical behavior of the Kalman filtering and its actual behavior do not agree,a new self-adaptive Kalman filtering,support vector machines adaptive Kalman filtering(SVMAKF),is presented.In order to tune the noise covariance of the Kalman filtering on line,SVM is employed to generate the adaptive factor,according to the ratio of the theoretical covariance of the innovation sequence to its actual covariance.Simulation on target tracking shows that SVMAKF can increase the estimation accuracy and the robustness of the Kalman filtering remarkably,compared with the traditional Kalman filtering.
WORKING PAPER SERIES OPTIMAL TAXATION AND R & D POLICIES

We study the optimal design of R&D policies and corporate taxation when the outputs of innovation are not appropriable in the absence of intellectual property rights policies and there are non-internalized technology spillovers across firms. Firms are heterogeneous in their research productivity, i.e., in the efficiency with which they convert a given set of R&D inputs into successful innovations. There is asymmetric information about firm productivity and about its stochastic evolution over time that prevents the first best solution to the technology spillover. The problem is thus posed as one of dynamic mechanism design with externalities. We characterize the optimal constrained efficient allocations over firms' life cycles and for firms of different productivities. We show that the constrained efficient allocations can be implemented either by a patent system plus a price subsidy for the monopolists' products, together with a parsimonious R&D subsidy function or, equivalently, by a prize mechanism. We estimate our model using firm-level data matched to patent data and quantify the optimal policies. Simpler innovation policies, such as linear R&D subsidies and linear profit taxes, lead to large revenue losses relative to the optimal mechanism. Ufuk Akcigit Department of Economics University of Chicago 1126 East 59th Street Saieh Hall, Office 403 Chicago, IL 60637 and NBER uakcigit@uchicago.edu Douglas Hanley Department of Economics, University of Pennsylvania 3718 Locust Walk, #160 Philadelphia, PA 19104 dohan@as.pitt. edu Stefanie Stantcheva Department of Economics Littauer Center 232 Harvard University Cambridge, MA 02138 and NBER sstantcheva@fas.harvard. edu
Supplementary Information: Particle-like topologies in light

Danica Sugic,1, 2, 3 Ramon Droop,4 Daniel Ehrmanntraut,4 Eileen Otte,4 Franco Nori,3, 5 Janne Ruostekoski,6 Cornelia Denz,4 and Mark R Dennis1, 2, 7 School of Physics and Astronomy, University of Birmingham, Birmingham B15 1TT, UK H H Wills Physics Laboratory, University of Bristol, Bristol BS8 1TL, UK Theoretical Quantum Physics Laboratory, RIKEN Cluster for Pioneering Research, Wako-shi, Saitama 351-0198, Japan Institute of Applied Physics and Center for Nonlinear Science (CeNoS), University of Münster, 48149 Münster, Germany Physics Department, University of Michigan, Ann Arbor, Michigan 48109-1040, USA Physics Department, Lancaster University, Lancaster LA1 4YB, UK EPSRC Centre for Doctoral Training in Topological Design,
Field Evaluation of the Insecticidal Activity of Some Plant Extracts again t Major Insect Pests of Mung bean (Vigna radiata L. Wilczek) in Nigeria

DOI: 10.15580/GTPPE.2019. 2.070519127 A field trial was conducted at the Teaching and Research Farm of the Michael Okpara University of Agriculture, Umudike during the 2018 cropping season to evaluate efficacy of selected plant extracts from five plant species against insect pests of Mung bean (Vigna radiata L. Wilczek). The extracts tested were obtained from leaves of Vernonia amygdalina, Tephrosia vogelii, Alchornea cordifolia, Azadirachta indica, Moringa oleifera and untreated plot was introduced as the check (control) in the trial. The experimental design was a Randomized Complete Block Design (RCBD) with four replicates. Data were collected weekly on the insect population densities, yield and yield components. The results indicated that there was a significant P<0.05) reduction in the population of insects on the plots treated with plant extracts compared with the control plot. The results indicated that all the treatments were effective against major field insect pests of Mung bean (Aphis craccivora (Aphid), Ootheca mutabilis, (brown leaf beetle), Megalurothrips sjostedti (flower bud thrips), Maruca vitrata (legume pod borer), and pod sucking bugs (Nezara viridula “green vegetable bug”), (Riptortus seripes “large brown bean bug”), Anoplocnemis curvipes, Melanacanthus scutellaris (small brown bean bug). Plots treated with Tephrosia vogelii recorded high insecticidal properties when compared with other plant extracts. The plots treated with Tephrosia vogelii and Moringa oleifera recorded the highest grain yield of 406.0kg/ha and 289.5kg/ha in 2018 cropping season. All the plant extracts used exhibited insecticidal activity against insect pests of Mung bean in the field. Submitted: 05/07/2019 Accepted: 30/07/2019 Published: 25/09/2019
Generalized and specific whole-brain white matter abnormalities in human cocaine and heroin use disorders

Neuroimaging studies in substance use disorder have shown widespread impairments in white matter (WM) microstructure suggesting demyelination and axonal damage. However, substantially fewer studies explored generalized vs. acute/specific drug effects on WM. Our study assessed whole-brain WM integrity in three subgroups of addicted individuals, encompassing cocaine (CUD) and heroin (HUD) use disorder, compared to healthy controls (CTL). Diffusion MRI was acquired in 58 CTL, 28 current cocaine users/CUD+, 32 abstinent cocaine users/CUD-, and 30 individuals with HUD (positive urine for cocaine in CUD+ and opiates used for treatment in HUD). Tract-Based Spatial Statistics allowed voxelwise analyses of diffusion metrics [fractional anisotropy/FA, mean diffusivity/MD, radial diffusivity/RD, and axial diffusivity/AD]. Permutation statistics (p-corrected<.05) were used for between-group t-tests. Compared to CTL, all drug-addicted individuals showed widespread FA reductions, and increased MD, RD, and AD (19-57% of WM skeleton, p<.05). The HUD showed the most impairments, followed by the CUD+, with only minor FA reductions in CUD- (<.2% of skeleton, p=.05). Longer periods of regular use were associated with decreased FA and AD, and higher subjective craving was associated with increased MD, RD, and AD, across all drug-addicted individuals (p<.05). These findings demonstrate extensive WM impairments in drug-addicted individuals characterized by decreased anisotropy and increased diffusivity, thought to reflect demyelination and lower axonal packing. Extensive abnormalities in both groups with positive urine status (CUD+ and HUD), and correlations with craving, suggest greater WM impairments with recency of use. Results in CUD-, and correlations with regular use, further imply cumulative and/or persistent WM damage.
Immunogenic superiority and safety of Biological E CORBEVAX vaccine compared to COVISHIELD (ChAdOx1 nCoV-19) vaccine studied in a phase III, single blind, multicenter, randomized clinical trial

Background: Optimum formulation of Biological Es CORBEVAX vaccine that contains protein sub unit of Receptor Binding Domain (RBD) from the spike protein of SARS-COV-2 formulated with aluminum hydroxide (Al3+) and CpG1018 as adjuvants was selected in phase-1 and 2 studies and proven to be safe, well tolerated and immunogenic in healthy adult population. In the current study, additional data was generated to determine immunogenic superiority of CORBEVAX vaccine over COVISHIELD vaccine and safety in larger and older population. Methods: This is a phase III prospective, single blinded, randomized, active controlled study (CTRI/2021/08/036074) conducted at 18 sites across India in healthy adults aged between 18-80 years. This study has two arms; immunogenicity arm and safety arm. Participants in immunogenicity arm were randomized equally to either CORBEVAX or COVISHIELD vaccination groups to determine the immunogenic superiority. Healthy adults without a history of Covid-19 vaccination or SARS-CoV-2 infection, were enrolled. Findings: The safety profile of CORBEVAX vaccine was comparable to the comparator vaccine COVISHIELD in terms of overall AE rates, related AE rates and medically attended AEs. Majority of reported AEs were mild in nature, and overall CORBEVAX appeared to cause fewer local and systemic adverse reactions/events. Overall, two grade-3 serious AEs (Dengue fever and femur fracture) were reported and they are unrelated to study vaccine. Neutralizing Antibody titers, against both Ancestral and Delta strain, induced post two-dose vaccination regimen were higher in the CORBEVAX arm as compared to COVISHIELD and the analysis of GMT ratios demonstrated immunogenic superiority of CORBEVAX in comparison with COVISHIELD. Both CORBEVAX and COVISHIELD vaccines showed comparable seroconversion post vaccination when assessed against anti-RBD IgG response. The subjects in CORBEVAX cohort also exhibited higher Interferon-gamma secreting PBMCs post stimulation with SARS-COV-2 RBD peptides than the subjects in COVISHIELD cohort. Interpretations: Neutralizing antibody titers induced by CORBEVAX vaccine against Delta and Ancestral strains were protective, indicative of vaccine effectiveness of >90% for prevention of symptomatic infections based on the Correlates of Protection assessment performed during Moderna and Astra-Zeneca vaccine Phase III studies. Safety findings revealed that CORBEVAX vaccine has excellent safety profile when tested in larger and older population.