Miracle-dz/UniFAR-FTUs huggingface dataset:
Regularized partial correlation provides reliable functional connectivity estimates while correcting for widespread confounding

Functional connectivity (FC) has been invaluable for understanding the brain’s communication network, with strong potential for enhanced FC approaches to yield additional insights. Unlike with the fMRI field-standard method of pairwise correlation, theory suggests that partial correlation can estimate FC without confounded and indirect connections. However, partial correlation FC can also display low repeat reliability, impairing the accuracy of individual estimates. We hypothesized that reliability would be increased by adding regularization, which can reduce overfitting to noise in regression-based approaches like partial correlation. We therefore tested several regularized alternatives – graphical lasso, graphical ridge, and principal component regression – against unregularized partial and pairwise correlation, applying them to empirical resting-state fMRI and simulated data. As hypothesized, regularization vastly improved reliability, quantified using between-session similarity and intraclass correlation. This enhanced reliability then granted substantially more accurate individual FC estimates when validated against structural connectivity (empirical data) and ground truth networks (simulations). Graphical lasso showed especially high accuracy among regularized approaches, seemingly by maintaining more valid underlying network structures. We additionally found graphical lasso to be robust to noise levels, data quantity, and subject motion – common fMRI error sources. Lastly, we demonstrated that resting-state graphical lasso FC can effectively predict fMRI task activations and individual differences in behavior, further establishing its reliability, external validity, and ability to characterize task-related functionality. We recommend graphical lasso or similar regularized methods for calculating FC, as they can yield more valid estimates of unconfounded connectivity than field-standard pairwise correlation, while overcoming the poor reliability of unregularized partial correlation.
Escherichia coli self-organizes developmental rosettes

Rosettes are self-organizing, circular multicellular communities that initiate developmental processes, like organogenesis and embryogenesis, in complex organisms. Their formation results from the active repositioning of adhered sister cells and is thought to distinguish multicellular organisms form unicellular ones. Though common in eukaryotes, this multicellular behavior has not been reported in bacteria. In this study, we discovered that Escherichia coli forms rosettes by active sister cell repositioning. After division, sister cells “fold” to actively align at the 2- and 4-cell stages of clonal division, thereby producing rosettes with characteristic quatrefoil configuration. Analysis revealed folding follows an angular random walk, comprised of ∼1-µm strokes and directional randomization. We further showed that this motion was produced by the flagellum, the extracellular tail whose rotation generates swimming motility. Rosette formation was found to require de novo flagella synthesis suggesting it must balance the opposing forces of Ag43 adhesion and flagellar propulsion. We went on to show that proper rosette formation was developmentally required for subsequent morphogenesis of multicellular chains, rpoS expression, and formation of hydrostatic clonal-chain biofilms. Moreover, we discovered self-folding rosette-like communities in the standard motility assay, indicating this behavior may be general to hydrostatic environments. This study establishes that self-organization of developmental rosettes is a cross-kingdom multicellular behavior. Our findings indicate the potential of targeting bacterial rosettes to interrupt biofilms or reduce their antibiotic tolerance.
RIDGE, a tool tailored to detect gene flow barriers across species pairs

Characterizing the processes underlying reproductive isolation between diverging lineages is central to understanding speciation. Here, we present RIDGE – Reproductive Isolation Detection using Genomic polymorphisms – a tool tailored for quantifying gene flow barrier proportions and identifying the corresponding genomic regions. RIDGE relies on an Approximate Bayesian Computation with a model-averaging approach to accommodate diverse scenarios of lineage divergence. It captures heterogeneity in effective migration rate along the genome while accounting for variation in linked selection and recombination. The barrier detection test relies on numerous summary statistics to compute a Bayes factor, offering a robust statistical framework that facilitates cross-species comparisons. Simulations revealed that RIDGE is particularly efficient both at capturing signals of ongoing migration and at identifying barrier loci, including for recent divergence times (~0.1 2Ne generations). Applying RIDGE to four published crow datasets, we validated our tool by identifying a well-known large genomic region associated with mate choice patterns. We identified additional barrier loci between species pairs, which have shown, on the one hand, that depending on the biological, demographic, and selection contexts, different combinations of summary statistics are informative for the detection of signals. On the other hand, these analyses also highlight the value of our newly developed outlier statistics in challenging detection conditions.
Structure of the portal complex from Staphylococcus aureus pathogenicity island 1 transducing particles in situ and in solution

Staphylococcus aureus is an important human pathogen, and the prevalence of antibiotic resistance is a major public health concern. The evolution of pathogenicity and resistance in S. aureus often involves acquisition of mobile genetic elements (MGEs). Bacteriophages play an especially important role, since transduction represents the main mechanism for horizontal gene transfer. S. aureus pathogenicity islands (SaPIs), including SaPI1, are MGEs that carry genes encoding virulence factors, and are mobilized at high frequency through interactions with specific “helper” bacteriophages, such as 80α, leading to packaging of the SaPI genomes into virions made from structural proteins supplied by the helper. Among these structural proteins is the portal protein, which forms a ring-like portal at a fivefold vertex of the capsid, through which the DNA is packaged during virion assembly and ejected upon infection of the host. We have used high- resolution cryo-electron microscopy to determine structures of the S. aureus bacteriophage 80α portal in solution and in situ in the empty and full SaPI1 virions, and show how the portal interacts with the capsid. These structures provide a basis for understanding portal and capsid assembly and the conformational changes that occur upon DNA packaging and ejection.
Towards a nomenclatural clarification of the Peltigera ponojensis/monticola clade including metagenomic sequencing of type material and the introduction of P. globulata Miadl. & Magain sp. nov.

Abstract Peltigera globulata Miadl. & Magain, a new species in the P. ponojensis/monticola species complex of section Peltigera, is formally described. This clade was previously given the interim designation Peltigera sp. 17. It is found in sun-exposed and xeric habitats at high altitudes in Peru and Ecuador. Peltigera globulata can be easily recognized by its irregularly globulated margins covered mostly by thick, white pruina, somewhat resembling the sorediate thallus margins of P. soredians, another South American species from section Peltigera. The hypervariable region of ITS1 (ITS1-HR), which is in general highly variable among species of section Peltigera, does not have diagnostic value for species identification within the P. ponojensis/monticola complex. Nevertheless, no significant level of gene flow was detected among eight lineages representing a clade of putative species (including P. globulata) within this complex. ITS sequences from the holotype specimens of P. monticola Vitik. (collected in 1979) and P. soredians Vitik. (collected in 1981) and lectotype specimens of P. antarctica C. W. Dodge (collected in 1941) and P. aubertii C. W. Dodge (collected in 1952) were successfully obtained through Sanger and Illumina metagenomic sequencing. BLAST results of these sequences revealed that the type specimen of P. monticola falls within the P. monticola/ponojensis 7 clade, which represents P. monticola s. str. , and confirmed that the type specimen of P. aubertii falls within a clade identified previously as P. aubertii based on morphology. The ITS sequence from the type specimen of P. soredians, which superficially resembles P. globulata, confirms its placement in the P. rufescens clade. Finally, we discovered that the name P. antarctica was erroneously applied to a lineage in the P. ponojensis/monticola clade. The ITS sequence from the type specimen of P. antarctica represents a lineage within the P. rufescens clade, which is sister to the P. ponojensis/monticola clade.
Benchmarking atomic data for astrophysics: Fe xiii EUV lines

Recent atomic data for Fe xiii are benchmarked against high-resolution spectroscopic observations of the solar corona. All the identifications of the EUV lines are reviewed by also taking into account laboratory measurements. A few new identifications are proposed, and many wavelengths are revised. All the strongest EUV lines are now identified. Very good agreement between predicted and observed line intensities is generally found using the latest atomic calculations. We clearly indicate which EUV lines are blended, and which are best for electron-density measurements in different regimes.
UvA-DARE (Digital Academic Putting things in perspective. Young people’s susceptibility to the effects of sexual media content

Previous research has suggested that adolescents’ social network site use is related to their sexual self-concept, but systematic empirical research on the issue is lacking. The present study investigated the relationships between self-and other-generated sexy self-presentations (i.e., posting sexy pictures of themselves or looking at sexy pictures of others) on social network sites (SNSs) and a relevant aspect of adolescents’ sexual self-concept (i.e., the importance of being sexually outgoing) over time. Results from a representative two-wave panel study among 1,586 Dutch adolescents (aged 13-17) showed that both self- and other-generated sexy self-presentations influenced adolescents’ sexual self-concept directly. In addition, looking at others’ sexy self-presentations also had an indirect influence on sexual self-concept through increased favorability of prototypes of sexual others. Moreover, adolescents’ sexual self-concept predicted their exposure to sexy self-presentations of others, as well as their own sexy self-presentation over time. These results did not differ for boys and girls.
Probiotic bacteria alleviate chlorpyrifos‐induced rat testicular and renal toxicity: A possible mechanism based on antioxidant and anti‐inflammatory activity

Chlorpyrifos (CPF) has caused many potential toxicities in nontarget organisms. Fewer studies have been conducted on the effects of lactic acid bacteria (LAB) in mitigating tissue damage induced by CPF in vivo. Therefore, we investigated CPF renal and testicular toxicity and the alleviating effect of probiotic lactobacilli, based on antioxidant and anti‐inflammatory activity, on induced toxicity in an animal model. Biochemical assays showed that CPF induced oxidative stress along with a change in superoxide dismutase (SOD) and catalase (CAT) activity in a tissue‐dependent manner. After treatment with CPF, testicular and renal levels of TNF‐α were significantly reduced and enhanced, respectively, compared to the control group. The probiotic treatment restored renal and testicular TNF‐α levels and modulated and blocked the increasing effect of CPF on renal IL‐1β levels. Testicular IL‐1β levels in the probiotic‐treated and CPF groups demonstrated similar values. Exposure to CPF significantly induced renal histopathological damage that, of course, was completely inhibited by treatment with Lactobacillus casei and the LAB mixture. In summary, CPF showed significant toxicological effects on oxidative stress and the inflammation rate in CPF‐exposed rats. Therefore, supplementation with probiotic bacteria may alleviate CPF renal toxicity and mitigate its oxidative stress and inflammation effects.
The inducible secreting TLR5 agonist, CBLB502, enhances the anti-tumor activity of CAR133-NK92 cells in colorectal cancer

Objective: CAR-T/NK cells have had limited success in the treatment of solid tumors, such as colorectal cancer (CRC), in part because of the heterogeneous nature of tumor-associated antigens that lead to antigen-negative relapse after the initial response. This barrier might be overcome by enhancing the recruitment and durability of endogenous immune cells. Methods: Immunohistochemistry and flow cytometry were used to assess the expression of CD133 antigen in tissue microarrays and cell lines, respectively. Retroviral vector transduction was used to generate CBLB502-secreting CAR133-NK92 cells (CAR133-i502-NK92). The tumor killing capacity of CAR133-NK92 cells in vitro and in vivo were quantified via LDH release, the RTCA assay, and the degranulation test, as well as measuring tumor bioluminescence signal intensity in mice xenografts. Results: We engineered CAR133-i502-NK92 cells and demonstrated that those cells displayed enhanced proliferation (9.0 × 104 cells vs. 7.0 × 104 cells) and specific anti-tumor activities in vitro and in a xenogeneic mouse model, and were well-tolerated. Notably, CBLB502 secreted by CAR133-i502-NK92 cells effectively activated endogenous immune cells. Furthermore, in hCD133+/hCD133− mixed cancer xenograft models, CAR133-i502-NK92 cells suppressed cancer growth better than the counterparts (n = 5, P = 0.0297). Greater T-cell infiltration was associated with greater anti-tumor potency (P < 0.0001). Conclusions: Armed with a CBLB502 TLR5 agonist, CAR133-NK92 cells were shown to be capable of specifically eliminating CD133-positive colon cancer cells in a CAR133-dependent manner and indirectly eradicating CD133-negative colon cancer cells in a CBLB502-specific endogenous immune response manner. This study describes a novel technique for optimizing CAR-T/NK cells for the treatment of antigenically-diverse solid tumors.
Generalisable Agents for Neural Network Optimisation

Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long training times. To address this difficulty, we propose the framework of Generalisable Agents for Neural Network Optimisation (GANNO) -- a multi-agent reinforcement learning (MARL) approach that learns to improve neural network optimisation by dynamically and responsively scheduling hyperparameters during training. GANNO utilises an agent per layer that observes localised network dynamics and accordingly takes actions to adjust these dynamics at a layerwise level to collectively improve global performance. In this paper, we use GANNO to control the layerwise learning rate and show that the framework can yield useful and responsive schedules that are competitive with handcrafted heuristics. Furthermore, GANNO is shown to perform robustly across a wide variety of unseen initial conditions, and can successfully generalise to harder problems than it was trained on. Our work presents an overview of the opportunities that this paradigm offers for training neural networks, along with key challenges that remain to be overcome.
Estimation of Model Bias by the Assimilation of Satellite Ocean Chlorophyll Data into a Global Model

Chlorophyll concentration estimates by ocean-biogeochemical models showtypically significant errors. Data assimilation algorithms based onthe Kalman filter can be applied to improve the model state. However,these algorithms do usually not account for possible biases in themodel prediction. Taking model bias explicitly into account canimprove the assimilation estimates.Here, the effect of bias estimation is studied with the assimilationof chlorophyll data from the Sea-viewing Wide Field-of-view Sensor(SeaWiFS) into the NASA Ocean Biogeochemical Model (NOBM). Theensemble-based SEIK filter has been combined with an online biascorrection scheme. A static error covariance matrix is used for simplicity. The performance of the filter algorithm is assessed by comparisonwith independent in situ data over the 7-year period 1998--2004.Compared to the assimilation without bias estimation, the biascorrection results in significant improvements of the surfacechlorophyll. With bias estimation, the daily surface chlorophyllestimates from the assimilation show about 3.3\% lower error thanSeaWiFS data. In contrast, the error in the global surfacechlorophyll estimate without bias estimation is 10.9\%. Next to theimprovement of the estimated chlorophyll concentrations, the estimatedbiases indicate regions with systemic errors in the model-represenedchlorophyll.
Coastal management: Mapping of littoral cells

As a guide for coastal managers, a study has been carried out identifying the major regional littoral drift cells in England and Wales. For coastal defence management the regional cells have been further subdivided into sub-cells which are either independent or only weakly dependent upon each other. The coastal regime within each cell has been described and this together with the maps of the coastline identify the special characteristics of each area.
Silent Speech Recognition with Articulator Positions Estimated from Tongue Ultrasound and Lip Video

We present a multi-speaker silent speech recognition system trained on articulator features derived from the Tongue and Lips corpus, a multi-speaker corpus of ultrasound tongue imaging and lip video data. We extracted articulator features using the pose estimation software DeepLabCut , then trained recognition models with these point-tracking features using Kaldi . We trained with voiced utterances, then tested performance on both voiced and silent utterances. Our multi-speaker SSR improved WER by 23.06% when compared to a previous similar multi-speaker SSR system which used image-based instead of point-tracking features. We also found great improvements (up to 15.45% decrease in WER) in recognition of silent speech using fMLLR adaptation compared to raw features. Finally, we investigated differences in articulator trajectories between voiced and silent speech and found that speakers tend to miss articulatory targets that are present in voiced speech when speaking silently.
A new adaptive receiver-initiated scheme for mitigating starvation in wireless networks

Please cite this article in press as: A. Leonardi works, Ad Hoc Netw. (2011), doi:10.1016/j.ad Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) has been adopted by the IEEE 802.11 standard and provides good performance when all transmitters are within the range of each other. Unfortunately, in multi-hop topologies, the asymmetric view of the channel state leads to a throughput distribution where a few flows may capture all the available bandwidth while many other flows get very low throughput and sometime meet starvation. To address this problem, in this paper we describe a solution called Carrier Sense Multiple Access with Collision Avoidance by Receiver Detection (CSMA/CARD) which makes use of collisions sensed by a receiver at the physical layer to help the handshake mechanism and mitigate the effect of such problem. More specifically, we propose a mechanism based on historical observations, where collisions can be used by the receiver to predict whether some sender attempted to initiate a transmission. The receiver then reacts accordingly by participating itself in a handshake sequence. We show some interesting results, obtained through analysis and simulations, when the CSMA/CARD is compared to the IEEE 802.11 protocol. 2011 Elsevier B.V. All rights reserved.
The State of the Art in End-User Software Engineering

ANDREW J. KO The Information School, DUB Institute, University of Washington ROBIN ABRAHAM Microsoft Corporation LAURA BECKWITH Unaffiliated ALAN BLACKWELL The Computer Laboratory, University of Cambridge MARGARET BURNETT, MARTIN ERWIG, AND CHRIS SCAFFIDI School of Electrical and Engineering and Computer Science, Oregon State University JOSEPH LAWRANCE MIT CSAIL HENRY LIEBERMAN MIT Media Laboratory BRAD MYERS Human-Computer Interaction Institute, Carnegie Mellon University MARY BETH ROSSON Information Sciences and Technology, Penn State University GREGG ROTHERMEL Department of Computer Science and Engineering, University of Nebraska at Lincoln MARY SHAW Institute for Software Research, Carnegie Mellon University SUSAN WIEDENBECK College of Information Science and Technology, Drexel University
Propagation, Detection and Containment of Mobile Malware

Today's enterprise systems and networks are frequent targets of malicious attacks, such as worms, viruses, spyware and intrusions that can disrupt, or even disable critical services. Recent trends suggest that by combining spyware as a malicious payload with worms as a delivery mechanism, malicious programs can potentially be used for industrial espionage and identity theft. The problem is compounded further by the increasing convergence of wired, wireless and cellular networks, since virus writers can now write malware that can crossover from one network segment to another, exploiting services and vulnerabilities specific to each network. This dissertation makes four primary contributions. First, it builds more accurate malware propagation models for emerging hybrid malware (i.e., malware that use multiple propagation vectors such as Bluetooth, Email, Peer-to-Peer, Instant Messaging, etc.), addressing key propagation factors such as heterogeneity of nodes, services and user mobility within the network. Second, it develops a proactive containment framework based on group-behavior of hosts against such malicious agents in an enterprise setting. The majority of today's anti-virus solutions are reactive, i.e., these are activated only after a malicious activity has been detected at a node in the network. In contrast, proactive containment has the potential of closing the vulnerable services ahead of infection, and thereby halting the spread of the malware. Third, we study (1) the current-generation mobile viruses and worms that target SMS/MMS messaging and Bluetooth on handsets, and the corresponding exploits, and (2) their potential impact in a large SMS provider network using real-life SMS network data. Finally, we propose a new behavioral approach for detecting emerging malware targeting mobile handsets. Our approach is based on the concept of generalized behavioral patterns instead of traditional signature-based detection. The signature-based methods are not scalable for deployment in mobile devices due to limited resources available on today's typical handsets. Further, we demonstrate that the behavioral approach not only has a compact footprint, but also can detect new classes of malware that combine some features from existing classes of malware.