Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge Graphs: A Practical Review of the Research Landscape

: Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten years. Building on a storied tradition of graphs in the AI community, a KG may be simply deﬁned as a directed, labeled, multi-relational graph with some form of semantics. In part, this has been fueled by increased publication of structured datasets on the Web, and well-publicized successes of large-scale projects such as the Google Knowledge Graph and the Amazon Product Graph. However, another factor that is less discussed, but which has been equally instrumental in the success of KGs, is the cross-disciplinary nature of academic KG research. Arguably, because of the diversity of this research, a synthesis of how different KG research strands all tie together could serve a useful role in enabling more ‘moonshot’ research and large-scale collaborations. This review of the KG research landscape attempts to provide such a synthesis by ﬁrst showing what the major strands of research are, and how those strands map to different communities, such as Natural Language Processing, Databases and Semantic Web. A uniﬁed framework is suggested in which to view the distinct, but overlapping, foci of KG research within these communities.
The Glycan-Specificity of the Pineapple Lectin AcmJRL and its Carbohydrate-Dependent Binding of the SARS-CoV-2 Spike Protein

The current SARS-CoV-2 pandemic has become one of the most challenging global health threats, with over 530 million reported infections by May 2022. In addition to vaccines, research and development have also been directed towards novel drugs. Since the highly glycosylated spike protein of SARS-CoV-2 is essential for infection, it constitutes a prime target for antiviral agents. The pineapple-derived jacalin-related lectin (AcmJRL) is present in the medication bromelain in significant quantities and has previously been described to bind mannosides. Here, we elucidated its ligand specificity by glycan array analysis, quantified the interaction with carbohydrates and validated high-mannose glycans as preferred ligands. Because the SARS-CoV-2 spike protein was previously reported to carry a high proportion of high-mannose N-glycans, we tested the binding of AcmJRL to recombinantly produced spike protein. We could demonstrate that AcmJRL binds the spike protein with a low micromolar KD in a carbohydrate-dependent fashion, suggesting its use as a potential SARS-CoV-2 neutralising agent.
Identification of epigenetic modulators as determinants of nuclear size and shape

The shape and size of the human cell nucleus is highly variable amongst cell types and tissues. Changes in nuclear morphology are associated with disease, including cancer, as well as with premature and normal aging. Despite the very fundamental nature of nuclear morphology, the cellular factors that determine nuclear shape and size are not well understood. To identify regulators of nuclear architecture in a systematic and unbiased fashion, we performed a high-throughput imaging-based siRNA screen targeting 867 nuclear proteins including chromatin-associated proteins, epigenetic regulators, and nuclear envelope components. Using multiple morphometric parameters, we identified cell-type specific and general effectors of nuclear size and shape. Interestingly, most identified factors altered nuclear morphology without affecting the levels of lamin proteins, which are known prominent regulators of nuclear shape. In contrast, a major group of nuclear shape regulators were modifiers of repressive heterochromatin. Biochemical and molecular analysis uncovered a direct physical interaction of histone H3 with lamin A mediated via combinatorial histone modifications. Furthermore, disease-causing lamin A mutations that result in disruption of nuclear shape inhibited lamin A-histone H3 interactions. Finally, oncogenic histone H3.3 mutants defective for H3K27 methylation resulted in nuclear morphology abnormalities. Altogether, our results represent a systematic exploration of cellular factors involved in determining nuclear morphology and they identify the interaction of lamin A with histone H3 as an important contributor to nuclear morphology in human cells.
Genome Similarities between Human-Derived and Mink-Derived SARS-CoV-2 Make Mink a Potential Reservoir of the Virus

The SARS-CoV-2 has RNA as the genome, which makes the virus more prone to mutations. Occasionally, mutations help a virus to cross the species barrier. The SARS-CoV-2 infection to humans and minks (Neovison vison) are examples of zoonotic spillover. Many studies have been published on the analysis of human-derived SARS-CoV-2, here we performed mutation analysis on the minks-derived SARS-CoV-2 genome sequences. We analyzed all available full-length mink derived SARS-CoV-2 genome sequences on GISAID (214 from Netherlands and 133 from Denmark). We found that the mutation pattern in the Netherlands and Denmark derived samples were different. Out of a total of 201 mutations, we found in this study, only 13 mutations were common in the Netherlands and Denmark derived samples. We found 4 mutations prevailed in the Netherlands and Denmark mink derived samples and these 4 mutations are also reported to prevail in human-derived SARS-CoV-2.
Inferring gene expression models from snapshot RNA data

Gene networks, key toward understanding a cell’s regulatory response, underlie experimental observations of single cell transcriptional dynamics. While information on the gene network is encoded in RNA expression data, existing computational frameworks cannot currently infer gene networks from such data. Rather, gene networks—composed of gene states, their connectivities, and associated parameters—are currently deduced by pre-specifying gene state numbers and connectivity prior to learning associated rate parameters. As such, the correctness of gene networks cannot be independently assessed which can lead to strong biases. By contrast, here we propose a method to learn full distributions over gene states, state connectivities, and associated rate parameters, simultaneously and self-consistently from single molecule level RNA counts. Notably, our method propagates noise originating from fluctuating RNA counts over networks warranted by the data by treating networks themselves as random variables. We achieve this by operating within a Bayesian nonparametric paradigm. We demonstrate our method on the lacZ pathway in Escherichia coli cells, the STL1 pathway in Saccharomyces cerevisiae yeast cells, and verify its robustness on synthetic data.
The Effect of Paracrine Factors Released by Irradiated Peripheral Blood Mononuclear Cells on Neutrophil Extracellular Trap Formation

Neutrophil extracellular trap (NET)-formation represents an important defence mechanism for rapid clearance of infections. However, exaggerated NET formation has been shown to negatively affect tissue-regeneration after injury. As our previous studies revealed strong tissue-protective and regenerative properties of the secretome of stressed peripheral blood mononuclear cells (PBMCsec), we here investigated the influence of PBMCsec on the formation of NETs. The effect of PBMCsec on NET formation was assessed ex vivo in ionomycin stimulated neutrophils derived from healthy donors using flow cytometry, image stream analysis and quantification of released extracellular DNA. Molecular mechanisms involved in NET formation that were potentially impaired by PBMCsec treatment, including protein kinase C activity, reactive oxygen species production and peptidyl arginine deiminase 4 activity were analysed. Our results showed that PBMCsec significantly inhibited NET formation. Investigation of the different biological substance classes found in PBMCsec revealed only partial reduction of NET formation, suggesting a synergistic effect. Mechanistically, PBMCsec treatment did not interfere with calcium signalling and PKC-activation, but exerted anti-oxidant activity, as evidenced by reduced levels of reactive oxygen species and upregulation of heme oxygenase 1, hypoxia inducible-factor 1 as well as heat shock protein 27 in PBMCsec-treated neutrophils. In addition, PBMCsec strongly inhibited the activation of peptidyl arginine deiminase 4 (PAD4), ultimately leading to the inhibition of NET formation. As therapeutics antagonizing excessive NET formation are currently not available, our study provides a promising novel treatment option for a variety of conditions resulting from exaggerated NET formation.
Comprehensive Comparative Genomic revels: Bacteroides fragilis is a reservoir of antibiotic resistance genes in the gut microbiota

Bacteroides fragilis are commensal bacteria of the gut microbiota of mammals and may cause severe infection in a susceptible host. Treatment can be cumbersome if multidrug resistant strains are present in the affected tissue. The principal aim of this study was to provide new insights into the genomic properties of B. fragilis through different approaches in comparative genomics. Results revealed that the pan-genome is opened, and an intense exchange of genetic material reinforces this inference. The Don complex, responsible for extraintestinal adaptation, is present in all strains, suggesting a crucial role for B. fragilis adaptation. CRISPR-Cas system is at 76% of the samples, but it apparently has low accuracy against prophage. Multidrug resistance genes are in 80% of strains. Conjugative transposons and integrative and conjugative elements (ICE) are the main spreaders of genes for antimicrobial resistance. We also reported evidence for horizontal gene transfer (HGT) of antimicrobial resistance genes among the B. fragilis strains and Bacteriodales. At least 398 genes are under positive selection, including genes for antimicrobial resistance and transport of toxins and nutrients.
DIAGNOSA KERUSAKAN BANTALAN BOLA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

Bearings are the critical part of any rotating machine. The catastrophic failure of the bearing can lead to fatal and harmful to the operation of the machine. Therefore, predictive maintenance based on condition monitoring of bearing is very important. The objective of this research is to apply Support Vector Machine (SVM) method for fault diagnosis of the ball bearing. The research was carried out at the bearing test rig. Four types of ball bearing condition, such as normal, inner race defect, ball defect, and outer race defect were measured of the vibration signals using data acquisition with a sampling frequency of 20 kHz at the constant speed of 1400 RPM. Various features were extracted from vibration signals in time domain, such as RMS, variance, standard deviation, crest factor, shape factor, skewness, kurtosis, log energy entropy and sure entropy. PCA transformation was employed to reduce the dimension of feature extracted data. SVM classification problems were solved using MATLAB 2016a. The results showed that the application of RBF kernel function with the C parameter =1 was the best configuration. The training model accuracy was 98.93% and the testing accuracy of SVM was 97.5%. Finally, the research results show that the SVM classification method can be used to diagnose the fault condition of the ball bearing.
Intestinal Norovirus Binding Patterns in Nonsecretor Individuals

Human norovirus (HuNoV) is the main etiological agent of viral gastroenteritis in all age classes. HuNoV infection affects mainly secretor individuals where ABO(H) and Lewis histo-blood group antigens (HBGAs) are present in the small intestine. ABSTRACT Human norovirus (HuNoV) infection is associated with an active FUT2 gene, which characterizes the secretor phenotype. However, nonsecretor individuals are also affected by HuNoV infection although in a lesser proportion. Here, we studied GII.3, GII.4, and GII.17 HuNoV interactions in nonsecretor individuals using virus-like particles (VLPs). Only GII.4 HuNoV specifically interacted with nonsecretor saliva. Competition experiments using histo-blood group antigen (HBGA)-specific monoclonal antibodies (MAbs) demonstrate that GII.4 VLPs recognized the Lewis a (Lea) antigen. We also analyzed HuNoV VLP interactions on duodenum tissue blocks from healthy nonsecretor individuals. VLP binding was observed for the three HuNoV genotypes in 10 of the 13 individuals, and competition experiments demonstrated that VLP recognition was driven by an interaction with the Lea antigen. In 3 individuals, binding was restricted to either GII.4 alone or GII.3 and GII.17. Finally, we performed a VLP binding assay on proximal and distal colon tissue blocks from a nonsecretor patient with Crohn’s disease. VLP binding to inflammatory tissues was genotype specific since GII.4 and GII.17 VLPs were able to interact with regenerative mucosa, whereas GII.3 VLP was not. The binding of GII.4 and GII.17 HuNoV VLPs was linked to Lea in regenerative mucosae from the proximal and distal colon. Overall, our data clearly showed that Lea has a pivotal role in the recognition of HuNoV in nonsecretors. We also showed that Lea is expressed in inflammatory/regenerative tissues and interacts with HuNoV in a nonsecretor individual. The physiological and immunological consequences of such interactions in nonsecretors have yet to be elucidated. IMPORTANCE Human norovirus (HuNoV) is the main etiological agent of viral gastroenteritis in all age classes. HuNoV infection affects mainly secretor individuals where ABO(H) and Lewis histo-blood group antigens (HBGAs) are present in the small intestine. Nonsecretor individuals, who only express Lewis (Le) antigens, are less susceptible to HuNoV infection. Here, we studied the interaction of common HuNoV genotypes (GII.3, GII.4, and GII.17) in nonsecretor individuals using synthetic viral particles. Saliva binding assays showed that only GII.4 interacted with nonsecretor saliva via the Lewis a (Lea) antigen Surprisingly, the three genotypes interacted with nonsecretor enterocytes via the Lea antigen on duodenal tissue blocks, which were more relevant for HuNoV/HBGA studies. The Lea antigen also played a pivotal role in the recognition of GII.4 and GII.17 particles by inflammatory colon tissue from a nonsecretor Crohn’s disease patient. The implications of HuNoV binding in nonsecretors remain to be elucidated in physiological and pathological conditions encountered in other intestinal diseases.
KIF1A is kinetically tuned to be a superengaging motor under hindering loads

KIF1A is a highly processive vesicle transport motor in the kinesin-3 family. Mutations in KIF1A lead to neurodegenerative diseases including hereditary spastic paraplegia. We applied optical tweezers to study the ability of KIF1A to generate and sustain force against hindering loads. We used both the three-bead assay, where force is oriented parallel to the microtubule, and the traditional single-bead assay, where force is directed along the radius of the bead, resulting in a vertical force component. The average force and attachment duration of KIF1A in the three-bead assay were substantially greater than those observed in the single-bead assay. Thus, vertical forces accelerate termination of force ramps of KIF1A. Average KIF1A termination forces were slightly lower than the kinesin-1 KIF5B, and the median attachment duration of KIF1A was >10-fold shorter than KIF5B under hindering loads. KIF1A rapidly reengages with microtubules after detachment, as observed previously. Strikingly, quantification enabled by the three-bead assay shows that reengagement largely occurs within 2 ms of detachment, indicating that KIF1A has a nearly tenfold faster reengagement rate than KIF5B. We found that rapid microtubule reengagement is not due to KIF1A’s positively charged loop-12; however, removal of charge from this loop diminished the unloaded run length at near physiological ionic strength. Both loop-12 and the microtubule nucleotide state have modulatory effects on reengagement under load, suggesting a role for the microtubule lattice in KIF1A reengagement. Our results reveal adaptations of KIF1A that lead to a novel model of super-engaging transport under load.
Overview of the NTCIR-13 QA Lab-3 Task

The NTCIR-13 QA Lab-3 task aims at the real-world complex Question Answering (QA) technologies using Japanese university entrance exams and their English translation on the subject of “World history”. QA Lab-3 has three end-toend tasks for multiple-choice, term and essay questions. The essay task has three subtasks of extraction, summarization and evaluation-method. There were 85 submissions from 13 teams in total. We describe the used data, formal run results, and comparison between human marks and automatic evaluation scores for essay questions. Categories and Subject Descriptions H.3. 4 [INFORMATION STORAGE AND RETRIEVAL]: Systems and Software Performance evaluation (efficiency and effectiveness), Question-answering (fact retrieval) systems.
Module for Determining the Technological State of Lease Automatic Custody Transfer Unit

The article discusses the relevance of the use of information systems in the oil industry, in particular – monitoring systems. The article describes the metrological equipment "Oil custody transfer metering system" (CTM). An integral part of the CTM work is monitoring its condition.One of the existing solutions for monitoring CTM is being developed by the Russian IT company CROC Incorporated. The article discusses the experience of designing and developing a module for determining the technological state of the CTM, which should become part of the solution of CROC Incorporated and become part of the solution for one of the leaders of Russia in the oil industry.The article proposes an approach for determining the technological state of the CTM depending on the operation status of each individual element located on the CTM. The first stage involves the interpretation of the CTM scheme as a mathematical graph and the application of the K-shortest path search algorithm to the graph. The second stage consists in analyzing the found paths and determining their state as part of the work of the CTM.To test the presented approach, a prototype of the module for determining the technological state of the CTM has been developed. One of the properties of the module is a universal interface for receiving the initial data of the CTM from various source systems. Due to this property, the module was able to integrate with the Microsoft Visio platform, in which various initial CTM diagrams were formed.In the presented material, the step-by-step application of the module for CTM with two measuring lines is considered. The material may be of interest not only from the point of view of approbation on real projects, but also in the process of advanced training of specialists operating the CTM.
A Wind Power Forecasting Method Considering Shape and Time Loss

To improve the accuracy of wind power time series with strong nonlinearity and non-stationarity, this paper proposed a wind power forecasting (WPF) method based on deep learning, which considers shape and time loss. First, A two-layer Gated Recurrent Unit (GRU) is used to construct a WPF model. Then, this paper uses differentiable dynamic time warping (DTW) to construct shape and time loss (STL) to improve the loss function of the GRU. STL decouples the time series in shape and time and provides their loss metrics. Finally, the test results on the wind power data of the Global Energy Forecasting Competition 2014 (GEFCom2014) show that compared with the traditional mean squared error (MSE) loss, the STL has a higher prediction accuracy on abrupt and non-stationary time series.
3D Printed Waveguide Transition for 77 GHz Radar Applications

A novel approach of a differential microstrip line to a rectangular waveguide realized by an alternative manu-facturing method, based on additive manufacturing, is presented. In comparison with conventional machining, this approach offers an improved behavior regarding weight, costs and uncomplicated alignment with simultaneous high manufacturing accuracy. The transition is designed for applications in the frequency range of 70 - 90 GHz in particular for automotive radar at 77 GHz but yet can easily be adapted for other frequencies. Measurements are carried out stating a return loss of /S11/2 < -24 dB and an insertion loss /S21/2 better than -1.3 dB at 77 GHz for the transition. To demonstrate excellent suitability for hybrid circuits an analysis of manufacturing tolerances and resulting degradation on the performance of the transition have been conducted. The measurements of this analysis prove a high reproducibility and robustness of the promising technology even for precision demanding mmW applications.
Research on 5G Base Station Energy Storage Configuration Taking Photovoltaics into Account

Because of its large number and wide distribution, 5G base stations can be well combined with distributed photovoltaic power generation. However, there are certain intermittent and volatility in the photovoltaic power generation process, which will affect the power quality and thus affect the operation of the base station. Energy storage technology is one of the effective measures to solve such problems. The battery-supercapacitor hybrid energy storage method is currently widely used in absorbing new energy. This article first introduces the energy depletion of 5G communication base stations(BS) and its mathematical model. Secondly, it introduces the photovoltaic output model, the power model of batteries and super capacitors(SC), and the capacity model, as well as the 5G BS hybrid energy storage system(HESS) model. Ground on the 24-hour photovoltaic power generation and load power depletion data of the 5G BS, the optimization solution is performed. The results verify the feasibility of the HESS for 5G communication BS.
Introducing Operations and Materials Management Concepts with a Classroom Production Activity

This active learning exercise has students build prototype products in order to learn materials control and manufacturing operations management concepts. Students go on to develop bills of material, create planned operations lists and bills of resources. Optionally, the exercise may be expanded to teach materials requirement planning (MRP) and rough-cut capacity planning (RCCP) techniques.
Simulation Research on Multi-energy Participation in Electricity Market Operation Considering User-side Carbon Responsibility

With the formal proposal of carbon peaking and carbon neutrality goals, as one of the key industries with large carbon emissions, the power industry needs to actively promote the low-carbon transformation of the power system. Since userside resources are the direct driving factor of carbon emissions on the power generation side, user-side demand response resources will be an important part of the development of low-carbon power systems in the future. Therefore, traditional power generation-side carbon emissions calculation methods are no longer applicable and there is an urgent need for a way to clarify the carbon responsibilities on the user side. This paper proposes a simulation research on power market operation that considers the participation of multi-energy generators. The market is cleared based on the unilateral three-stage quotation of the generators and the user-side carbon liability accounting is performed. Taking the PJM5 node system as an example, the simulation research on the operation of the power market involving multi-energy generators is carried out. In addition, a reasonable carbon liability allocation and carbon cost calculation on the user side are carried out. It is found that the indirect carbon emissions caused by different users are different, which provides a basis for the user side to actively participate in the low-carbon power system in the future.