Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Factors that Promote the Growth of Dormant Mycobacterium avium subsp. paratuberculosis

Johne’s disease, which is caused by the acid-fast bacterium Mycobacterium avium subspecies paratuberculosis (Mpt), is a chronic, inflammatory intestinal disease that primarily affects ruminants. This disease has a significant effect on the economics of dairy farming. Mpt has a remarkable ability to survive in host tissues for 2-6 years without producing any signs of infection. However, the reliability of diagnostic techniques is limited only to those animals with clinical disease. This may be due to the entry of the organism into a dormant state, which has been reported for other mycobacteria. Reversion to the actively growing state (resuscitation) would improve the sensitivity of diagnostic culture; however, the substances effecting resuscitation have not been defined. Previous work in our laboratory showed that conditioned medium obtained from starvation-dormant Mpt (SDCM) enhanced the resuscitation of dormant Mpt. Research by others demonstrated that resuscitation of other dormant mycobacterial pathogens was enhanced by resuscitation promoting factors (Rpf), a class of 17-19 kDa proteins that are secreted by these organisms. We therefore hypothesized that one or more Rpf was responsible for the resuscitative activity in SDCM. In this study, we sought to identify and characterize fractions of SDCM that contain resuscitative activity. SDCM was fractionated into 6 molecular weight classes, and each fraction was tested for the ability to promote the resuscitation of anaerobically dormant Mpt responder cells. Most (if not all) of this activity was confined to a fraction containing molecules with a molecular weight of 5 kDa or less (F5). To characterize F5, this fraction was subjected to
Calibrating Median and Uncertainty Estimates for a Practical Use of Empirical Green’s Functions Technique

The empirical Green’s functions (EGF) technique is used to investigate two methods for predicting ground motion in a sedimentary basin for a future earthquake, including variability assessment. This study focuses on the Grenoble basin (French Alps). The basic principle of both methods is to generate a variety of source parameter sets based on a grid testing approach. Next, these sets are used to compute a population of ground motions by means of a kinematic EGF method and to estimate ground-motion variability. The first method tried, called the direct-parameter-input approach, selects input parameter combinations from assumed source parameter probability density functions. It is demonstrated that this approach leads to overestimated variability. Moreover, these simulation results are not calibrated. A new (screened-parameter-input) procedure is therefore proposed: (1) reference rock site response spectra are simulated for fractiles of several orders using empirical ground-motion prediction equations; (2) a large population of rock site response spectra is generated by means of the EGF method with varying rupture parameter combinations; (3) the spectra that do not fit the empirical motion for the chosen fractiles are screened out and sets of permissible source parameter combinations are thus obtained; (4) sediment site response spectra are computed with this EGF procedure and with these permissible parameter combinations; and (5) for each frequency median spectral acceleration and standard-deviation values are derived.
SONOGASHIRA COUPLING REACTION CATALYZED BY GOLD NANOCATALYST UNDER MICROWAVE: EFFECT OF SIZE AND SHAPE.

Damra E. Mustafa 1 , Safia A/Alla Elhag 1 and Aidong Zhang 2 . 1. College of Applied and Industrial Science, University of Bahri, Sudan. 2. Key Laboratory of Pesticide & Chemical Biology of Ministry of Education, Central China Normal University, Wuhan 430079, P. R. China. Manuscript Info Abstract . Manuscript History
Strongly non-linear magnetization dynamics in nano-structures: perturbations, multi-mode generation, and topological droplets

Spin torque oscillators (STOs) are magnetic nano-devices in which strongly non-linear magnetodynamic phenomena can be excited by current. In this thesis, we study some of these phenomena by means of micromagnetic simulations, analytical calculations, and electrical characterization. Three main subjects are discussed: 1. External perturbations, which can induce synchronization and modulation. In the former case, STOs are shown to exhibit an under-damped or non-Adlerian behavior, defining a minimum synchronization time. For the latter, slow external sources can induce the so-called Nonlinear Amplitude and Frequency Modulation, from which the modulation bandwidth is defined. Both perturbations can be combined for the technologically relevant case of synchronized and modulated STOs. It is shown that regimes of resonant and non-resonant unlocking exist. 2. Multi-mode generation of STOs is described by a novel analytical framework. In particular, the generation linewidth is calculated, and it is shown to be intrinsically related to the coupling between multiple modes. Mode coexistence is found to be analytically possible and, further, observed experimentally and numerically. Electrical characterization of in-house fabricated devices confirms the analytical predictions and suggests the possibility of fine-tuning and controlling spin wave propagation at the nanoscale. 3. Topological droplets are numerically shown to exist when the STOs are patterned into nanowires. The following droplet modes have been found: a non-topological edge mode that is attracted by the physical boundaries and increases its footprint to satisfy the damping / spin torque balance, and a topological (chiral) quasi-one-dimensional droplet that can be considered as the dynamical counterpart of breathing soliton-soliton pairs.
Moniliformis cryptosaudi n. sp. (Acanthocephala: Moniliformidae) from the Long-eared Hedgehog Hemiechinus auritus (Gmelin) (Erinaceidae) in Iraq; A Case of Incipient Cryptic Speciation Related to M. saudi in Saudi Arabia

Moniliformis cryptosaudi n. sp. (Moniliformidae) is an acanthocephalan described from the long-eared hedgehog Hemiechinus auritus (Gmelin) (Erinaceidae) in Iraq as an incipient cryptic species of Moniliformis saudi Amin, Heckmann, Mohammed, Evans, 2016 described from the desert hedgehog Paraechinus aethiopicus (Ehrenberg) (Erinaceidae) in Saudi Arabia. Microscopical studies demonstrate that the two species are morphologically indistinguishable with practically identical measurements and counts but differed significantly in their energy dispersive X-ray analysis (EDXA) of metal composition of hooks. Hooks of specimens of the new species appeared to be of collagen material with very low levels of phosphorus and calcium unlike those of M. saudi and Moniliformis kalahariensis Meyer, 1931 that had high levels of calcium and phosphorus. Using 18S rDNA and cox1 genes, M. Saudi and M. kalahariensis were shown to be molecularly distinct but the molecular profiles of M. saudi and M. cryptosaudi were more similar. The molecular profile of M. kalahariensis collected from the South African hedgehog Atelerix frontalis Smith (Erinaceidae) in South Africa is reported for the first time and is studied only for comparative purposes. Moniliformis saudi and M. kalahariensis had comparable EDXA metal analysis that was distinct from that of M. cryptosaudi.
Fast tree-based wavelet image coding with efficient use of memory

In this paper, we present a new wavelet image encoder that focuses on overcoming the main drawbacks of other wavelet based-image coders; their high memory requirements and complexity. In our proposal, we tackle these problems in both parts of the wavelet coder, both the DWT algorithm and the coding system. For the DWT, we propose the use of a line-based algorithm, in which we get rid of the wavelet coefficients as soon as they have been calculated. Some previous line-based proposals cannot be easily implemented, and here we describe a recursive algorithm that is implemented more easily. For the coding system, we use a tree-based coder. These coders have evidenced good Rate/Distortion (R/D) performance. However, it has not been clearly shown their excellent possibilities for fast processing of coefficients. Previous tree-based proposals need the entire image in memory to work and so they cannot be used in our system. Other wavelet encoders achieve good R/D performance, but exhibit high complexity. Our proposal is simpler and therefore faster. Numerical results show that the compression performance of our tree-based encoder is equal or better than state-of- the-art coders, such as SPIHT and JPEG 2000, except for highly detailed images. However, the real benefits of our proposal is shown in the amount of memory required, which is reduced drastically (in the order of 25 times less memory than SPIHT and more than 35 times less than JPEG 2000), and in its lower execution time (about four times lower than SPIHT, and more than 20 times lower than JPEG 2000). These results show that our encoder is a good candidate for many embedded systems and other memory-constrained environments, such as digital cameras and PDAs.
Privacy Issues and Protection in Secure Data Outsourcing

Utilizing database encryption to safeguard data in several conditions where access control is not sufficient is unavoidable. Database encryption offers an extra layer of security to traditional access control methods. It stops users that are unauthorized, such as hackers breaking into a system, and observing private data. Consequently, data is safe even when the database is stolen or attacked. Nevertheless, the process of data decryption and encryption causes degradation in the database performance. In conditions where the entire information is kept in an encrypted format, it is not possible to choose the database content any longer. The data must be first decrypted, and as such, the unwilling and forced tradeoff occurs between the function and the security. The suitable methods to improve the function are techniques that directly deal with the data that is encrypted without having to decrypt them first. In this study, we determined privacy protection and issues that each organization should consider when it decides to outsource own data.
Inapproximability within W [ 1 ] : the case of Steiner Orientation

In the k-Steiner Orientation problem we are given a mixed graph, that is, with both directed and undirected edges, and a set of k terminal pairs. The goal is to find an orientation of the undirected edges that maximizes the number of terminal pairs for which there is a path from the source to the sink. The problem is known to be W[1]-hard when parameterized by k and hard to approximate up to some constant for FPT algorithms assuming Gap-ETH. On the other hand, no approximation better than O(k) is known. We show that k-Steiner Orientation admits no sublogarithmic approximation algorithm, even with a parameterized running time, assuming W[1] 6= FPT. To obtain this result, we reduce the problem to itself via a hashing-based gap amplification technique, which turns out useful even outside of the FPT paradigm. Precisely, we rule out any approximation ratio of the form (log k) for parameterized algorithms and (log n) for purely polynomial running time, under the same assumption. This constitutes a novel inapproximability result for polynomial time algorithms obtained via tools from the FPT theory. Moreover, we prove k-Steiner Orientation to be W[1]-complete, what provides an example of a natural approximation task that is complete in a parameterized complexity class. Finally, we apply our technique to the maximization version of Directed Multicut and obtain a simple proof that the problem admits no FPT approximation with ratio O(k 1 2−ε) (assuming W[1] 6= FPT) and no polynomial-time approximation with ratio O(m 12−ε) (assuming NP 6⊆ co-RP). ∗Address: m.wlodarczyk@mimuw.edu. pl. This work is part of the project TOTAL that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 677651). 1 ar X iv :1 90 7. 06 52 9v 2 [ cs . C C ] 2 8 Ju l 2 01 9
Infrastructure-Based Access Policy Enforcement Using Software-Defined Networks

Title: Infrastructure-Based Access Policy Enforcement Using Software-Defined Networks Author: Tyler Carden Culp Major Advisor: Thomas C. Eskridge, Ph.D. This thesis describes a method to enhance network security using software defined networks. Standard networks use perimeter-based defenses to block attackers from gaining access to internal systems. A key problem with standard networks is that once a malicious entity has gained access to the network, they are often able to freely move throughout the network and to attack internal systems with impunity. This problem can be mitigated by placing defenses such as firewalls between machines on the network, but this approach requires significant resources and constant maintenance. If the network infrastructure itself is leveraged as a defense by individualizing the visibility of the network for each user according to their roles and permissions, then the resulting network will eliminate most or all of the actions attackers would take to monitor and attack the network from the inside. This type of defense requires identifying the sources of communication, enforcing global permissions, and dynamically updating the user’s view of the network.
Sublethal Doses of Inorganic Mercury Induce Dose-Depended Upregulation of RPA1 Content and Inhibit p53 Expression in the Brain of Rainbow Trout (Oncorhynchus mykiss)

Civa (Hg), su ortaminin en toksik ve yaygin unsurlarindan biridir. Hemen hemen her balik turu Hg’ ya maruz kaldigi zaman bunu dokularinda biriktirebilir. Civa ile induklenen hucresel fonksiyon bozuklugu, sucul ortamdaki kirlenme riskini tahmin etmek icin yeterli biyobelirtec olarak kullanilabilir. Beyin hucreleri, civa bilesiklerinin sitoksisitesine karsi oldukca hassastir. Cesitli civa turleri, beyin hucrelerinin hem yapisi hem de islevi uzerinde farkli zararli etkilere sahiptir. Son zamanlarda yapilan calismalarda inorganik civanin norotoksisitesi tartisilmaya devam etse de tamamiyla incelenmemistir. Bu calismada organik civanin subletal dozlarina maruz birakilan gokkusagi alabaliginin beyin dokusunda rpa1 ve p53 proteinlerinin rolunu arastirdik. Sunulan calismada civa klorurun LD 50 degeri, 96 saat maruz kalma ile 551 μg / L olarak belirlenmistir. Gokkusagi alabaliklari 2 ve 7 gunluk zaman araliklarinda iki subletal doza maruz birakildi. Civa klorure maruz birakilan baliklarin beyin dokusunda doz ve zaman bagimli olarak ROS seviyesinde bir artis belirlenmistir. Ayrica, hem % 25 hem de % 50 LD 50 civa dozlarina maruz kalma suresince RPA1 ekspresyonunun onemli olcude upregulasyonuna neden olmustur. 2 gun sure ile Hg maruz birakilan baliklarin beyin dokusunda, p53 ekspresyonunu zayif bir sekilde uyarmistir. Bunun tam tersine olarak, 7 gunluk maruz kalma, p53 ekspresyonunda onemli bir azalmaya neden oldu. Sunulan calismanin sonuclari inorganik civanin alt dozlarinin son derece norotoksik oldugunu ve stres sensoru proteini p53 un azalmasi ile balik beyni sinyal yollarinda bozukluga neden olabilecegini kanitlamaktadir. Ayrica, RPA1 ekspresyonundaki artis, baliklarin beyin hucrelerinin ROS kaynakli DNA kirilmalarini tamir edebilecegini ve inorganik Hg'nin genotoksik etkisini onleyebilecegini gostermektedir. Genel olarak, mevcut veriler inorganik civalarin balik beyin hucrelerine toksik oldugunu ve bu sorunun gelecekte de arastirilmasinin gerekliligine isaret etmektedir.
German handball TV demand: did it pay for the Handball-Bundesliga to move from free to pay TV?

ABSTRACT Research question In an increasingly segmented TV market, niche sports rights owners competing with giants such as professional football often face the question of whether it ultimately pays for them to move from a free to a pay TV distribution strategy – that is, behind a paywall. Interestingly, at present, sport management research has not provided a definitive answer to this critical question. Research methods In this short paper, we address this question by exploring German TV audience demand for all 404 handball games broadcast during the three most recent seasons: 2015/16, 2016/17 and 2017/18. Results and findings Our results suggest that, despite hopes to the contrary, moving from a primarily free TV-based distribution strategy to a largely pay TV-based approach has decreased rather than increased the audience reach of the Handball-Bundesliga. On a more general note, we observe a positive role of both game outcome uncertainty and the absence of simultaneous fixtures in shaping German TV demand for professional handball. As such, our empirical results complement the otherwise rich literature on the determinants for professional sports by providing a first look at the potential determinants of niche sports TV demand, a previously neglected topic in sport management research. Implications Niche sport federations have to reflect carefully on their TV marketing strategy under digital plenitude.
Quantum Algorithm for Finding the Optimal Variable Ordering for Binary Decision Diagrams

An ordered binary decision diagram (OBDD) is a directed acyclic graph that represents a Boolean function. OBDDs are also known as special cases of oblivious read-once branching programs in the field of complexity theory. Since OBDDs have many nice properties as data structures, they have been extensively studied for decades in both theoretical and practical fields, such as VLSI design, formal verification, machine learning, and combinatorial problems. Arguably, the most crucial problem in using OBDDs is that they may vary exponentially in size depending on their variable ordering (i.e., the order in which the variable are to read) when they represent the same function. Indeed, it is NP hard to find an optimal variable ordering that minimizes an OBDD for a given function. Hence, numerous studies have sought heuristics to find an optimal variable ordering. From practical as well as theoretical points of view, it is also important to seek algorithms that output optimal solutions with lower (exponential) time complexity than trivial brute-force algorithms do. Friedman and Supowit provided a clever deterministic algorithm with time/space complexity $O^\ast(3^n)$, where $n$ is the number of variables of the function, which is much better than the trivial brute-force bound $O^\ast(n! 2^n)$. This paper shows that a further speedup is possible with quantum computers by demonstrating the existence of a quantum algorithm that produces a minimum OBDD together with the corresponding variable ordering in $O^\ast(2.77286^n)$ time and space with an exponentially small error. Moreover, this algorithm can be adapted to constructing other minimum decision diagrams such as zero-suppressed BDDs, which provide compact representations of sparse sets and are often used in the field of discrete optimization and enumeration.
National Laboratory Title Induced seismicity within geologic carbon sequestration projects : Maximum earthquake magnitude and leakage potential from undetected faults

With developing countries strongly relying on fossil fuels for energy generation, geological carbon sequestration (GCS) is seen as a candidate for large reductions in CO2 emissions during the next several decades. GCS does, however, raise some safety concerns. Specifically, it has been associated with induced seismicity, as a result of pressure buildup arising from prolonged CO2 injection in GCS projects. This seismicity is a delicate issue for two main reasons. First, over a short time scale, deformation of rock could release seismic energy, potentially affecting surface structures or simply alarming the population, with negative consequences for the social acceptance of this kind of project. Second, over a longer time scale, activated faults may provide preferential paths for CO2 leakage out of reservoirs. While known major faults intersecting target aquifers can be identified and avoided during site screening, the same might not be true for faults that are not resolvable by geophysical surveys. In this study, we use geological observations and seismological theories to estimate the maximum magnitude of a seismic event that could be generated by a fault of limited dimensions. We then compare our estimate with results of geomechanical simulations that consider faults with different hydrodynamic and geomechanical characteristics. The coupled simulations confirm the notion that the tendency of faults to be reactivated by the pressure buildup is linked with the in situ stress field and its orientation relative to the fault. Small, active (critically stressed) faults are capable of generating sufficiently large events that could be felt on the surface, although they may not be the source of large earthquakes. Active, relatively permeable faults may be detrimental concerning the effectiveness of a storage project, meaning that they could be preferential pathway for upward CO2 leakage, although minor faults may not intersect both CO2 reservoirs and shallower potable aquifers. *Manuscript Click here to view linked References
Machine learning to predict Reynolds stresses in transitional boundary layer fluid flow

Motivation and objectives Computation fluid dynamics (CFD) is often used to model the fluid flow along a surface. In calculating the Reynolds averaged Navier-Stokes (RANS) equations we find that modeling the Reynolds stresses is required and calculating these terms is a matter of research and various models have been proposed and adopted by the modeling community. However, calculating these terms in laminar to turbulent transitional boundary layer has proven difficult. Slotnick et al. (2014) states that the single most critical area in CFD simulation capability is the ability to predict viscous turbulent flows with possible boundary layer transition and flow separation present. Currently, in order to accurately solve these flows, expensive direct numerical simulations must be conducted to resolve the flow (e.g. Zaki, 2013). Models have been developed to reduce this cost (e.g. Langtry and Menter, 2009; Durbin, 2018), but, for various reasons, these models have resulted in poor performance in application and have not been widely adopted by the CFD community. Ling et al. (2016) applied a deep neural network to calculate the Reynolds stresses. The input to their model, however, required the full non-averaged velocity and pressure terms. These input features allowed for Galilean and rotational invariant coordinate system, which is an advantageous property for these systems. A major conclusion is that significant improvements over classical RANS closure solvers is possible using the deep neural network described there. The input to the model used in this work will retain the Galilean invariant property, but will not retain the rotational invariant property. This is done such that the model will take advantage of already readily available values in a typical CFD solver. These inputs are also very similar to the inputs used by Wu et al. (2019) where these features were used to identify the interface between turbulent and laminar portions of the boundary layer. The dataset used there was the same dataset used here in this research found in the work by Zaki (2013) and published online in the John Hopkins Turbulence Databases.