Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural equation modeling approach between salience network dysfunction, depressed mood, and subjective quality of life in schizophrenia: an ICA resting-state fMRI study

Purpose Quality of life (QOL) is an important clinical outcome for patients with schizophrenia, and recent studies have focused on subjective QOL. We evaluated the causal relationship between psychosocial aspect of subjective QOL, symptoms, cognitive functions, and salience network (SN) dysfunction in schizophrenia using structural equation modeling (SEM). Patients and methods We performed a cross-sectional study of 21 patients with symptomatically stabilized schizophrenia and 21 age-, sex-, and education level-matched healthy controls who underwent resting-state functional magnetic resonance imaging. We evaluated SN dysfunction in schizophrenia using independent component analysis (ICA). We rated participant psychopathology using the Positive and Negative Syndrome Scale (PANSS), the Brief Assessment of Cognition in Schizophrenia (BACS), and the Calgary Depression Scale for Schizophrenia (CDSS). We rated psychosocial aspect of subjective QOL using the Schizophrenia Quality of Life Scale (SQLS) psychosocial subscale. We applied SEM to examine the relationships between SN dysfunction, PANSS positive and negative scores, CDSS total scores, BACS composite scores, and SQLS psychosocial subscale scores. Results In second-level analysis after group ICA, patient group had significant lower right pallidum functional connectivity (FC) within the SN than the controls did (Montreal Neurological Institute [MNI] [x y z] = [22 −2 −6]) (p = 0.027, family-wise error [FWE] corrected). In SEM, we obtained a good fit for an SEM model in which SN dysfunction causes depressed mood, which in turn determines psychosocial aspect of subjective QOL (chi-squared p = 0.9, root mean square error of approximation (RMSEA) < 0.001, comparative fit index [CFI] = 1.00, and standardized root mean square residual [SRMR]= 0.020). Conclusion We found a continuous process by which SN dysfunction causes depressed moods that determine psychosocial aspect of subjective QOL in schizophrenia. This is the first report that offers a unified explanation of functional neuroimaging, symptoms, and outcomes. Future studies combining neuroimaging techniques and clinical assessments would elucidate schizophrenia’s pathogenesis.
Ten-year study of late electrotherapy complications. Single-centre analysis of indications and safety of transvenous leads extraction.

BACKGROUND An increase in the number of cardiac implantable electronic device (CIED) implantations is associated with a higher frequency of electrotherapy complications. AIM The aim of the study was to determine the risk factors for late electrotherapy complications and to evaluate the effectiveness of transvenous lead extraction (TLE) and survival after TLE. METHODS We analysed the clinical data of 225 patients with electrotherapy complications referred for TLE in a single centre in the years 2006 to 2015. Indications for TLE, risk factors for infectious complications, effectiveness of TLE, and survival after the procedure were assessed. RESULTS In the study group, non-infectious indications for TLE predominated (78.2%). Analysis of risk for infectious complications demonstrated the important role of chronic renal failure (hazard ratio [HR] 1.842, p = 0.034) and a greater number of CIED-related procedures (HR 4.768, p < 0.001). High effectiveness of TLE and significantly higher long-term mortality of patients with infectious complications compared with the remainder (50% vs. 20%, p < 0.05) were documented. CONCLUSIONS The study demonstrated a high rate of patients with non-infectious complications referred for TLE and very high effectiveness of the procedure. The worse long-term survival of patients with infectious complications, as well as increased risk for such complications due to the greater number of prior procedures, should prompt the consideration of early referral for TLE in the case of lead dysfunctions.
Capsid protein structure, self-assembly, and processing reveal morphogenesis of the marine virophage mavirus

Significance Virophages are parasites of giant viruses within protists. They reduce giant virus production and increase host cell survival. They provide a defense system for protists against giant viruses in diverse environments, likely with ecological relevance for protist populations. To understand the remarkable virophage life cycle, it is crucial to investigate how they assemble into infectious particles and which processes require interactions with giant virus and host. We examined the marine virophage mavirus to show that its major and minor capsid proteins assemble into virus-like particles in the absence of specific host or viral factors. Subsequently, the virophage-encoded protease processes the major capsid protein to prepare virions for infection. Virophages have the unique property of parasitizing giant viruses within unicellular hosts. Little is understood about how they form infectious virions in this tripartite interplay. We provide mechanistic insights into assembly and maturation of mavirus, a marine virophage, by combining structural and stability studies on capsomers, virus-like particles (VLPs), and native virions. We found that the mavirus protease processes the double jelly-roll (DJR) major capsid protein (MCP) at multiple C-terminal sites and that these sites are conserved among virophages. Mavirus MCP assembled in Escherichia coli in the absence and presence of penton protein, forming VLPs with defined size and shape. While quantifying VLPs in E. coli lysates, we found that full-length rather than processed MCP is the competent state for capsid assembly. Full-length MCP was thermally more labile than truncated MCP, and crystal structures of both states indicate that full-length MCP has an expanded DJR core. Thus, we propose that the MCP C-terminal domain serves as a scaffolding domain by adding strain on MCP to confer assembly competence. Mavirus protease processed MCP more efficiently after capsid assembly, which provides a regulation mechanism for timing capsid maturation. By analogy to Sputnik and adenovirus, we propose that MCP processing renders mavirus particles infection competent by loosening interactions between genome and capsid shell and destabilizing pentons for genome release into host cells. The high structural similarity of mavirus and Sputnik capsid proteins together with conservation of protease and MCP processing suggest that assembly and maturation mechanisms described here are universal for virophages.
P16INK4a detection using an ultra-sensitive silicon nanowire field effect transistor

In general, if cancer can be earlier detected and treated, the chance of recovery is relatively much higher. Among all advanced molecular diagnostic techniques, silicon nanowire field effect transistor sensors have proven to have extremely high sensitivity and specificity. Through side-wall spacer etch technique which possesses simpler and cheaper process steps to manufacture polycrystalline silicon nanowire field effect transistor sensor. And p16INK4a protein which is related to cervical cancer, is taken as the target of detection. When human is infected with high-risk HPV, p16INK4a protein will be overexpressed. Therefore, we can know the extent of HPV infection by detecting p16INK4a protein, and then assess whether there is the risk of cervical cancer.
Early butyrate induced acetylation of histone H4 is proteoform specific and linked to methylation state

ABSTRACT Histone posttranslational modifications (PTMs) help regulate DNA templated processes; however, relatively little work has unbiasedly explored the single-molecule combinations of histone PTMs, their dynamics on short timescales, or how these preexisting histone PTMs modulate further histone modifying enzyme activity. We use quantitative top down proteomics to unbiasedly measure histone H4 proteoforms (single-molecule combinations of PTMs) upon butyrate treatment. Our results show that histone proteoforms change in cells within 10 minutes of application of sodium butyrate. Cells recover from treatment within 30 minutes after removal of butyrate. Surprisingly, K20me2 containing proteoforms are the near-exclusive substrate of histone acetyltransferases upon butyrate treatment. Single-molecule hierarchies of progressive PTMs mostly dictate the addition and removal of histone PTMs (K16ac > K12ac ≥ K8ac > K5ac, and the reverse on recovery). This reveals the underlying single-molecule mechanism that explains the previously reported but indistinct and unexplained patterns of H4 acetylation. Thus, preexisting histone PTMs strongly modulate histone modifying enzyme activity and this suggests that proteoform constrained reaction pathways are crucial mechanisms that enable the long-term stability of the cellular epigenetic state.
Merging-and-Evolution Networks for Mobile Vision Applications

Compact neural networks are inclined to exploit “sparsely-connected” convolutions, such as depthwise convolution and group convolution for employment in mobile applications. Compared with standard “fully-connected” convolutions, these convolutions are more computationally economical. However, “sparsely-connected” convolutions block the inter-group information exchange, which induces severe performance degradation. To address this issue, we present two novel operations named merging and evolution to leverage the inter-group information. Our key idea is encoding the inter-group information with a narrow feature map, and then combining the generated features with the original network for better representation. Taking advantage of the proposed operations, we then introduce the Merging-and-Evolution (ME) module, an architectural unit specifically designed for compact networks. Finally, we propose a family of compact neural networks called MENet based on the ME modules. Extensive experiments on CIFAR, SVHN, ILSVRC 2012, and PASCAL VOC 2007 data sets demonstrate that MENet consistently outperforms other state-of-the-art compact networks under different computational budgets. For instance, under the computational budget of 140 MFLOPs, MENet surpasses ShuffleNet by 1% and MobileNet by 1.95% on ILSVRC 2012 top-1 accuracy, while by 2.9% and 4.1% on PASCAL VOC 2007 mAP, respectively.
A novel pheromone initialization strategy of ACO algorithms for solving TSP

Travelling salesman problem (TSP), as a famous combinational optimization problem, has promoted the generation of a large number of algorithms. However, the existing algorithms, such as ant colony optimization (ACO) algorithms, still need to be enhanced further in terms of their robustness and the quality of the solution. In this paper, a novel pheromone initialization (NPI) strategy of ACO algorithms has been proposed for solving TSP, which shows a better efficiency in both robustness and the quality of the solution. Combining NPI strategy with a typical ACO algorithm like ant colony system (ACS) algorithm, a novel algorithm, called NPI-ACS algorithm, is put forward to strengthen the efficiency of ACS. Meanwhile, seven different scale datasets related to TSP are used to estimate the performance of NPI strategy. Afterwards, the experimental results show that there is a remarkable improvement in terms of robustness and the quality of the solution. Moreover, the proposed NPI strategy is flexible enough to be combined with multifarious ACO algorithms for solving TSP because of its independence in operation details.
Predicting miRNA‐disease association based on inductive matrix completion

Motivation: It has been shown that microRNAs (miRNAs) play key roles in variety of biological processes associated with human diseases. In Consideration of the cost and complexity of biological experiments, computational methods for predicting potential associations between miRNAs and diseases would be an effective complement. Results: This paper presents a novel model of Inductive Matrix Completion for MiRNA‐Disease Association prediction (IMCMDA). The integrated miRNA similarity and disease similarity are calculated based on miRNA functional similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. The main idea is to complete the missing miRNA‐disease association based on the known associations and the integrated miRNA similarity and disease similarity. IMCMDA achieves AUC of 0.8034 based on leave‐one‐out‐cross‐validation and improved previous models. In addition, IMCMDA was applied to five common human diseases in three types of case studies. In the first type, respectively, 42, 44, 45 out of top 50 predicted miRNAs of Colon Neoplasms, Kidney Neoplasms, Lymphoma were confirmed by experimental reports. In the second type of case study for new diseases without any known miRNAs, we chose Breast Neoplasms as the test example by hiding the association information between the miRNAs and Breast Neoplasms. As a result, 50 out of top 50 predicted Breast Neoplasms‐related miRNAs are verified. In the third type of case study, IMCMDA was tested on HMDD V1.0 to assess the robustness of IMCMDA, 49 out of top 50 predicted Esophageal Neoplasms‐related miRNAs are verified. Availability and implementation: The code and dataset of IMCMDA are freely available at https://github.com/IMCMDAsourcecode/IMCMDA. Supplementary information: Supplementary data are available at Bioinformatics online.
Patterns of Stability and Change in Business Processes

With the ubiquity of information systems in business and everyday life, people are increasingly leaving digital traces of their activities. Using this trace data alongside with other – more traditional – data collection techniques, such as interviews and document analysis, researchers can enhance their understanding of organizational processes and the different actors involved in these. In this Ph.D. research proposal, I outline an innovative approach that uses process mining techniques to capture “reality in flight”. Additionally, information stored in process model repositories and derived through expert interviews help to complement this perspective and make sense how stability and change occur in organizational processes.
Unsupervised Model for Topic Viewpoint Discovery in Online Debates Leveraging Author Interactions

Online debate forums provide a valuable resource for textual discussions about controversial social and political issues. Discovering the viewpoints and their discourse or arguments from such resources is important for policy and decision makers. In order to detect the stance, most of the existing methods rely on expensively obtained human annotations and propose supervised solutions. In this work, we introduce a purely unsupervised Author Interaction Topic Viewpoint model (AITV) for viewpoint identification at the post and the discourse levels. The model favors "heterophily" over "homophily" when encoding the nature of the authors' interactions in online debates. It assumes that the difference in viewpoints breeds interactions, unlike similar studies based on social network analysis, which hypothesize that similar viewpoints encourage interactions. We evaluate the model's viewpoint identification and clustering accuracies at the author and post levels. Experiments are held on six corpora about four different controversial issues, extracted from two online debate forums. AITV's results show a better performance in terms of viewpoint identification at the post level than the state-of-the-art supervised methods in terms of stance prediction, even though it is unsupervised. It also outperforms a recently proposed topic model for viewpoint discovery in social networks and achieves close results to a weakly guided unsupervised method in terms of author level viewpoint identification. Our results highlight the importance of encoding "heterophily" for purely unsupervised viewpoint identification in the context of online debates. We also carry out a brief qualitative evaluation of the discourse modeling in terms of Topic-Viewpoint word clusters. AITV shows encouraging results suggesting an accurate discovery of the viewpoints and topics' discourses.
Luminance compensation design using modified histogram equalization for driving assistance system under night vision

Night Vision Assistant can offer safety for the pedestrians at night, but the clarity of the capturing video has historically been an issue and needed to be improved. This paper focuses on applying MATLAB (Matrix Laboratory) for determining how the image should be modified through back-propagation neural network, and the image will be adjusted for better luminosity automatically through the modified algorithm of histogram equalization. The result shows that the modified image can be more easily discernable, as well as the distortion problems caused by overexposure and underexposure can be improved.
Eye-diagram estimation with stochastic model for 8B/10B encoded high-speed channel

This paper proposes an eye-diagram estimation method for 8B/10B encoded channel. The stochastic model describes the encoder with respect to probability, which replaces the practical encoder. Because the 8B/10B encoder consists of 3-to-4 and 5-to-6 look-up-table (LUTs), they can be represented as its own stochastic model. For verification, we compare the statistical eye-diagram by the proposed method and the SPICE at the same data rate. The changes on the eye-diagram for both cases are nearly the same by the encoder. Therefore, the proposed method successfully achieves the eye-diagram evaluation for the 8B/10B encoded high-speed channel.
A Survey of Online Sequential Extreme Learning Machine

Online sequential extreme learning machine (OS-ELM) can learn the data one-by-one or chunk-by-chunk with the fixed or varying chunk size. It was proposed by Liang et al. is a faster and more accurate algorithm as compared to other online learning algorithms. However, besides the advantages of OS-ELM machine, the original OS-ELM algorithm also introced some issues; first, the improved OS-ELM algorithms need to be network structure adjustment to improve learning promance; second, OS-ELM algorithm learning with stability will affect its generalization ability. For such reasons, in this paper we propose a survey of OS-ELM algorithm with the development of history and the latest results of researching which can hopefully support researchers in the furture.
Histone H3 threonine 11 phosphorylation by Sch9 and CK2 regulates chronological lifespan by controlling the nutritional stress response

Upon nutritional stress, the metabolic status of cells is changed by nutrient signaling pathways to ensure survival. Altered metabolism by nutrient signaling pathways has been suggested to influence cellular lifespan. However, it remains unclear how chromatin regulation is involved in this process. Here, we found that histone H3 threonine 11 phosphorylation (H3pT11) functions as a marker for nutritional stress and aging. Sch9 and CK2 kinases cooperatively regulate H3pT11 under stress conditions. Importantly, H3pT11 defective mutants prolonged chronological lifespan (CLS) by altering nutritional stress responses. Thus, the phosphorylation of H3T11 by Sch9 and CK2 links a nutritional stress response to chromatin in the regulation of CLS.
SenFact algorithm: Fact-checking by the confrontation of opinions

The pluralism of media and the unbridled running in production have resulted in a considerable increase of the volume of treated and produced data, but also the proliferation of wrong information. The internet-user is so confronted with two major problems: the identification of the reliable sources and the reliability of information. Indeed, there is no guarantee of the accuracy of the given information and it is not always obvious to determine in advance priori one or several reliable sources. It has been since then necessary to have new methods, automated by fact-checking to satisfy this strong request with quality information. One of the approaches used in this quality search is Fact-Checking or «check on facts1». But, when the number of sources becomes numerous, most part of the algorithm of literature becomes less definite. In this paper, we introduce an algorithm of fact-checking named SenFact based on the confrontation of opinions that is to say the use of the knowledge of domain as a key element in the process of fact-checking.
A high-gain circularly-polarized patch antenna design using an advanced shielding technique

In this paper, a high-gain circularly-polarized antenna is created by integrating a simple linearly-polarized patch antenna and an advanced electromagnetic shielding. This shielding is specially designed to have a band-pass property which could reduce the electromagnetic interference (EMI) of the shielded system and allow its signal wave radiated from the internal antenna to pass through. Moreover, the shielding could transform a linearly-polarized wave to circularly-polarized and highly increase its gain as well.
Influence of photoluminescent Si and ZnO QD multilayered films on solar cell efficiency

We report the synthesis and characterization of silicon (Si) and zinc oxide (ZnO) quantum dots (QDs), that exhibit down-shifting photoluminescent characteristics, and their deployment on photovoltaic devices. The ZnO QDs were synthesized in an ethanol-based colloidal solution and dispersed in a matrix of poly-methyl-methacrylate (PMMA), while the Si QDs were synthesized in a water-based colloidal solution and spin cast directly on the window surface of solar cells. The thickness of the photoluminescent coatings for silicon solar cells was theoretically optimized to reduce the reflectivity and verified experimentally for a variety of configurations, including single- layer and double-layer coatings. The analysis also included the effect of the presence of the antireflective layer of silicon nitride on the solar cell surface. The deployment of the aforementioned films as photon down shifting layers on solar cells enabled improvements in the efficiency of the photovoltaic devices from 14.42% to 15.41%. These observations indicate an improvement of ~6.8% in the power conversion efficiency. The identified best practices conducive to increasing the efficiency of photovoltaic devices employing Si and ZnO quantum dots are discussed herein.