Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of sodium nitroprusside on sperm functional membrane integrity and acrosome integrity of frozen thawed buffalo semen

The present study was undertaken to assess the effects of exogenous supplementation of sodium nitroprusside (SNP), a nitric oxide (NO) donor on sperm functional membrane integrity and acrosome integrity of frozen thawed buffalo semen. Frozen semen straws from 6 buffalo bulls were procured from Central Frozen Semen Production and Training Institute, Hesseraghatta, Banglore-51. The straws were thawed at 37 ̊C for 30 seconds and emptied into 15 ml sterile plastic centrifuge tube containing 1 ml of capacitation medium (control), addition of 100 μM SNP to capacitation medium (SNP treatment I) and 100 nM SNP to capacitation medium (SNP treatment II) were incubated at 37 ̊C for 1 hour. After 1 hour incubation, sperm functional membrane integrity was studied by hypo-osmotic swelling test (HOST). In control, SNP treatment I and II, 57.42% ± 0.62, 28.08% ± 1.02 and 39.75% ± 1.20 spermatozoa had intact functional membrane. Functional membrane integrity of spermatozoa was significantly (P<0.01) higher in control than SNP treatment I and II. Spermatozoa with intact functional membrane were significantly (P<0.01)more in SNP treatment II than SNP treatment I. Sperm acrosome integrity was assessed by Giemsa stain method. Acrosome intact spermatozoa were significantly (P<0.01) more in control (37.42% ± 0.70) as compared to SNP treatment I (12.58% ± 0.68) and II (27.33% ± 0.64). Spermatozoa with intact acrosome were significantly (P<0.01) high in SNP treatment II than SNP treatment I. From this study, it is concluded that addition of SNP, a NO donor has detrimental effects on sperm functional membrane integrity and acrosome integrity of frozen thawed buffalo semen on concentration dependant manner.
Knowledge Management and Public Sector Accountants: Knowledge Management Models in the Accountant General’s Department of Malaysia

Knowledge Management (KM) in an accounting organization in developing countries has not yet received much attention in the research literature. Therefore, this study aims to investigate how accountants as professional intellects working in a public sector accounting organization perceived the importance of KM implementation factors in their organization. The Accountant General’s Department (AGD) of Malaysia is selected for an in-depth study of KM in a public sector accounting organization because it is a knowledge intensive organization and it has a large pool of public sector accountants. This paper presents the knowledge sharing (KS) model and the integrated KM model that interconnect KM enablers and performance of KM in the AGD. Literature reviews and previous empirical studies provide the basis for the study models which integrate KM solution through learning, leadership, technology and organizational structure and culture to improve organizational performance. A questionnaire was used to collect data from accountants employed by the AGD. Through factor and multiple regression analysis, the results provide support for the KS model and KM model with the positive effects of KM enablers on knowledge sharing process and organizational performance. Performance evaluation and incentives has a high significant impact on the knowledge sharing performance. However, when both KM enablers and knowledge sharing process are regarded as antecedents of organizational performance, knowledge sharing process and technology resources are among those of highly significant KM enablers. As a knowledge nexus of public sector accounting knowledge and practices, ACD has to give serious emphasis to those significant KM enablers in drawing up its KM models and KM implementation strategy in managing and leveraging the intellectual assets of its professional intellects.
Five Level Boost Switched-Capacitor Multilevel Module Multilevel Inverter Topology

In this paper five level boost switched-capacitor multilevel module multilevel inverter topology is presented (BSCMLM MLI). The proposed topology is consisting of two capacitors and single source for generation of five inverter output voltage. The switched-capacitor circuit boost up the voltage and balancing the capacitor voltages. This five level topology offers less switching device count with capacitor voltage balancing, it lead to reducing the conduction and switching losses of converter and increase the efficiency of converter. The analyses of switching and conduction losses of suggested topology are presented. This topology is tested with variable frequency multi carrier pulse width modulation (VFMCPWM) technique with different loading conditions are carried out in MATLAB environment.
Insights into the Photosensitive Activity of Monolayer HNb3O8 Nanosheets Under Visible Light Irradiation

Monolayer HNb3O8 nanosheets, as a platform, were prepared for investigating the mechanism of photosensitized degradation of RhB. We found that RhB molecules were capable to absorb on HNb3O8 nanosheets via a strong interaction between the –N(Et)2 group in RhB molecules and surface Lewis acid sites on HNb3O8 nanosheets, contribution to an easier oxidation of RhB molecules. Thanks to the suitable conduction band of HNb3O8 nanosheets, electrons transferred from excited RhB to HNb3O8 nanosheets effectively and reduced the dissolved O2 in the reaction solution into O2 immediately, resulting in the efficient photosensitized degradation of RhB.
A Virtual Sequencer Reveals the Dephasing Patterns in Error-Correction Code DNA Sequencing

An error-correction code (ECC) sequencing approach has recently been reported to effectively reduce sequencing errors by interrogating a DNA fragment with three orthogonal degenerate sequencing-by-synthesis (SBS) reactions. However, similar to other non-single-molecule SBS methods, the reaction will gradually lose its synchronization within a molecular colony in ECC sequencing. This phenomenon, called dephasing, causes sequencing error, and in ECC sequencing, induces distinctive dephasing patterns. To understand the characteristic dephasing patterns of the dual-base flowgram in ECC sequencing and to generate a correction algorithm, we built a virtual sequencer in silico . Starting from first principles and based on sequencing chemical reactions, we simulated ECC sequencing results, identified the key factors of dephasing in ECC sequencing chemistry, and designed an effective dephasing algorithm. The results show that our dephasing algorithm is applicable to sequencing signals with at least 500 cycles, or 1,000-bp average read length, with acceptably low error rate for further parity-checks and ECC deduction. Our virtual sequencer with our dephasing algorithm can further be extended to a dichromatic form of ECC sequencing, allowing for a potentially much more accurate sequencing approach.
NORSK GEOLOGISK TIDSSKRIFT 43 THE MIDDLE ORDOVICIAN OF THE OSLO REGION, NORWAY

1897 and 1925 are redescribed and reillustrated. Approximately six hundred fifty specimens, including the types, are available from units 4a and 4b. Most specimens are not specifically identifiable; within same superfamilies, man y specimens are generically indeterminate. Because well preserved specimens are rare, an apen nomenclature has been employed for most new taxa. The fauna of 4b is slightly more diversified than that of 4a, but both faunas are limited to few species. The preponderant number of specimens come from limestone masses within dark shale. This is considered to be an allocthonous occurrence. Few specimens come from shallow water deposits peripheral to and overlying the dark shales. The faunas of these two facies is different, but the second is so poorly known that no dose comparisons can be made. Several of the forms in the shallow water assemblage are known from single specimens. Less than a dozen specimens of monoplacophorans are known. Pollicina conoidea is transferred to Hypseloconus ? Palaeoscurria ( ? ) norvegica is trans­ ferred to Archinacella. One new species, Archinacella stoermeri, is described. Lepetopsis inopinata may be an inarticulate brachiopod. The gastropod fauna is composed almost entirely of Archaeogastropoda with Bellerophontacea and Pleurotomariacea constituting the majority of the taxa. Three specimens of Archaeogastropoda? representing three genera are known. Only one caenogastropod is known. In summary of the gastropod taxonomy, twenty-six genera are recognized in the Middle Ordovician of Norway, but only twenty-two genera can be named; three are indeterminate and the fourth is based on a nomen dubium. Three new 134 ELLIS L. YOCHELSON species are described and named. These are Omospira? holtedahli, lvl ourlonia mjoesa and Holopea henningsmoeni. Four new species are described but not named and ten species, including two from undetermined genera, are described or discussed informally. One species is only tentatively identified and is not described and another is well known and again not described. Five species are in their originally described generic taxon. Twelve species are transferred to other generic taxa. Five specific names based on Norwegian type specimens have been placed in synonymy.
Generating collection transformations from proofs

Nested relations, built up from atomic types via product and set types, form a rich data model. Over the last decades the nested relational calculus, NRC, has emerged as a standard language for defining transformations on nested collections. NRC is a strongly-typed functional language which allows building up transformations using tupling and projections, a singleton-former, and a map operation that lifts transformations on tuples to transformations on sets. In this work we describe an alternative declarative method of describing transformations in logic. A formula with distinguished inputs and outputs gives an implicit definition if one can prove that for each input there is only one output that satisfies it. Our main result shows that one can synthesize transformations from proofs that a formula provides an implicit definition, where the proof is in an intuitionistic calculus that captures a natural style of reasoning about nested collections. Our polynomial time synthesis procedure is based on an analog of Craig's interpolation lemma, starting with a provable containment between terms representing nested collections and generating an NRC expression that interpolates between them. We further show that NRC expressions that implement an implicit definition can be found when there is a classical proof of functionality, not just when there is an intuitionistic one. That is, whenever a formula implicitly defines a transformation, there is an NRC expression that implements it.
Confrontation of Observation and Theory: High-frequency QPOs in X-Ray Binaries, Tidal Disruption Events, and Active Galactic Nuclei

We compile observations of high-frequency quasi-periodic oscillations (QPOs) around black holes, both stellar and supermassive, and compare their positions in the parameter space of black hole mass, spin, and oscillation frequency. We find that supermassive black holes occupy a separate region of parameter space than stellar, and further, that QPOs seen around tidal disruption events rather than Seyfert-type active galactic nuclei (AGN) occupy an entirely different space. We then compare these results to the orbital resonance, diskoseismic, warped disk, and disk–jet coupling theoretical models for the origin of high-frequency QPOs. We find that while oscillations around stellar mass black holes are generally consistent with the above models, supermassive black holes are decidedly not. Oscillations seen in tidal disruption events are consistent with oscillations near the frequency of the innermost stable circular orbit, while QPOs in AGN are not accounted for by any of the physical models in consideration. This indicates that despite the scale invariance of accretion processes implied by a decades-wide correlation between QPO frequency and black hole mass, any theory of high-frequency QPOs must relate the frequency to more than just the mass and spin.
SALR: Sharpness-aware Learning Rates for Improved Generalization

In an effort to improve generalization in deep learning, we propose SALR: a sharpness-aware learning rate update technique designed to recover flat minimizers. Our method dynamically updates the learning rate of gradient-based optimizers based on the local sharpness of the loss function. This allows optimizers to automatically increase learning rates at sharp valleys to increase the chance of escaping them. We demonstrate the effectiveness of SALR when adopted by various algorithms over a broad range of networks. Our experiments indicate that SALR improves generalization, converges faster, and drives solutions to significantly flatter regions.
Transient Simulation of Grid-Feeding Converter System for Stability Studies Using Frequency Response Optimized Integrators

A grid-feeding converter system is added to a novel power system transient simulation scheme based on frequency response optimized integrators considering second order derivative. The converter system and its implementation in the simulation scheme are detailed. Case studies verify the accuracy and efficiency of the simulation scheme. Furthermore, this paper proposes and justifies extending the simulation scheme by integrating commonly used numerical integrators considering first order derivative for part of the studied system. The proposed extension has an insignificant impact on the accuracy of the simulation scheme while significantly enhancing its efficiency. It also reduces the development burden in adding new devices.
On Performance of Multiscale Sparse Fast Fourier Transform Algorithm

Computing the Sparse Fast Fourier Transform(sFFT) of a K-sparse signal of size N has emerged as a critical topic for a long time. The sFFT algorithms decrease the runtime and sampling complexity by taking advantage of the signal inherent characteristics that a large number of signals are sparse in the frequency domain(e.g., sensors, video data, audio, medical image, etc.). The first stage of sFFT is frequency bucketization through one of these filters: Dirichlet kernel filter, flat filter, aliasing filter, etc. Compared to other sFFT algorithms, the sFFT algorithms using the flat filter is more convenient and efficient because the filtered signal is concentrated both in the time domain and frequency domain. Up to now, three sFFT algorithms sFFT1.0, sFFT2.0, sFFT3.0 algorithm have been proposed by the Massachusetts Institute of Technology(MIT) in 2013. Still, the sFFT4.0 algorithm using the multiscale approach method has not been implemented yet. This paper will discuss this algorithm comprehensively in theory and implement it in practice. It is proved that the performance of the sFFT4.0 algorithm depends on two parameters. The runtime and sampling complexity are in direct ratio to the multiscale parameter and in inverse ratio to the extension parameter. The robustness is in direct ratio to the extension parameter and in inverse ratio to the multiscale parameter. Compared with three similar algorithms or other four types of algorithms, the sFFT4.0 algorithm has excellent runtime and sampling complexity that ten to one hundred times better than the fftw algorithm, although the robustness of the algorithm is medium.
Neutrino refractive effects during their decoupling era in the early universe

There is an accepted approach to calculation of the neutrino flavor density-matrix in the halo of a supernova, in which neutrino amplitudes, not cross-sections, need to be followed carefully in the region above the region of frequent scatterings. The same reasoning and techniques, applied to the evolution of neutrino flavors and energy distributions in the early universe in the era of neutrino decoupling, leads to radical changes in the prediction of the effects of the neutrino-neutrino interaction. Predictions for the production of sterile neutrinos, should they exist, will also be changed.
Adaptive Community Search in Dynamic Networks

Community search is a well-studied problem which, given a static graph and a query set of vertices, requires to find a cohesive (or dense) subgraph containing the query vertices. In this paper we study the problem of community search in temporal dynamic networks. We adapt to the temporal setting the notion of network inefficiency which is based on the pairwise shortest-path distance among all the vertices in a solution. For this purpose we define the notion of shortest-fastest-path distance: a linear combination of the temporal and spatial dimensions governed by a user-defined parameter. We thus define the MINIMUM TEMPORAL-INEFFICIENCY SUBGRAPH problem and show that it is NP-hard. We develop an algorithm which exploits a careful transformation of the temporal network to a static directed and weighted graph, and some recent approximation algorithm for finding the minimum Directed Steiner Tree. We finally generalize our framework to the streaming setting in which new snapshots of the temporal graph keep arriving continuously and our goal is to produce a community search solution for the temporal graph corresponding to a sliding time window.
Compression Boosts Differentially Private Federated Learning

Federated Learning allows distributed entities to train a common model collaboratively without sharing their own data. Although it prevents data collection and aggregation by exchanging only parameter updates, it remains vulnerable to various inference and reconstruction attacks where a malicious entity can learn private information about the participants' training data from the captured gradients. Differential Privacy is used to obtain theoretically sound privacy guarantees against such inference attacks by noising the exchanged update vectors. However, the added noise is proportional to the model size which can be very large with modern neural networks. This can result in poor model quality. In this paper, compressive sensing is used to reduce the model size and hence increase model quality without sacrificing privacy. We show experimentally, using 2 datasets, that our privacy-preserving proposal can reduce the communication costs by up to 95 % with only a negligible performance penalty compared to traditional non-private federated learning schemes.
Robust Reinforcement Learning for General Video Game Playing

Reinforcement learning has successfully learned to play challenging board and video games. However, its generalization ability remains under-explored. The General Video Game AI Learning Competition aims at designing agents that are capable of learning to play different games levels that were unseen during training. This paper presents the games, entries and results of the 2020 General Video Game AI Learning Competition, held at the Sixteenth International Conference on Parallel Problem Solving from Nature and the 2020 IEEE Conference on Games. Three new games with sparse, periodic and dense rewards, respectively, were designed for this competition and the test levels were generated by adding minor perturbations to training levels or combining training levels. In this paper, we also design a reinforcement learning agent, called Arcane, for general video game playing. We assume that it is more likely to observe similar local information in different levels rather than global information. Therefore, instead of directly inputting a single, raw pixel-based screenshot of current game screen, Arcane takes the encoded, transformed global and local observations of the game screen as two simultaneous inputs, aiming at learning local information for playing new levels. Two versions of Arcane, using a stochastic or deterministic policy for decision-making during test, both show robust performance on the game set of the 2020 General Video Game AI Learning Competition.
A 2‐component Camassa‐Holm Equation, Euler‐Bernoulli Beam Problem, and Noncommutative Continued Fractions

A new approach to the Euler‐Bernoulli beam based on an inhomogeneous matrix string problem is presented. Three ramifications of the approach are developed: motivated by an analogy with the Camassa‐Holm equation a class of isospectral deformations of the beam problem is formulated; a reformulation of the matrix string problem in terms of a certain compact operator is used to obtain basic spectral properties of the inhomogeneous matrix string problem with Dirichlet boundary conditions; the inverse problem is solved for the special case of a discrete Euler‐Bernoulli beam. The solution involves a noncommutative generalization of Stieltjes’ continued fractions, leading to the inverse formulas expressed in terms of ratios of Hankel‐like determinants.
Transmission of a Bit over a Discrete Poisson Channel with Memory

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated to the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we find the best codebook design by minimizing the error probability of the decoder over all codebooks. For the case of having only a total-power constraint, the optimal code structure is obtained provided that the blocklength is greater than the memory length of the channel. For the case of having only a peak-power constraint, the optimal code is derived for arbitrary memory and blocklength in the high-power regime. For the case of having both the peak-power and total-power constraints, the optimal code is derived for memoryless Poisson channels when both the totalpower and the peak-power bounds are large.
Higher-Derivative Supergravity, Wrapped M5-branes, and Theories of Class $\mathcal{R}$

We study the interplay between four-derivative 4d gauged supergravity, holography, wrapped M5-branes, and theories of class $\mathcal{R}$. Using results from Chern-Simons theory on hyperbolic three-manifolds and the 3d-3d correspondence we are able to constrain the two independent coefficients in the four-derivative supergravity Lagrangian. This in turn allows us to calculate the subleading terms in the large-$N$ expansion of supersymmetric partition functions for an infinite class of three-dimensional $\mathcal{N}=2$ SCFTs of class $\mathcal{R}$. We also determine the leading correction to the Bekenstein-Hawking entropy of asymptotically AdS$_4$ black holes arising from wrapped M5-branes. In addition, we propose and test some conjectures about the perturbative partition function of Chern-Simons theory with complexified ADE gauge groups on closed hyperbolic three-manifolds.