Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting an Insider Threat and Analysis of XGBoost using Hyperparameter tuning

Nowadays, organizations of all forms and sizes are facing many challenges with regards to protecting their data, systems and devices, and one of the alarming concernsis the Insider threat. Insiders try to misuse their privileges to compromise the privacy, integrity and accessibility of the data or the device. An Insider attack leads to immense loss to the company in terms of integrity, trust and revenue. There are many Machine Learning approaches to detect malicious insiders that provide solutions to these attacks. At the same time, they demonstrated short-comings with regards to performance and Accuracy. Therefore, in this paper, a novel machine learning model is proposed using XGBoost algorithm to address these problems. XGBoost is a decision-tree based ensemble machine learning algorithm that uses a gradient boosting framework that improves speed and performance. Hyper-parameter optimization using Grid Search was applied to enhance the performance of the model using the CERT 4.2 dataset to detect the insider. The model has generated the desired results with a high accuracy rate of 98.6%. A webform was also created using Flask Micro Web Framework that takes user attributes as an input and detects insider activity using the XGBoost model.
Parameter Characterization of Power MOSFET Gate Oxide Degradation Based on Current Falling Time during Turn-off Process

Power MOSFET is an indispensable key component in circuits and electronic systems. For power MOSFET, gate oxide degradation often occurs in various applications, so the research on gate oxide degradation has important theoretical significance for the reliability evaluation of electronic components. This paper proposes a power MOSFET gate oxide degradation parameter characterization technique based on the current fall time (tfi) during the turn-off process. Firstly, it introduces the failure mechanism and effects of gate oxide degradation of power MOSFET; secondly, analyzes the mechanism of gate oxide degradation based on the current drop time during turn-off; finally, an accelerated gate oxide degradation experiment was taken, and the results proved that the current fall time can effectively characterize the degradation state of the gate oxide layer of the power MOSFET, and verified the effectiveness of the proposed parameter characterization technique.
Two-photon microscopy in vivo reveals brain vessel type-specific loss of glycocalyx caused by apoM/S1P signaling impairment

Increases in adsorptive mediated transcytosis (AMT) at the blood-brain barrier (BBB) are linked to many brain disorders. In a healthy brain, AMT is suppressed by sphingosine-1-phosphate (S1P) receptor 1 (S1PR1) signaling. Low levels of S1P lead to a rise in AMT, but the mechanisms are incompletely understood. Here, we explored whether the rises in AMT are caused by the loss of the endothelial glycocalyx (gcx). We used two-photon microscopy in mice with low S1P plasma levels (Apom-/-) and developed a novel photobleaching approach to measure gcx in vivo at distinct classes of cerebral microvessels, i.e., arterioles, capillaries and venules. We show that S1P signaling impairment reduced gcx in arterioles but not in other vessel segments. The location of gcx loss corresponded to the vascular topology of AMT increases. The S1PR1 agonist SEW2871 restores low levels of AMT in Apom-/- mice but did not restore the gcx within the same time window. We propose that while the gcx loss may contribute to AMT increase, restoring gcx is not necessary for AMT to return to normal. These data establish a new imaging method to study gcx in the living mouse brain, demonstrate zonation of gcx in cerebral microvessels, and suggest differences in vascular susceptibility to gcx loss in disease states.
System for integration of tools for full content verification on multiple sensors

Cyberspace is the newest addition to the domains for warfare. As in the other domains both offensive and defensive operations are relevant. Defensive operations in cyberspace can draw on experience from traditional information security, but might use other procedures and use tools in a different way. This thesis shows how existing command line tools for packet captures can be used more effectively. The research provides a definition of a scalable effective system for packet capture for use in Computer Network Defense (CND) verification and analysis. A prototype of the system is presented and evaluated in terms of efficiency and effectiveness.
The Temporal Dynamics of Willed Attention in Vision

Most models of attention distinguish between voluntary and involuntary attention, the latter being driven in a bottom-up fashion by salient sensory signals. Studies of voluntary visual-spatial attention have used informational or instructional cues, such as arrows, to induce or instruct observers to direct selective attention to relevant locations in visual space in order to detect or discriminate subsequent target stimuli. In everyday vision, however, voluntary attention is influenced by a host of factors, most of which are quite different from the laboratory paradigms that utilize attention-directing cues. These factors include priming, experience, reward, meaning, motivations, and high-level behavioral goals. Attention that is endogenously directed in the absence of external cues has been referred to as self-initiated attention, or in our prior work as “willed attention”. Such studies typically replace attention-directing cues with a “prompt” that signals the subject when to choose where they will attend in preparation for the upcoming target stimulus. We used a novel paradigm that was designed to minimize external influences (i.e., cues or prompts) as to where, as well as when, spatial attention would be shifted and focused. Participants were asked to view bilateral dynamic dot motion displays, and to shift their covert spatial attention to either the left or right visual field patch at a time of their own choosing, thus allowing the participants to control both when and where they attended on each trial. The task was to discriminate and respond to a pattern in the attended dot motion patch. Our goal was to identify patterns of neural activity in the scalp-recorded EEG that revealed when and where attention was focused. Using machine learning methods to decode attention-related EEG alpha band activity, we were able to identify the onset of voluntary (willed) shifts of visual-spatial attention, and to determine where attention was focused. This work contributes to our understanding of the neural antecedents of voluntary attention, opening the door for improved models of attentional control, and providing steps toward development of brain-computer interfaces using non-invasive electrical recordings of brain activity.
Transient Oxygen Exposure Causes Profound and Lasting Changes to a Benzene-Degrading Methanogenic Community

We investigated the impact of oxygen on a strictly anaerobic, methanogenic benzene-degrading enrichment culture derived decades ago from oil-contaminated sediment. The culture includes a benzene fermenter from Deltaproteobacteria Candidate clade Sva0485 (referred to as ORM2) and methanogenic archaea. A relatively small one-time injection of air, simulating a small leak into a batch culture bottle, had no measurable impact on benzene degradation rates, although retrospectively, a tiny enrichment of aerobic taxa was detected. A subsequent 100 times larger injection of air stalled methanogenesis and caused drastic perturbation of the microbial community. A benzene-degrading Pseudomonas became highly enriched and consumed benzene and all available oxygen. Anaerobic benzene-degrading ORM2 cell numbers plummeted during this time; re-growth and associated recovery of methanogenic benzene degradation took almost one year. These results highlight the oxygen-sensitivity of this methanogenic culture and confirm that the mechanism for anaerobic biotransformation of benzene is independent of oxygen, fundamentally different from established aerobic pathways, and is carried out by distinct microbial communities. The study further highlights the importance of including microbial decay in characterizing and modelling and mixed microbial communities. SYNOPSIS Methanogenic benzene degradation in a highly enriched anaerobic consortium was inhibited for a year after transient exposure to oxygen, causing mass decay of benzene-fermenting bacteria. GRAPHIC FOR ABSTRACT ART
Hypervoxels: a multidimensional framework for the representation and analysis of neuroimaging data

Most neuroimaging modalities use regular grids of voxels to represent the three-dimensional space occupied by the brain. However, a regular 3D voxel grid does not reflect the anatomical and topological complexity represented by the brain’s white matter connections. In contrast, tractography reconstructions based on diffusion MRI provide a closer characterisation of the white matter pathways followed by the neuronal fibres interconnecting different brain regions. In this work, we introduce hypervoxels as a new methodological framework that combines the spatial encoding capabilities of multidimensional voxels with the anatomical and topological information found in tractography data. We provide a detailed description of the framework and evaluate the benefits of using hypervoxels by carrying out comparative voxel and hypervoxel cluster inference analyses on diffusion MRI data from a neuroimaging study on amyotrophic lateral sclerosis (ALS). Compared to the voxel analyses, the use of hypervoxels improved the detection of effects of interest in the data in terms of statistical significance levels and spatial distribution across white matter regions known to be affected in ALS. In these regions, the hypervoxel results also identified specific white matter pathways that resolve the anatomical ambiguity otherwise observed in the results from the voxel analyses. The observed increase in sensitivity and specificity can be explained by the superior ability of hypervoxel-based methods to represent and disentangle the anatomical overlap of white matter connections. Based on this premise, we expect that the use of hypervoxels should improve the analysis of neuroimaging data when the effects of interest under investigation are expected to be aligned along distinct but potentially overlapping white matter pathways.
Extended Brain Sources Estimation via Unrolled Optimization Neural Network

Electroencephalography (EEG)/Magnetoencephalography (MEG) source imaging aims to seek an estimation of underlying activated brain sources to explain the observed EEG/MEG recording. Due to the ill-posed nature of inverse problem, solving EEG/MEG Source Imaging (ESI) requires design of regularization or prior terms to guarantee a unique solution. Traditionally, the design of regularization terms is based on preliminary assumptions on the spatio-temporal structure in the source space. In this paper, we propose a novel paradigm to solve the ESI problem by using Unrolled Optimization Neural Network (UONN) (1) to improve the efficiency compared to traditional iterative algorithms; (2) to establish a data-driven way to model the source solution structure instead of using hand-crafted regularizations; (3) to learn the hyperparameter automatically in a data-driven manner. The proposed framework is based on unfolding of the iterative optimization algorithm with neural network modules. The proposed new learning framework is the first one that use the unrolled optimization neural network to solve the ESI problem. The newly designed framework can effectively learn the source extents pattern and achieved significantly improved performance compared to benchmark algorithms.
The synaptonemal complex controls cis- versus trans- 1 interference in coarsening-based meiotic crossover 2 patterning 3

12 13 The shuffling of genetic material facilitated by meiotic crossovers is a critical driver of genetic 14 variation. Therefore, the number and positions of crossover events must be carefully controlled. In 15 Arabidopsis, an obligate crossover and repression of nearby crossovers on each chromosome pair 16 are abolished in mutants that lack the synaptonemal complex (SC), a conserved protein scaffold. We 17 use mathematical modelling and quantitative super-resolution microscopy to explore and 18 mechanistically explain meiotic crossover pattering in Arabidopsis zyp1 mutants, that lack an SC. We 19 develop an SC mutant coarsening model in which crossover precursors globally compete for a 20 limited pool of the pro-crossover factor HEI10, with dynamic HEI10 exchange mediated through the 21 nucleoplasm. We demonstrate that this model is capable of quantitatively reproducing and 22 predicting experimental crossover patterning and HEI10 foci intensity data. Our results reveal that 23 regulation of the number of crossovers within a cell in SC mutants (“trans-interference”), and 24 inhibition of nearby crossovers on the same chromosome in wild-type cells (“cis-interference”), likely 25 act through the same underlying coarsening mechanism, differing only in the spatial compartment 26 through which the pro-crossover factor diffuses. The spatial compartment used is controlled by the 27 SC, which therefore acts as a critical regulator of cis- versus trans-interference. 28
Sensory conflict disrupts circadian rhythms in the sea anemone Nematostella vectensis

Circadian clocks allow organisms to optimize their phenotypes in relation to rhythmic environmental conditions. Clocks must synchronize, or entrain, to environmental signals called zeitgebers (such as light and temperature) while maintaining internal rhythms that are robust to environmental noise. We know surprisingly little about how clocks function in the presence of multiple zeitgebers, although these are the conditions that exist in nature. Misalignment between zeitgeber cycles (here, “sensory conflict”) can disrupt circadian rhythms in behavior and gene expression, but it is not clear whether this is generally true across animals. In order to understand general rules about animal clocks, and how clocks have evolved throughout Metazoa, it is necessary to study non-bilaterian animals such as cnidarians, which include corals, jellies, and sea anemones. The sea anemone Nematostella vectensis has emerged as the principal model system for cnidarian circadian biology. In this study, we show that temperature cycles entrain circadian locomotor rhythms in Nematostella, and then conduct extensive behavioral experiments across a range of light and temperature cycles to show that Nematostella’s circadian behavior is disrupted by sensory conflict. Chronic exposure to conflicting light and temperature cycles also causes substantial changes to the rhythmic transcriptome, including the breakdown of rhythmic expression of various metabolic processes. These results have important implications for our understanding of cnidarian circadian clocks at both the molecular and organismal levels, and for how sensory information is processed by clocks in the absence of a central nervous system.
Highly selective transgene expression through double-floxed inverted orientation system by using a unilateral spacer sequence

The double-floxed inverted orientation (DIO) system with adeno-associated viral (AAV) vector provides a beneficial approach to express transgenes in specific cell populations having Cre recombinase. A significant issue with this system is the protection against non-specific expression of transgenes in tissues after vector injection. We here show that Cre-independent recombination in AAV genome carrying the DIO sequence occurs during the production of viral vectors in packaging cells, which results in transgene expression in off-target populations. Introduction of a relatively longer nucleotide sequence between two recognition sites at the unilateral side of the transgene cassette, termed a unilateral spacer sequence (USS), is useful to suppress recombination during the vector production, leading to the protection of non-specific transgene expression with enhanced gene expression selectivity. Our DIO/USS system offers a powerful strategy for highly specific Cre-dependent transgene expression, aiming at various applications for structural and functional analyses of target cell populations.
Evidence for shared resources in visuospatial attention: Endogenous attention misleads the decoding of exogenous attention in alpha rhythms

Prevailing accounts of visuospatial attention differentiate exogenous orienting, which 1 corresponds to involuntary shifts of attention, from endogenous orienting, which reflects 2 the voluntary control of attention. While these different forms of attention are functionally 3 separable, evidence shows that they can nevertheless interact with each other. These 4 dynamics have been at the center of ongoing debates for more than two decades. One 5 hypothesis regarding these interactions is that, while both forms of attention orienting map 6 onto independent functional systems, they are capable of mutual interference. This 7 viewpoint implies that exogenous attention, a ballistic and stimulus-driven process, is not 8 impervious to the influence of endogenous attention. Evidence in support of this view 9 remains sparse and the mechanisms that underlie these interactions remain largely 10 unknown. The present study tackles these questions by examining whether endogenous 11 attention influences the neural processes of exogenous attention using multivariate 12 pattern classification to electroencephalography (EEG). We contrasted the effects of 13 exogenous attention across two experimental conditions: Single cueing where exogenous 14 attention is engaged alone, and double cueing where exogenous attention is concurrently 15 engaged with endogenous attention. Our results show that the simultaneous engagement 16 of endogenous attention alters the emergence of exogenous attention across cue-related 17 and target-related neural processes. Exogenous attention is therefore not impervious to 18 the influence of endogenous attention. More importantly, we observed that classifiers 19 trained to decode exogenous attention from the power and phase of alpha band activity 20 during single cueing condition were systematically misled by endogenous attention when 21 tested in the context of double cueing. Hence, both the power and phase of alpha rhythms 22 are central to exogenous and endogenous attention. These findings not only highlight 23 overlapping neural processes between both form of attention orienting, but further 24 demonstrate that the dynamics of exogenous and endogenous attention are 25 characterized by limited processing resources. examines the relationship between top-down and bottom-up attention. Using electroencephalography (EEG) and multivariate pattern classification techniques, the researchers show that top-down attention modified the brain activity of bottom-up attention. Moreover, machine learning classifiers trained to decode bottom-up attention based on alpha band activity (8-12 Hz), a well-known marker of visuospatial attention, are systematically misled by top-down attention. The researchers conclude that both forms of visuospatial orienting are supported by several overlapping which implies shared resources between them. these
A deep learning-based automated closed-loop optogenetic system for neuromodulation during seizures

Closed-loop electrical brain stimulation is becoming a popular technique proposed for use as a treatment alternative to surgical resection of brain tissue for drug-resistant seizures in epilepsy patients. Closed-loop optogenetic stimulation is an experimental alternative to electrical stimulation since it can stimulate or inhibit neurons. The closed-loop part contains an online seizure detection algorithm, which, based on the design, can detect the onset of a seizure or evaluate a running window for seizure membership. Conventional configurations of closed-loop optogenetics have several limitations, ranging from the adaptability of hardware-based implementation to inadequate, customized feature selection of seizures, among others. Here we provide a detailed description of our closed-loop components. We used a sequential, fully convolutional neural network regressor for complex feature selection of seizures against the controls from local field potential recordings. Our modular design kept the local field potential-recording headset and optical probe separate. The seizure detection and execution of light delivery are fast and can be precisely timed. This automated system is robust to noise, modular in design, flexible in use, and simple execution. When applied in vivo, the proposed work shows efficacy over the state of the arts in terms of improved seizure detection and reduction in false positives.
An Inhibitory Function of TRPA1 Channels in TGF-β1-driven Fibroblast to Myofibroblast Differentiation

Transient receptor potential ankyrin 1 (TRPA1) is a non-selective Ca2+ permeable cation channel, which was originally cloned from human lung fibroblasts (HLFs). TRPA1-mediated Ca2+ entry is evoked by exposure to several chemicals, including allyl isothiocyanate (AITC), and a protective effect of TRPA1 activation in the development of cardiac fibrosis has been proposed. Yet, the function of TRPA1 in transforming growth factor β1 (TGF-β1)-driven fibroblast to myofibroblast differentiation and the development of pulmonary fibrosis remains elusive. TRPA1 expression and function was analyzed in cultured primary HLFs, and mRNA levels were significantly reduced after adding TGF-β1. Expression of genes encoding fibrosis markers, e.g. alpha smooth muscle actin (ACTA2), plasminogen activator inhibitor 1 (SERPINE1), fibronectin (FN1) and type I collagen (COL1A1) was increased after siRNA-mediated down-regulation of TRPA1-mRNA in HLFs. Moreover, AITC-induced Ca2+ entry in HLFs was decreased after TGF-β1 treatment and by application of TRPA1 siRNAs, while AITC treatment alone did not reduce cell viability or enhanced apoptosis. Cell barrier function increased after addition of TRPA1 siRNAs or TGF-β1 treatment. Most interestingly, AITC-induced TRPA1 activation augmented ERK1/2 phosphorylation, which might inhibit TGF-β-receptor signaling. Our results suggest an inhibitory function of TRPA1 channels in TGF-β1-driven fibroblast to myofibroblast differentiation. Therefore, activation of TRPA1 channels might be protective during the development of pulmonary fibrosis in patients.
A flexible method for estimating tip diversification rates across a range of speciation and extinction scenarios

Estimates of diversification rates at the tips of a phylogeny provide a flexible approach for correlation analyses with multiple traits and to map diversification rates in space, while also avoiding the uncertainty of deep time rate reconstructions. Available methods for tip rate estimation make different assumptions, and thus their accuracy usually depends on characteristics of the underlying model generating the tree. Here we introduce MiSSE, a trait-free, state-dependent speciation and extinction approach that can be used to estimate varying speciation, extinction, net-diversification, turnover rates, and extinction fraction at the tips of the tree. We compare the accuracy of tip rates inferred by MiSSE against similar methods and demonstrate that, due to certain characteristics of the model, the error is generally low across a broad range of speciation and extinction scenarios. MiSSE can be used alongside regular phylogenetic comparative methods in trait related diversification hypotheses, and we also describe a simple correction to avoid pseudoreplication from sister tips in analyses of independent contrasts. Finally, we demonstrate the capabilities of MiSSE, with a renewed focus on classic comparative methods, to examine correlation between plant height and turnover rates in eucalypts, a species-rich lineage of flowering plants.