Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene expression analysis of MBD proteins after treatment with DNMT inhibitors in breast cancer

Methyl-CpG binding domain (MBD) proteins are considered as the epigenetic readers of the methyl tags on DNA. This highly conserved family of DNA-binding proteins recognizes the information represented by methylation patterns and transduces them into appropriate functional states. MBD proteins bind to the DNA around methylated cytosine bases located particularly in the promoter regions, preventing binding of transcription factors and RNA polymerase and thereby repress transcription. Region-specific DNA hypermethylation is considered as a critical factor in tumorigenic progression. This hypermethylation induced silencing of tumor suppressor genes in cancer cells is mediated by MBD proteins, hence they are now considered as potential biomarkers for diagnosis and prognosis of malignant transformation. The present study will be conducted to analyse the gene expression status of the methyl-CpG-binding (MBD) proteins - MeCP2, MBD1, MBD2, MBD3 and MBD4 in breast cancer. This study will help in creating an epigenetic signature based on MBD protein distribution and occupancy in a gene and tumor type specific context for diagnosis and detection of different cancer types.
Age of Information for Single Buffer Systems With Vacation Server

In this research, we study the information freshness in M/G/1 queueing system with a single buffer and the server taking multiple vacations. This system has wide applications in communication systems. We aim to evaluate the information freshness in this system with both i.i. d. and non-i.i. d. vacations under three different scheduling policies, namely Conventional Buffer System (CBS), Buffer Relaxation System (BRS), and Conventional Buffer System with Preemption in Service (CBS-P). For the systems with i.i. d. vacations, we derive the closed-form expressions of information freshness metrics such as the expected Age of Information (AoI), the expected Peak Age of Information (PAoI), and the variance of peak age under each policy. For systems with non-i.i. d. vacations, we use the polling system as an example and provide the closed-form expression of its PAoI under each policy. We explore the conditions under which one of these policies has advantages over the others for each information freshness metric. We further perform numerical studies to validate our results and develop insights.
Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning

Channel pruning is one of the most important techniques for compressing neural networks with convolutional filters. However, in our study, we find strong similarities among some primary pruning criteria proposed in recent years. The sequence of filters'"importance" in a convolutional layer according to these criteria are almost the same, resulting in similar pruned structures. This finding can be explained by our assumption that the trained convolutional filters approximately follow a Gaussian-alike distribution, which is demonstrated through systematic and comprehensive statistical tests. Under this assumption, the similarity of these criteria is theoretically proved. Moreover, we also find that if the network has too much redundancy(exists a large number of filters in each convolutional layer), then these criteria can not distinguish the "importance" of the filters. This phenomenon is due to that the convolutional layer will form a special geometric structure when redundancy is large enough and our assumption holds: for every pair of filters in one layer, (1)Their $\ell_2$ norm are equivalent; (2)They are equidistant; (3)and they are orthogonal. The full appendix is released at this https URL.
Introducing Virtual Security Functions into Latency-aware Placement for NFV Applications

The shift towards a completely virtualized networking environment is triggered by the emergence of software defined networking and network function virtualization (NFV). Network service providers have unlocked immense capabilities by these technologies, which have enabled them to dynamically adapt to user needs by deploying their network services in real-time through generating Service Function Chain (SFCs). However, NFV still faces challenges that hinder its full potentials, including availability guarantees, network security, and other performance requirements. For this reason, the deployment of NFV applications remains critical as it should meet different service level agreements while insuring the security of the virtualized functions. In this paper, we tackle the challenge of securing these SFCs by introducing virtual security functions (VSFs) into the latency-aware deployment of NFV applications. This work insures the optimal placement of the SFC components including the security functions while considering the performance constraints and the VSFs’ operational rules such as, functions’ alliance, proximity, and anti-affinity. This paper develops a mixed integer linear programming model to optimally place all the requested SFCs while satisfying the above constraints and minimizing the latency of every SFC and the intercommunication delay between the SFC components. The simulations are evaluated against a greedy algorithm on the virtualized Evolved Packet Core use case and have shown promising results in maintaining the security rules while achieving minimum delays.
Maschke type theorems for Hopf monoids

We study integrals of Hopf monoids in duoidal endohom categories of naturally Frobenius map monoidales in monoidal bicategories. We prove two Maschke type theorems, relating the separability of the underlying monoid and comonoid, respectively, to the existence of normalized integrals. It covers the examples provided by Hopf monoids in braided monoidal categories, weak Hopf algebras, Hopf algebroids over central base algebras, Hopf monads on autonomous monoidal categories and Hopf categories.
Fréchet Distance for Uncertain Curves

In this article, we study a wide range of variants for computing the (discrete and continuous) Fréchet distance between uncertain curves. An uncertain curve is a sequence of uncertainty regions, where each region is a disk, a line segment, or a set of points. A realisation of a curve is a polyline connecting one point from each region. Given an uncertain curve and a second (certain or uncertain) curve, we seek to compute the lower and upper bound Fréchet distance, which are the minimum and maximum Fréchet distance for any realisations of the curves. We prove that both problems are NP-hard for the Fréchet distance in several uncertainty models, and that the upper bound problem remains hard for the discrete Fréchet distance. In contrast, the lower bound (discrete [5] and continuous) Fréchet distance can be computed in polynomial time in some models. Furthermore, we show that computing the expected (discrete and continuous) Fréchet distance is #P-hard in some models. On the positive side, we present an FPTAS in constant dimension for the lower bound problem when Δ/δ is polynomially bounded, where δ is the Fréchet distance and Δ bounds the diameter of the regions. We also show a near-linear-time 3-approximation for the decision problem on roughly δ-separated convex regions. Finally, we study the setting with Sakoe–Chiba time bands, where we restrict the alignment between the curves, and give polynomial-time algorithms for the upper bound and expected discrete and continuous Fréchet distance for uncertainty modelled as point sets.
Nonconvex penalization for sparse neural networks

Training methods for artificial neural networks often rely on over-parameterization and random initialization in order to avoid spurious local minima of the loss function that fail to fit the data properly. To sidestep this, one can employ convex neural networks, which combine a convex interpretation of the loss term, sparsity promoting penalization of the outer weights, and greedy neuron insertion. However, the canonical $\ell_1$ penalty does not achieve a sufficient reduction in the number of nodes in a shallow network in the presence of large amounts of data, as observed in practice and supported by our theory. As a remedy, we propose a nonconvex penalization method for the outer weights that maintains the advantages of the convex approach. We investigate the analytic aspects of the method in the context of neural network integral representations and prove attainability of minimizers, together with a finite support property and approximation guarantees. Additionally, we describe how to numerically solve the minimization problem with an adaptive algorithm combining local gradient based training, and adaptive node insertion and extraction.
Neural Correlates of Own- and Other-Face Perception in Body Dysmorphic Disorder

Background Body dysmorphic disorder (BDD) is characterized by an excessive preoccupation with one or more perceived flaws in one’s own appearance. Previous studies provided evidence for deficits in configural and holistic processing in BDD. Preliminary evidence suggests abnormalities at an early stage of visual processing. The present study is the first examining early neurocognitive perception of the own face in BDD by using electroencephalography (EEG). We investigated the face inversion effect, in which inverted (upside-down) faces are disproportionately poorly processed compared to upright faces. This effect reflects a disruption of configural and holistic processing, and in consequence a preponderance of featural face processing. Methods We recorded face-sensitive event-related potentials (ERPs) in 16 BDD patients and 16 healthy controls, all unmedicated. Participants viewed upright and inverted (upside-down) images of their own face and an unfamiliar other face, each in two facial emotional expressions (neutral vs. smiling). We calculated the early ERP components P100, N170, P200, N250, and the late positive component (LPC), and compared amplitudes among both groups. Results In the early P100, no face inversion effects were found in both groups. In the N170, both groups exhibited the common face inversion effects, with significantly larger N170 amplitudes for inverted than upright faces. In the P200, both groups exhibited larger inversion effects to other (relative to own) faces, with larger P200 amplitudes for other upright than inverted faces. In the N250, no significant group differences were found in face processing. In the LPC, both groups exhibited larger inversion effects to other (relative to own) faces, with larger LPC amplitudes for other inverted than upright faces. These overall patterns appeared to be comparable for both groups. Smaller inversion effects to own (relative to other) faces were observed in none of these components in BDD, relative to controls. Conclusions The findings suggest no evidence for abnormalities at all levels of early face processing in our observed sample of BDD patients. Further research should investigate the neural substrates underlying BDD symptomatology.
Inhibition of Helicoverpa armigera gut zymogen activation by plant protease inhibitors

The present studies demonstrated that non-host plant PIs were effective in inhibiting the isoproteinases and larval growth of H. armigera. Larval growth and development were reduced when fed on non-host plant PIs in artificial diet. Among the non-host plant PIs, Datura alba ness resulted in highest stunted growth. Non-host plant PIs have the potential to inhibit the growth of H. armigera larvae, which provides the basis for deploying these PI is in insect-resistant transgenic plants. Further research should focus on developing transgenic plants that express higher level of potent PIs to achieve protection against H. armigera.
FROST

The facility relocation (FR) problem, which aims to optimize the placement of facilities to accommodate the changes of users’ locations, has a broad spectrum of applications. Despite the significant progress made by existing solutions to the FR problem, they all assume each user is stationary and represented as a single point. Unfortunately, in reality, objects (e.g., people, animals) are mobile. For example, a car-sharing user picks up a vehicle from a station close to where he or she is currently located. Consequently, these efforts may fail to identify a superior solution to the FR problem. In this article, for the first time, we take into account the movement history of users and introduce a novel FR problem, called motion-fr, to address the preceding limitation. Specifically, we present a framework called frost to address it. frost comprises two exact algorithms: index based and index free. The former is designed to address the scenario when facilities and objects are known a priori, whereas the latter solves the motion-fr problem by jettisoning this assumption. Further, we extend the index-based algorithm to solve the general k-motion-fr problem, which aims to relocate k inferior facilities. We devise an approximate solution due to NP-hardness of the problem. Experimental study over both real-world and synthetic datasets demonstrates the superiority of our framework in comparison to state-of-the-art FR techniques in efficiency and effectiveness.
PRISM

Profession is an important social attribute of people. It plays a crucial role in commercial services such as personalized recommendation and targeted advertising. In practice, profession information is usually unavailable due to privacy and other reasons. In this article, we explore the task of identifying user professions according to their behaviors in social media. The task confronts the following challenges that make it non-trivial: how to incorporate heterogeneous information of user behaviors, how to effectively utilize both labeled and unlabeled data, and how to exploit community structure. To address these challenges, we present a framework called Profession Identification in Social Media. It takes advantage of both personal information and community structure of users in the following aspects: (1) We present a cascaded two-level classifier with heterogeneous personal features to measure the confidence of users belonging to different professions. (2) We present a multi-training process to take advantages of both labeled and unlabeled data to enhance classification performance. (3) We design a profession identification method synthetically considering the confidences from personal features and community structure. We collect a real-world dataset to conduct experiments, and experimental results demonstrate the significant effectiveness of our method compared with other baseline methods. By applying prediction on large-scale users, we also analyze characteristics of microblog users, finding that there are significant diversities among users of different professions in demographics, social network structures, and linguistic styles.
DomLock

We present efficient locking mechanisms for hierarchical data structures. Several applications work on an abstract hierarchy of objects, and a parallel execution on this hierarchy necessitates synchronization across workers operating on different parts of the hierarchy. Existing synchronization mechanisms are too coarse, too inefficient, or too ad hoc, resulting in reduced or unpredictable amount of concurrency. We propose a new locking approach based on the structural properties of the underlying hierarchy. We show that the developed techniques are efficient even when the hierarchy is an arbitrary graph. Theoretically, we present our approach as a locking-cost-minimizing instance of a generic algebraic model of synchronization for hierarchies. Using STMBench7, we illustrate considerable reduction in the locking cost, resulting in an average throughput improvement of 42%.
Transcriptome analysis indicates dominant effects on ribosome and mitochondrial function of a premature termination codon mutation in the zebrafish gene psen2

PRESENILIN 2 (PSEN2) is one of the genes mutated in early onset familial Alzheimer’s disease (EOfAD). PSEN2 shares significant amino acid sequence identity with another EOfAD-related gene PRESENILIN 1 (PSEN1), and partial functional redundancy is seen between these two genes. However, the complete range of functions of PSEN1 and PSEN2 is not yet understood. In this study, we performed targeted mutagenesis of the zebrafish psen2 gene to generate a premature termination codon close downstream of the translation start with the intention of creating a null mutation. Homozygotes for this mutation, psen2S4Ter, are viable and fertile, and adults do not show any gross pigmentation defects, arguing against significant loss of γ-secretase activity. Also, assessment of the numbers of Dorsal Longitudinal Ascending (DoLA) interneurons that are responsive to psen2 but not psen1 activity during embryogenesis did not reveal decreased psen2 function. Transcripts containing the S4Ter mutation show no evidence of destabilization by nonsense-mediated decay. Forced expression in zebrafish embryos of fusions of psen2S4Ter 5’ mRNA sequences with sequence encoding enhanced green fluorescent protein (EGFP) indicated that the psen2S4Ter mutation permits utilization of cryptic, novel downstream translation start codons. These likely initiate translation of N-terminally truncated Psen2 proteins that obey the “reading frame preservation rule” of PRESENILIN EOfAD mutations. Transcriptome analysis of entire brains from a 6-month-old family of wild type, heterozygous and homozygous psen2S4Ter female siblings revealed profoundly dominant effects on gene expression likely indicating changes in ribosomal, mitochondrial, and anion transport functions.
Ligand sensing enhances bacterial flagellar motor output via stator recruitment

The phenomenon of chemotaxis in bacteria, where the cells migrate towards or away from chemicals, has been extensively studied in the past. For flagellated bacteria such as Escherichia coli, a change in chemical concentration in its environment is sensed by a chemoreceptor and communicated via a well-characterised signalling pathway to the flagellar motor. It has been widely accepted that the signals change the rotation bias of the motor without influencing the motor speed. Here, we present results to the contrary and show that the bacteria is also capable of modulating motor speed on merely sensing a ligand. Step changes in concentration of non-metabolisable ligand cause temporary recruitment of stators leading to a momentary increase in motor speeds. For metabolisable ligand, the combined effect of sensing and metabolism leads to higher motor speeds for longer durations. Swimming speeds measured at the population level corroborate the observations. Experiments performed with mutant strains delineate the role of metabolism and sensing in the modulation of motor speed and show how speed changes along with changes in bias can significantly enhance bacteria’s response to changes in its environment.
The environment-sensing aryl-hydrocarbon receptor inhibits the chondrogenic fate of modulated smooth muscle cells in atherosclerotic lesions

Introduction Smooth muscle cells (SMC) play a critical role in atherosclerosis. The Aryl hydrocarbon receptor (AHR) is an environment-sensing transcription factor that contributes to vascular development, and has been implicated in coronary artery disease (CAD) risk. We hypothesized that AHR can affect atherosclerosis by regulating phenotypic modulation of SMC. Methods We combined RNA-Seq, ChIP-Seq, ATAC-Seq and in-vitro assays in human coronary artery SMC (HCASMC), with single-cell RNA-Seq (scRNA-Seq), histology, and RNAscope in an SMC-specific lineage-tracing Ahr knockout mouse model of atherosclerosis to better understand the role of AHR in vascular disease. Results Genomic studies coupled with functional assays in cultured HCASMC revealed that AHR modulates HCASMC phenotype and suppresses ossification in these cells. Lineage tracing and activity tracing studies in the mouse aortic sinus showed that the Ahr pathway is active in modulated SMC in the atherosclerotic lesion cap. Furthermore, scRNA-Seq studies of the SMC-specific Ahr knockout mice showed a significant increase in the proportion of modulated SMC expressing chondrocyte markers such as Col2a1 and Alpl, which localized to the lesion neointima. These cells, which we term “chondromyocytes” (CMC), were also identified in the neointima of human coronary arteries. In histological analyses, these changes manifested as larger lesion size, increased lineage-traced SMC participation in the lesion, decreased lineage-traced SMC in the lesion cap, and increased alkaline phosphatase activity in lesions in the Ahr knockout compared to wild-type mice. We propose that AHR is likely protective based on these data and inference from human genetic analyses. Conclusion Overall, we conclude that AHR promotes maintenance of lesion cap integrity and diminishes the disease related SMC-to-CMC transition in atherosclerotic tissues.
Effects of genomic and functional diversity on stand-level productivity and performance of non-native Arabidopsis

Biodiversity can affect the properties of groups of organisms, such as ecosystem function and the persistence of colonizing populations. Genomic data offer a newly available window to diversity, complementary to other measures like taxonomic or phenotypic diversity. We tested whether native genetic diversity in field experimental stands of Arabidopsis thaliana affected their aboveground biomass and fecundity in their colonized range. We constructed some stands of genotypes that we a priori predicted would differ in performance or show overyielding. We found no relationship between genetic diversity and stand total biomass. However, increasing stand genetic diversity increased fecundity in high resource conditions. Polyculture (multiple genotype) stands consistently yielded less biomass than expected based on the yields of component genotypes in monoculture. This under-yielding was strongest in stands with late-flowering and high biomass genotypes, potentially due to interference competition by these genotypes. Using a new implementation of association mapping, we identified genetic loci whose diversity was associated with stand-level yield, revealing a major flowering time locus associated with under-yielding of polycultures. Our field experiment supports community ecology studies that find a range of diversity-function relationships. Nevertheless, our results suggest diversity in colonizing propagule pools can enhance population fitness. Furthermore, interference competition among genotypes differing in flowering time might limit the advantages of polyculture.