Miracle-dz/UniFAR-FTUs huggingface dataset:
Want to bring a community together? Create more sub-communities

Understanding overlapping community structures is crucial for network analysis and prediction. AGM (Affiliation Graph Model) is one of the favorite models for explaining the densely overlapped community structures. In this paper, we thoroughly re-investigate the assumptions made by the AGM model on real datasets. We find that the AGM model is not sufficient to explain several empirical behaviors observed in popular real-world networks. To our surprise, all our experimental results can be explained by a parameter-free hypothesis, leading to more straightforward modeling than AGM which has many parameters. Based on these findings, we propose a parameter-free Jaccard-based Affiliation Graph (JAG) model which models the probability of edge as a network specific constant times the Jaccard similarity between community sets associated with the individuals. Our modeling is significantly simpler than AGM, and it eliminates the need of associating a parameter, the probability value, with each community. Furthermore, JAG model naturally explains why (and in fact when) overlapping communities are densely connected. Based on these observations, we propose a new community-driven friendship formation process, which mathematically recovers the JAG model. JAG is the first model that points towards a direct causal relationship between tight connections in the given community with the number of overlapping communities inside it. Thus, \emph{the most effective way to bring a community together is to form more sub-communities within it. } The community detection algorithm based on our modeling demonstrates a significantly simple algorithm with state-of-the-art accuracy on six real-world network datasets compared to the existing link analysis based methods.
A Theoretical and Experimental Account of n-Tuple Classifier Performance

The n-tuple recognition method is briefly reviewed, summarizing the main theoretical results. Large-scale experiments carried out on Stat-Log project datasets confirm this method as a viable competitor to more popular methods due to its speed, simplicity, and accuracy on the majority of a wide variety of classification problems. A further investigation into the failure of the method on certain datasets finds the problem to be largely due to a mismatch between the scales which describe generalization and data sparseness.
Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes

Real-time moving object detection in unconstrained scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. In this paper, an optical flow based moving object detection framework is proposed to address this problem. We utilize homography matrixes to online construct a background model in the form of optical flow. When judging out moving foregrounds from scenes, a dual-mode judge mechanism is designed to heighten the system's adaptation to challenging situations. In experiment part, two evaluation metrics are redefined for more properly reflecting the performance of methods. We quantitatively and qualitatively validate the effectiveness and feasibility of our method with videos in various scene conditions. The experimental results show that our method adapts itself to different situations and outperforms the state-of-the-art methods, indicating the advantages of optical flow based methods.
Macroscopic Portal Vein Thrombosis in HCC Patients

Macroscopic portal vein invasion (PVT) by hepatocellular carcinoma (HCC) in the liver is one of the most important negative prognostic factors for HCC patients. The characteristics of a large cohort of such patients were examined. We found that the percent of patients with PVT significantly increased with increasing maximum tumor diameter (MTD), from 13.7% with tumors of MTD <5cm to 56.4% with tumors of MTD >10cm. There were similar numbers of HCC patients with very large tumors with and without PVT. Thus, MTD alone was insufficient to explain the presence of PVT, as were high AFP levels, since less than 50% of high AFP patients had PVT. However, the percent of patients with PVT was also found to significantly increase with increasing blood alpha-fetoprotein (AFP) levels and tumor multifocality. A logistic regression model that included these 3 factors together showed an odds ratio of 17.9 for the combination of MTD>5.0cm plus tumor multifocality plus elevated AFP, compared to low levels of these 3 parameters. The presence or absence of macroscopic PVT may therefore represent different HCC aggressiveness phenotypes, as judged by a significant increase in tumor multifocality and AFP levels in the PVT positive patients. Factors in addition to MTD and AFP must also contribute to PVT development.
The Scope of Planning Serial Actions during Typing

Human activities consisting of multiple component actions require the generation of ordered sequences. This study investigated the scope of response planning in highly serial task, typing, by means of ERPs indexing motor response preparation. Specifically, we compared motor-related ERPs yielded by words typed using a single hand against words that had all keystrokes typed with a single hand, except for a deviant one, typed with the opposite hand. The deviant keystroke occurred either early in the typed sequence, corresponding to the second or third letters, or late, corresponding to the penultimate or last letter. Motor-related ERPs detected before response onset were affected only by deviant keystrokes located at the beginning of the sequence, whereas deviant keystrokes located at the end yielded ERPs that were undistinguishable from unimanual responses. These results impose some constraints on the notion of parallel processing of component actions.
Vitamin K Deficiency Induced by Warfarin Is Associated With Cognitive and Behavioral Perturbations, and Alterations in Brain Sphingolipids in Rats

Initially discovered for its role in blood coagulation, there is now convincing evidence that vitamin K (VK) has important actions in the nervous system. In brain, VK is present in the form of menaquinone-4 (MK-4), a byproduct of the main dietary source, phylloquinone. It contributes to the biological activation of various proteins (i.e., Gas6), and participates in the synthesis of sphingolipids, a class of lipids widely present in brain cell membranes with important cell signaling functions. In a previous study, we reported that lifetime consumption of a low VK diet resulted in mild cognitive impairment in aged rats, a finding associated with an alteration of the sphingolipid profile. To confirm the role of VK as it relates to sphingolipids, cognition, and behavior outside the context of aging, we conducted a study of acute VK deficiency using a pharmacological model of VK deficiency in brain. In this procedure, rats (8 weeks) are maintained on a ratio of warfarin (a VK antagonist) to VK whereby coagulation is maintained while inducing VK deficiency in extrahepatic tissues. After 10 weeks of treatment, rats who were subjected to the warfarin plus phylloquinone protocol (WVK) exhibited longer latencies in the Morris water maze test as well as lower locomotor activity and exploratory behavior in the open field test, when compared to control rats. The WVK treatment resulted in a dramatic decrease in MK-4 level in all brain regions despite the presence of high local concentrations of phylloquinone, which suggests an inhibition of the biosynthetic MK-4 pathway in the presence of warfarin. Additionally, WVK treatment affected sphingolipid concentrations in key brain regions, notably those of the ganglioside family. Finally, brain MK-4 was correlated with performances in the open field test. This study confirms the modulatory role of VK in cognition and behavior and the implication of sphingolipids, notably those of the ganglioside family.
Neurorobotics—A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots

Neurorobots are robots whose control has been modeled after some aspect of the brain. Since the brain is so closely coupled to the body and situated in the environment, Neurorobots can be a powerful tool for studying neural function in a holistic fashion. It may also be a means to develop autonomous systems that have some level of biological intelligence. The present article provides my perspective on this field, points out some of the landmark events, and discusses its future potential.
Bayesian validation of grammar productions for the language of thought

Probabilistic proposals of Language of Thoughts (LoTs) can explain learning across different domains as statistical inference over a compositionally structured hypothesis space. While frameworks may differ on how a LoT may be implemented computationally, they all share the property that they are built from a set of atomic symbols and rules by which these symbols can be combined. In this work we propose an extra validation step for the set of atomic productions defined by the experimenter. It starts by expanding the defined LoT grammar for the cognitive domain with a broader set of arbitrary productions and then uses Bayesian inference to prune the productions from the experimental data. The result allows the researcher to validate that the resulting grammar still matches the intuitive grammar chosen for the domain. We then test this method in the language of geometry, a specific LoT model for geometrical sequence learning. Finally, despite the fact of the geometrical LoT not being a universal (i.e. Turing-complete) language, we show an empirical relation between a sequence’s probability and its complexity consistent with the theoretical relationship for universal languages described by Levin’s Coding Theorem.
Biomarkers for Predicting Malignant Pleural Mesothelioma in a Mexican Population

Background: Diagnosis of malignant pleural mesothelioma (MPM) remains a challenge, especially when resources in pathology are limited. The study aimed to evaluate cost-effective tumor markers to predict the probability of MPM in plasma samples in order to accelerate the diagnostic workup of the tissue of potential cases. Methods: We conducted a case-control study stratified by gender, which included 75 incident cases with MPM from three Mexican hospitals and 240 controls frequency-matched by age and year of blood drawing. Plasma samples were obtained to determine mesothelin, calretinin, and thrombomodulin using enzyme-linked immunosorbent assays (ELISAs). We estimated the performance of the markers based on the area under the curve (AUC) and predicted the probability of an MPM diagnosis of a potential case based on the marker concentrations. Results: Mesothelin and calretinin, but not thrombomodulin were significant predictors of a diagnosis of MPM with AUCs of 0.90 (95% CI: 0.85-0.95), 0.88 (95% CI: 0.82-0.94), and 0.51 (95% CI: 0.41-0.61) in males, respectively. For MPM diagnosis in men we estimated a true positive rate of 0.79 and a false positive rate of 0.11 for mesothelin. The corresponding figures for calretinin were 0.81 and 0.18, and for both markers combined 0.84 and 0.11, respectively. Conclusions: We developed prediction models based on plasma concentrations of mesothelin and calretinin to estimate the probability of an MPM diagnosis. Both markers showed a good performance and could be used to accelerate the diagnostic workup of tissue samples in Mexico.
ASSURED: Architecture for Secure Software Update of Realistic Embedded Devices

Secure firmware update is an important stage in the Internet of Things (IoT) device life-cycle. Prior techniques, designed for other computational settings, are not readily suitable for IoT devices, since they do not consider idiosyncrasies of a realistic large-scale IoT deployment. This motivates our design of architecture for secure software update of realistic embedded devices (ASSURED), a secure and scalable update framework for IoT. ASSURED includes all stakeholders in a typical IoT update ecosystem, while providing end-to-end security between manufacturers and devices. To demonstrate its feasibility and practicality, ASSURED is instantiated and experimentally evaluated on two commodity hardware platforms. Results show that ASSURED is considerably faster than current update mechanisms in realistic settings.
Information-Based Medicine in Glioma Patients: A Clinical Perspective

Glioma constitutes the most common type of primary brain tumor with a dismal survival, often measured in terms of months or years. The thin line between treatment effectiveness and patient harm underpins the importance of tailoring clinical management to the individual patient. Randomized trials have laid the foundation for many neuro-oncological guidelines. Despite this, their findings focus on group-level estimates. Given our current tools, we are limited in our ability to guide patients on what therapy is best for them as individuals, or even how long they should expect to survive. Machine learning, however, promises to provide the analytical support for personalizing treatment decisions, and deep learning allows clinicians to unlock insight from the vast amount of unstructured data that is collected on glioma patients. Although these novel techniques have achieved astonishing results across a variety of clinical applications, significant hurdles remain associated with the implementation of them in clinical practice. Future challenges include the assembly of well-curated cross-institutional datasets, improvement of the interpretability of machine learning models, and balancing novel evidence-based decision-making with the associated liability of automated inference. Although artificial intelligence already exceeds clinical expertise in a variety of applications, clinicians remain responsible for interpreting the implications of, and acting upon, each prediction.
Glyco-Engineered Anti-Human Programmed Death-Ligand 1 Antibody Mediates Stronger CD8 T Cell Activation Than Its Normal Glycosylated and Non-Glycosylated Counterparts

The programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis plays a central role in suppression of anti-tumor immunity. Blocking the axis by targeting PD-L1 with monoclonal antibodies is an effective and already clinically approved approach to treat cancer patients. Glyco-engineering technology can be used to optimize different properties of monoclonal antibodies, for example, binding to FcγRs. We generated two glycosylation variants of the same anti-PD-L1 antibody: one bearing core fucosylated N-glycans in its Fc part (92%) and its de-fucosylated counterpart (4%). The two glycosylation variants were compared to a non-glycosylated commercially available anti-PD-L1 antibody in various assays. No differences were observed regarding binding to PD-L1 and blocking of this interaction with its counter receptors PD-1 or CD80. The de-fucosylated anti-PD-L1 antibody showed increased FcγRIIIa binding resulting in enhanced antibody dependent cellular cytotoxicity (ADCC) activity against PD-L1+ cancer cells compared to the “normal”-glycosylated variant. Both glycosylation variants showed no antibody-mediated lysis of B cells and monocytes. The non-glycosylated reference antibody showed no FcγRIIIa engagement and no ADCC activity. Using mixed leukocyte reaction it was observed that the de-fucosylated anti-PD-L1 antibody induced the strongest CD8 T cell activation determined by expression of activation markers, proliferation, and cytotoxicity against cancer cells. The systematic comparison of anti-PD-L1 antibody glycosylation variants with different Fc-mediated potencies demonstrates that our glyco-optimization approach has the potential to enhance CD8 T cell-mediated anti-tumor activity which may improve the therapeutic benefit of anti-PD-L1 antibodies.
Urinary Biochemistry in the Diagnosis of Acute Kidney Injury

Acute kidney injury (AKI) is a common complication, impacting short- and long-term patient outcomes. Although the application of the classification systems for AKI has improved diagnosis, early clinical recognition of AKI is still challenging, as increments in serum creatinine may be late and low urine output is not always present. The role of urinary biochemistry has remained unclear, especially in critically ill patients. Differentiating between a transient and persistent acute kidney injury is of great need in clinical practice, and despite studies questioning their application in clinical practice, biochemistry indices continue to be used while we wait for a novel early injury biomarker. An ideal marker would provide more detailed information about the type, intensity, and location of the injury. In this review, we will discuss factors affecting the fractional excretion of sodium (FeNa) and fractional excretion of urea (FeU). We believe that the frequent assessment of urinary biochemistry and microscopy can be useful in evaluating the likelihood of AKI reversibility. The availability of early injury biomarkers could help guide clinical interventions.
A Type of Duality between Self-Organizing Maps and Minimal Wiring

I show here that two interpretations of neural maps are closely related. The first, due to Kohonen, sees these maps as forming by an adaptive process in response to stimuli. The secondthe minimal wiring or dimension-reduction perspectiveinterprets the maps as the solution of a minimization problem, where the goal is to keep the wiring between neurons with similar receptive fields as short as possible. Recent work by Luttrell provides a bridging concept, by showing that Kohonen's algorithm can be regarded as an approximation to gradient descent on a certain functional. I show how this functional can be generalized in a way that allows it to be interpreted as a measure of wirelength.
Electrical Control in Neurons by the Ketogenic Diet

The ketogenic diet is used as a diet treatment for drug-resistant epilepsy, but there are no antiepileptic drugs based on the ketogenic diet. The ketogenic diet changes energy metabolites (ketone bodies, glucose and lactate) in the brain, which consequently changes electrical activities in neurons and ultimately suppresses seizures in epileptic patients. In order to elucidate the antiseizure effects of the ketogenic diet, it is important to clarify the mechanism by which these metabolic changes are converted to electrical changes in neurons. In this review, we summarize electrophysiological studies focusing on electrical control in neurons by the ketogenic diet. Recent studies have identified electrical regulators driven by the ketogenic diet: ion channels (ATP-sensitive K+ channels and voltage-dependent Ca2+ channels), synaptic receptors (AMPA-type glutamate receptors and adenosine A1 receptors), neurotransmitter transporters (vesicular glutamate transporters), and others (BCL-2-associated agonist of cell death and lactate dehydrogenase). Thus, the ketogenic diet presumably elicits neuronal inhibition via the combined actions of these molecules. From the viewpoint of drug development, these molecules are valuable as targets for the development of new antiepileptic drugs. Drug therapy to mimic the ketogenic diet may be feasible in the future, through the combination of multiple antiepileptic drugs targeting these molecules.
An Uncharacterized Major Facilitator Superfamily Transporter From Planococcus maritimus Exhibits Dual Functions as a Na+(Li+, K+)/H+ Antiporter and a Multidrug Efflux Pump

Within major facilitator superfamily (MFS), up to 27 unknown major facilitator families and many members of 60 well-characterized families have been functionally unknown as yet, due to their sharing no or significantly low sequence identity with characterized MFS members. Here we present the first report on the characterization of one functionally unknown MFS transporter designated MdrP with the accession version No. ANU18183.1 from the slight halophile Planococcus maritimus DS 17275T. During the screening of Na+/H+ antiporter genes, we found at first that MdrP exhibits Na+(Li+, K+)/H+ antiport activity, and propose that it should represent a novel class of Na+(Li+, K+)/H+ antiporters. However, we speculate that MdrP may possess an additional protein function. The existence of the signature Motif A of drug/H+antiporter (DHA) family members and phylogenetic analysis suggest that MdrP may also function as a drug efflux pump, which was established by minimum inhibitory concentration tests and drug efflux activity assays. Taken together, this novel MFS transporter exhibits dual functions as a Na+(Li+, K+)/H+ antiporter and a multidrug efflux pump, which will be very helpful to not only positively contribute to the function prediction of uncharacterized MFS members especially DHA1 family ones, but also broaden the knowledge of Na+/H+ antiporters.
Interleukin-35 Inhibits TNF-α-Induced Osteoclastogenesis and Promotes Apoptosis via Shifting the Activation From TNF Receptor-Associated Death Domain (TRADD)–TRAF2 to TRADD–Fas-Associated Death Domain by JAK1/STAT1

Over-activated osteoclasts derived from myeloid or peripheral blood monocytes by inflammatory cytokines results in osteoporosis, osteoarthritis, and other bone erosion-related diseases. Interleukin 35 (IL-35) is a novel anti-inflammatory and immunosuppressive factor. This study investigated the effect of IL-35 on TNF-α-induced osteoclastogenesis. In the presence of IL-35, this process was detected by Tartrate-Resistant Acid Phosphatase (TRAP) staining, F-actin staining, and bone resorption assays. The effects of IL-35 on TNF-α-induced apoptosis were demonstrated by TUNEL staining, cell viability assays, and flow cytometry. Moreover, a microarray was performed to detect the effect of IL-35 on TNF-α-activated phosphatase kinase. The effect of IL-35 on the TNF-α-mediated activation of NF-κB, MAPK, TRAF2, RIP1, Fas-associated death domain (FADD), and caspase3 was further investigated. In addition, a murine calvarial osteolysis model was established via the subcutaneous injection of TNF-α onto the calvaria, and histological analysis was subsequently performed. As a result, IL-35 inhibited TNF-α-induced osteoclast formation and bone resorption in vitro and osteolysis calvaria in vivo. NFATc1, c-fos, and TRAP were downregulated by IL-35 through the inhibition of NF-κB and MAPK, during which JAK1/STAT1 was activated. Moreover, based on TUNEL staining and flow cytometry, IL-35 was shown to enhance TNF-α-induced osteoclast apoptosis. Meanwhile, FADD and cleaved-caspase 3 were increased in cells treated with TNF-α and IL-35, whereas the DNA-binding activity of NF-κB was increased in TNF-α-treated cells, but was decreased in cells treated with both TNF-α and IL-35. In conclusion, IL-35 inhibits TNF-α-induced osteoclastogenesis and promotes apoptosis by activating JAK1/STAT1 and shifting activation from TNF receptor-associated death domain (TRADD)-TRAF2/RIP1-NF-κB to TRADD-FADD-caspase 3 signaling.