Miracle-dz/UniFAR-FTUs huggingface dataset:
High rate of adaptation of mammalian proteins that interact with Plasmodium and related parasites

Plasmodium parasites, along with their Piroplasm relatives, have caused malaria-like illnesses in terrestrial mammals for millions of years. Several Plasmodium-protective alleles have recently evolved in human populations, but little is known about host adaptation to blood parasites over deeper evolutionary timescales. In this work, we analyze mammalian adaptation in ~500 Plasmodium- or Piroplasm- interacting proteins (PPIPs) manually curated from the scientific literature. We show that (i) PPIPs are enriched for both immune functions and pleiotropy with other pathogens, and (ii) the rate of adaptation across mammals is significantly elevated in PPIPs, compared to carefully matched control proteins. PPIPs with high pathogen pleiotropy show the strongest signatures of adaptation, but this pattern is fully explained by their immune enrichment. Several pieces of evidence suggest that blood parasites specifically have imposed selection on PPIPs. First, even non-immune PPIPs that lack interactions with other pathogens have adapted at twice the rate of matched controls. Second, PPIP adaptation is linked to high expression in the liver, a critical organ in the parasite life cycle. Finally, our detailed investigation of alpha-spectrin, a major red blood cell membrane protein, shows that domains with particularly high rates of adaptation are those known to interact specifically with P. falciparum. Overall, we show that host proteins that interact with Plasmodium and Piroplasm parasites have experienced elevated rates of adaptation across mammals, and provide evidence that some of this adaptation has likely been driven by blood parasites.
A 1 V 10 bit 25 kS/s VCO-based ADC for implantable neural recording

A differential-input A/D converter (ADC) based on voltage-controlled oscillator (VCO) is proposed for implantable bioelectronics. Two single-ended VCO-based ADCs are matched and combined to support differential input, hence suppressing the common-mode interference and even harmonics distortion. A 10-bit binary subtraction circuit, which is utilized to process the digital output of two matched ADCs, generates the final digital output. The subtraction circuit is realized with Domino logic gates for further reduction in power consumption and chip area. Designed with 0.18 μm CMOS process, the 10 bit 25 kS/s VCO-based ADC can operate under 1 V power supply. The active area of this ADC is 270 μm × 100 μm, much smaller than a successive-approximation-register (SAR) ADC with similar performance.
A Fast and Accurate Rule-Base Generation Method for Mamdani Fuzzy Systems

The problem of learning fuzzy rule bases is analyzed from the perspective of finding a favorable balance between the accuracy of the system, the speed required to learn the rules, and, finally, the interpretability of the rule bases obtained. Therefore, we introduce a complete design procedure to learn and then optimize the system rule base, called the precise and fast fuzzy modeling approach. Under this paradigm, fuzzy rules are generated from numerical data using a parameterizable greedy-based learning method called selection-reduction, whose accuracy–speed efficiency is confirmed through empirical results and comparisons with reference methods. Qualitative justification for this method is provided based on the coaction between fuzzy logic and the intrinsic properties of greedy algorithms. To complete the precise and fast fuzzy modeling strategy, we finally present a rule-base optimization technique driven by a novel rule redundancy index, which takes into account the concepts of the distance between rules and the influence of a rule over the dataset. Experimental results show that the proposed index can be used to obtain compact rule bases, which remain very accurate, thus increasing system interpretability.
Low-Complexity Propagator Based Two Dimensional Angle Estimation for Coprime MIMO Radar

The problem of 2-D angle estimation for coprime multiple-input multiple-output (MIMO) radar is considered, and a low-complexity propagator based method is proposed. Coprime MIMO radar is configured with transmit and receive rectangular arrays, where transmit array has <inline-formula> <tex-math notation="LaTeX">$\text{N}\times \text{Q}$ </tex-math></inline-formula> elements while receive array has <inline-formula> <tex-math notation="LaTeX">$\text{M}\times \text{P}$ </tex-math></inline-formula> elements (M is coprime to N while P is coprime to Q). Based on the uniformities of the arrays, unitary transformation is exploited to transform the complex data into real-valued one, and then the signal subspace is obtained from a low-complexity propagator matrix, which requires neither eigenvalue decomposition nor pseudo inversion. Thereafter, automatically paired two pairs of coprime parameter estimations can be acquired based on the rotational invariance within the signal subspace. Finally, unique 2-D angle can be estimated from the coincide result of the coprime estimations. Due to the real-valued propagator based method, the proposed method has low complexity, but it can achieve better angle estimation results than conventional methods. Theoretical analysis of the method is derived, and simulation results are presented to verify the effectiveness of the proposed approach.
Adaptive Fuzzy Decentralized Control for a Class of Strong Interconnected Nonlinear Systems With Unmodeled Dynamics

The state-feedback decentralized stabilization problem is considered for interconnected nonlinear systems in the presence of unmodeled dynamics. The functional relationship in affine form between the strong interconnected functions and error signals is established, which makes backstepping-based fuzzy control successfully generalized to strong interconnected nonlinear systems. By combining adaptive control with both backstepping design and the approximation property of fuzzy systems, an adaptive decentralized control algorithm is developed. It is demonstrated by both theoretical analysis and simulation study that the proposed control strategy ensures semiglobally uniformly ultimately bounded of all signals within the closed-loop systems.
Staining for viability testing, germination and maturation of Sambucus nigra L. pollen in vitro

Abstract Freshly released pollen of black elderberry (Sambucus nigra L.) was incubated under various culture conditions until germination was achieved. Optimal conditions for germination were determined and used for maturation of unicellular microspores in vitro. Staining with 5-diphenyltetrazolium bromide, propidium iodide and iodine potassium iodide was used to assess pollen viability, nuclear phase and maturation, respectively. The germination rate was highest when fresh pollen was agitated at 40 rpm in Petri dishes containing a liquid medium consisting of Brewbaker and Kwack salts, 15% (w/v) sucrose, 500 mg/l MES sodium salt, at pH 5.0; germination reached nearly 70% after only 1 h in culture. Under these conditions, and with addition of 200 mg/l glutamine, 260 mg/l cytidine and 500 mg/l uridine, uninucleate microspores developed into mature pollen at a 12% germination rate. Our report is the first demonstration of maturation of S. nigra microspores in vitro.
Data Fusion and Type-2 Fuzzy Inference in Contextual Data Stream Monitoring

Data stream monitoring provides the basis for building intelligent context-aware applications over contextual data streams. A number of wireless sensors could be spread in a specific area and monitor contextual parameters for identifying various phenomena, e.g., fire or flood. A back-end system receives measurements and derives decisions for possible abnormalities related to negative effects. We propose a mechanism which, based on multivariate sensors data streams, provides real-time identification of phenomena. The proposed framework performs contextual information fusion over consensus theory for the efficient measurements aggregation while time-series prediction is adopted to result future insights on the aggregated values. The unanimous fused and predicted pieces of context are fed into a type-2 fuzzy inference system to derive highly accurate identification of events. The type-2 inference process offers reasoning capabilities under the uncertainty of the phenomena identification. We provide comprehensive experimental evaluation over real contextual data and report on the advantages and disadvantages of the proposed mechanism. Our mechanism is further compared with type-1 fuzzy inference and other mechanisms to demonstrate its false alarms minimization capability.
Arcobacter canalis sp. nov., isolated from a water canal contaminated with urban sewage.

Four bacterial strains recovered from shellfish (n=3) and from the water (n=1) of a canal contaminated with urban sewage were recognized as belonging to a novel species of the genus Arcobacter (represented by strain F138-33T) by using a polyphasic characterization. All the new isolates required 2 % NaCl to grow. Phylogenetic analyses based on 16S rRNA gene sequences indicated that all strains clustered together, with the most closely related species being Arcobacter marinus and Arcobactermolluscorum. However, phylogenetic analyses using the concatenated sequences of housekeeping genes (atpA, gyrB, hsp60, gyrA and rpoB) showed that all the novel strains formed a distinct lineage within the genus Arcobacter. Results of in silico DNA-DNA hybridization and the average nucleotide identity between the genome of strain F138-33T and those of the closely related species A. marinus and other relatively closely related species such as A. molluscorum and Arcobacterhalophilus were all below 70 and 96 %, respectively. All the above results, together with the 15 physiological and biochemical tests that could distinguish the newly isolated strains from the closely related species, confirmed that these strains represent a novel species for which the name Arcobacter canalis sp. nov. is proposed, with the type strain F138-33T (=CECT 8984T=LMG 29148T).
Deletion of the Vaccinia Virus B1 Kinase Reveals Essential Functions of This Enzyme Complemented Partly by the Homologous Cellular Kinase VRK2

ABSTRACT The vaccinia virus B1 kinase is highly conserved among poxviruses and is essential for the viral life cycle. B1 exhibits a remarkable degree of similarity to vaccinia virus-related kinases (VRKs), a family of cellular kinases, suggesting that the viral enzyme has evolved to mimic VRK activity. Indeed, B1 and VRKs have been demonstrated to target a shared substrate, the DNA binding protein BAF, elucidating a signaling pathway important for both mitosis and the antiviral response. In this study, we further characterize the role of B1 during vaccinia infection to gain novel insights into its regulation and integration with cellular signaling pathways. We begin by describing the construction and characterization of the first B1 deletion virus (vvΔB1) produced using a complementing cell line expressing the viral kinase. Examination of vvΔB1 revealed that B1 is critical for the production of infectious virions in various cell types and is sufficient for BAF phosphorylation. Interestingly, the severity of the defect in DNA replication following the loss of B1 varied between cell types, leading us to posit that cellular VRKs partly complement for the absence of B1 in some cell lines. Using cell lines devoid of either VRK1 or VRK2, we tested this hypothesis and discovered that VRK2 expression facilitates DNA replication and allows later stages of the viral life cycle to proceed in the absence of B1. Finally, we present evidence that the impact of VRK2 on vaccinia virus is largely independent of BAF phosphorylation. These data support a model in which B1 and VRK2 share additional substrates important for the replication of cytoplasmic poxviruses. IMPORTANCE Viral mimicry of cellular signaling modulators provides clear evidence that the pathogen targets an important host pathway during infection. Poxviruses employ numerous viral homologs of cellular proteins, the study of which have yielded insights into signaling pathways used by both virus and cells alike. The vaccinia virus B1 protein is a homolog of cellular vaccinia virus-related kinases (VRKs) and is needed for viral DNA replication and likely other stages of the viral life cycle. However, much remains to be learned about how B1 and VRKs overlap functionally. This study utilizes new tools, including a B1 deletion virus and VRK knockout cells, to further characterize the functional links between the viral and cellular enzymes. As a result, we have discovered that B1 and VRK2 target a common set of substrates vital to productive infection of this large cytoplasmic DNA virus.
Placenta in Preterm Birth

To the perinatal pathologists, preterm births are those occurring at less than 37 weeks of gestation. In almost all countries with reliable data, preterm birth rates have increased worldwide. The complications of preterm birth due to prematurity are often serious com‐ munity health problems and account for 75% of perinatal mortalities and more than 50% of long-term infant morbidities [1]. Globally, prematurity is the leading cause of newborn deaths and now the second leading cause of death after pneumonia in children under the age of five [2]. The complications of prematurity include adverse cognitive, organ functional and motor outcomes. Moreover, preterm infants have increased rates chronic lung disease, necrotizing enterocolitis and neurological sequels including periventricular leukomalacia. Later in childhood, they have reduced motor, intellectual and behavioral skills compared to children born at term.
Applications of Mass Spectrometric Techniques to the Analysis of Fuels and Lubricants

The application of mass spectrometric techniques for the analysis of the complex mix‐ tures inherent in fuel and lubricant samples will be examined. These samples because they are naturally complex mixtures, typically requires either very high resolution mass spectrometry or one of the hyphenated techniques gas chromatography‐mass spectrometry(GC‐MS) or liquid chromatography‐mass spectrometry (LC‐MS). Some fuel problems that can be addressed through mass spectrometry are associated with the changes in composition and degradation of fuels as they age, including the analysis of both major hydrocarbon components non‐polar components and minor polar compo‐ nents will be described. The properties and composition of natural and major classes of synthetic lubricants, the presence of additives and the problems that develop as the lubri‐ cant is used such as additive depletion, thermal and oxidative degradation and lubricant contamination have also been examined using mass spectrometric techniques. esters. Each of these categories of lubricants has characteristic features which allow them to be identified.
Localization of cortical cataract in subjects of diverse races and latitude.

PURPOSE To compare the characteristics of early cortical cataract localization in three groups in cataract epidemiologic surveys performed in Reykjavík, Melbourne, and Singapore. METHODS Individuals who had right eyes with an area of cortical opacity less than 20% of the pupil when dilated 7 mm or more were selected as subjects. This included 197 subjects from the Reykjavík Eye Study, 231 from the Vitamin E, Cataract, and Age-Related Maculopathy (VECAT) study in Melbourne, and 92 from the Singapore-Japan Cooperative Cataract Study, all showing early-stage cataract in pupils dilated to 7 mm or more. Scheimpflug and retroilluminated photographs were used to locate opacities. Localization of cortical cataract was determined by dividing the retroillumination image into seven concentric circles with diameters of 1 through 7 mm, and eight sections of 45 degrees radial octants. The positive rate of opacification was then calculated for each quadrant. RESULTS The highest positive rate of opacification was observed in the lower nasal quadrant in all groups. The relative risk of the prevalence of cortical opacity in the lower nasal oblique hemisphere to the upper temporal oblique hemisphere was the highest in the Singaporean subjects followed by those of Melbourne and then of Reykjavík. CONCLUSIONS The prevalence of cortical cataract was higher in the lower nasal quadrant than in the other quadrants for all subjects of diverse race in three climatically different locations. This higher prevalence was most pronounced in subjects living at low latitude. These results support the view that solar UV exposure is a possible risk factor for development of human cortical cataract.
Controllable Video Generation with Sparse Trajectories

Video generation and manipulation is an important yet challenging task in computer vision. Existing methods usually lack ways to explicitly control the synthesized motion. In this work, we present a conditional video generation model that allows detailed control over the motion of the generated video. Given the first frame and sparse motion trajectories specified by users, our model can synthesize a video with corresponding appearance and motion. We propose to combine the advantage of copying pixels from the given frame and hallucinating the lightness difference from scratch which help generate sharp video while keeping the model robust to occlusion and lightness change. We also propose a training paradigm that calculate trajectories from video clips, which eliminated the need of annotated training data. Experiments on several standard benchmarks demonstrate that our approach can generate realistic videos comparable to state-of-the-art video generation and video prediction methods while the motion of the generated videos can correspond well with user input.
Screening for adult attention deficit/hyperactivity disorder in high‐dose benzodiazepine dependent patients

BACKGROUND AND OBJECTIVES Adult attention-deficit/hyperactivity disorder (ADHD) is frequent in patients with substance use disorders (SUD), but information on its prevalence in high-dose benzodiazepine (BZD) dependence is lacking. We estimated the prevalence of adult ADHD in a group of treatment-seeking high-dose BZD dependent patients according to a valid screening tool, and explored the demographic and clinical characteristics of patients that screened positive for ADHD (ADHD+) in comparison to those that screened negative (ADHD-). METHODS We prospectively recruited 167 consecutive patients with high-dose BZD dependence and screened them for adult ADHD with the World Health Organization Adult ADHD Self-Report Scale version 1.1 (ASRS-v1.1) Symptom Checklist Part A. We compared demographic and clinical characteristics in ADHD+ and ADHD- groups. RESULTS Fifty-three patients (31.7% of the sample) were positive to adult ADHD screening. ADHD+ patients showed a significantly larger prevalence of poly-drug abuse than ADHD- ones. BZD formulation and active principle significantly differed between the two groups. The other clinical variables, including psychiatric comorbidity, as well as the demographic ones, did not differ in ADHD+ versus ADHD- comparison. DISCUSSION AND CONCLUSIONS Adult ADHD may be common in treatment-seeking high-dose BZD dependent patients according to ASRS-v1.1 Symptom Checklist Part A. SCIENTIFIC SIGNIFICANCE Screening for ADHD in this type of SUD with this questionnaire is quick and may offer useful information for prognosis and treatment. (Am J Addict 2017;26:610-614).
Neural Autoregressive Flows

Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to accelerate state-of-the-art WaveNet-based speech synthesis to 20x faster than real-time, via Inverse Autoregressive Flows (IAF). We unify and generalize these approaches, replacing the (conditionally) affine univariate transformations of MAF/IAF with a more general class of invertible univariate transformations expressed as monotonic neural networks. We demonstrate that the proposed neural autoregressive flows (NAF) are universal approximators for continuous probability distributions, and their greater expressivity allows them to better capture multimodal target distributions. Experimentally, NAF yields state-of-the-art performance on a suite of density estimation tasks and outperforms IAF in variational autoencoders trained on binarized MNIST.
Training Very Deep CNNs for General Non-Blind Deconvolution

Non-blind image deconvolution is an ill-posed problem. The presence of noise and band-limited blur kernels makes the solution of this problem non-unique. Existing deconvolution techniques produce a residual between the sharp image and the estimation that is highly correlated with the sharp image, the kernel, and the noise. In most cases, different restoration models must be constructed for different blur kernels and different levels of noise, resulting in low computational efficiency or highly redundant model parameters. Here we aim to develop a single model that handles different types of kernels and different levels of noise: general non-blind deconvolution. Specifically, we propose a very deep convolutional neural network that predicts the residual between a pre-deconvolved image and the sharp image rather than the sharp image. The residual learning strategy makes it easier to train a single model for different kernels and different levels of noise, encouraging high effectiveness and efficiency. Quantitative evaluations demonstrate the practical applicability of the proposed model for different blur kernels. The model also shows the state-of-the-art performance on synthesized blurry images.
The Zn-finger domain of human PrimPol is required to stabilize the initiating nucleotide during DNA priming

Abstract Human PrimPol is a monomeric enzyme whose DNA primase activity is required to rescue stalled replication forks during nuclear and mitochondrial DNA replication. PrimPol contains an Archeal-Eukaryotic Primases (AEP) core followed by a C-terminal Zn finger-containing domain (ZnFD), that is exclusively required for primer formation and for PrimPol function in vivo. The present study describes the sequential substrate interactions of human PrimPol during primer synthesis, and the relevance of the ZnFD at each individual step. Both the formation of a PrimPol:ssDNA binary complex and the upcoming interaction with the 3′-nucleotide (pre-ternary complex) remained intact when lacking the ZnFD. Conversely, the ZnFD was required for the subsequent binding and selection of the 5′-nucleotide that will become the first nucleotide of the new primer strand. Providing different 5′-site nucleotides, we can conclude that the ZnFD of PrimPol most likely interacts with the γ-phosphate moiety of the 5′-site nucleotide, optimizing formation of the initial dimer. Moreover, the ZnFD also contributes to recognize the cryptic G at the preferred priming sequence 3′GTC5′. Dimer elongation to obtain long DNA primers occurs processively and is facilitated by the 5′-terminal triphosphate, indicating that the ZnFD is also essential in the subsequent translocation/elongation events during DNA primer synthesis.
Simulating DDOS attacks on the us fiber-optics internet infrastructure

Network-based attacks like the distributed denial-of-service (DDoS) attacks are not new, but we are beginning to see attacks of unprecedented scale. Examples of such attacks include the 2016 attack on DYN INC that crippled a part of the Internet for hours, and the attack on Liberia, which partially brought down the African nation. Limitations in identifying vulnerable Internet infrastructure and testing possible defense strategies are a part of the problem. We need a simulation testbed that can reflect the complexity of the Internet, yet allows to swiftly test attacks, providing insights that can apply to real-world attack scenarios. In this research, we have designed a test-bed that mirrors the Internet infrastructure of the US and can simulate the Internet traffic flow patterns for different attack targets. We also estimate the degradation in the quality-of-service and the number of users impacted in two attack scenarios.