Frequency-Domain Identification of Radiation Forces for Floating Wind Turbines by Moment-Matching

The dynamics of a floating structure can be expressed in terms of Cummins’ equation, which is an integro-differential equation of the convolution class. In particular, this convolution operator accounts for radiation forces acting on the structure. Considering that the mere existence of this operator is highly inconvenient due to its excessive computational cost, it is commonly replaced by an approximating parametric model. Recently, the Finite Order Approximation by Moment-Matching (FOAMM) toolbox has been developed within the wave energy literature, allowing for an efficient parameterisation of this radiation force convolution term, in terms of a state-space representation. Unlike other parameterisation strategies, FOAMM is based on an interpolation approach, where the user can select a set of interpolation frequencies where the steady-state response of the obtained parametric representation exactly matches the behaviour of the target system. This paper illustrates the application of FOAMM to a UMaine semi-submersible-like floating structure.

Development and Validity of Questionnaire for Healthy Adult Human Participants of Early Phase Bioequivalence Pharmacokinetic Endpoint Study

Participation of humans in clinical research is always remained questionable. Hence evaluation of such doubt helps to conclude the perception about such participation. This research presents the process for development and validation of questionnaire for Healthy Adult Human Participants of Early Phase Bioequivalence Pharmacokinetic Endpoint Study. For development of questionnaire, literature search, experts’ discussion and authors’ experience was used for domain identification and its segregation for different variables. For validity of questionnaire, face validity and content validity was performed. Modification was done based on response from experts during non-quantitative face validity. % of overall agreement was 94.55 for question asked in face validity. While, Content Validity Ratio and Content Validity Index was calculated using the process mentioned by Lawshe and Lynn respectively. Initially 83 items were identified but based on validation 84 items were finalized after removal of three and addition of four questions. Deleted three items had Content Validity Ratio of 0.00, 0.67 and 0.67 and which were below accepted level of 0.99. While, I-CVI was observed from range of 0.83 to 1.00 and S-CVI values were above acceptable level of 0.90 for S-CVI (S-CVI/ Ave) and 0.80 for S-CVI (S-CVI/UA) for whole questionnaire and each part.

An Enhanced Deep Recurrent Neural Network for Autism Spectrum Disorder Diagnosis

Autism Spectrum Disorder is one of the major investigation area in current era. There are many research works introduced earlier for handling the Autism Spectrum Disorders. However those research works doesn’t achieve the expected accuracy level. The accuracy and prediction efficiency can be increased by building a better classification system using Deep Learning. This paper focuses on the deep learning technique for Autism Diagnosis and the domain identification. In the proposed work, an Enhanced Deep Recurrent Neural Network has been developed for the detection of ASD at all ages. It attempts to predict the autism spectrum in the children along with prediction of areas which can predict the autism in the prior level. The main advantage of EDRNN is to provide higher accuracy in classification and domain identification. Here Artificial Algal Algorithm is used for identifying the most relevant features from the existing feature set. This model was evaluated for the data that followed Indian Scale for Assessment of Autism. The results obtained for the proposed EDRNN has better accuracy, sensitivity, specificity, recall and precision.

The Role of Flagellin B in Vibrio anguillarum-Induced Intestinal Immunity and Functional Domain Identification

Vibrio anguillarum, an opportunistic pathogen of aquatic animals, moves using a filament comprised of polymerised flagellin proteins. Flagellins are essential virulence factors for V. anguillarum infection. Herein, we investigated the effects of flagellins (flaA, flaB, flaC, flaD and flaE) on cell apoptosis, TLR5 expression, and production of IL-8 and TNF-α. FlaB exhibited the strongest immunostimulation effects. To explore the functions of flaB in infection, we constructed a flaB deletion mutant using a two-step recombination method, and in vitro experiments showed a significant decrease in the expression of TLR5 and inflammatory cytokines compared with wild-type cells. However in the in vivo study, expression of inflammatory cytokines and intestinal mucosal structure showed no significant differences between groups. Additionally, flaB induced a significant increase in TLR5 expression based on microscopy analysis of fluorescently labelled TLR5, indicating interactions between the two proteins, which was confirmed by native PAGE and yeast two-hybrid assay. Molecular simulation of interactions between flaB and TLR5 was performed to identify the residues involved in binding, revealing two binding sites. Then, based on molecular dynamics simulations, we carried out thirteen site-directed mutations occurring at the amino acid sites of Q57, N83, N87, R91, D94, E122, D152, N312, R313, N320, L97, H316, I324 in binding regions of flaB protein by TLR5, respectively. Surface plasmon resonance (SPR) was employed to compare the affinities of flaB mutants for TLR5, and D152, D94, I324, N87, R313, N320 and H316 were found to mediate interactions between flaB and TLR5. Our comprehensive and systematic analysis of V. anguillarum flagellins establishes the groundwork for future design of flagellin-based vaccines.

Natural variant frequencies across domains from different sarcomere proteins cross-correlate to identify inter-protein contacts associated with cardiac muscle function and disease

Coordinated sarcomere proteins produce contraction force for muscle shortening. In human ventriculum they include the cardiac myosin motor (βmys), repetitively converting ATP free energy into work, and myosin binding protein C (MYBPC3) that in complex with βmys is regulatory. Single nucleotide variants (SNVs) causing hereditary heart diseases frequently target this protein pair. The βmys/MYBPC3 complex models a regulated motor and is used here to study how the proteins couple. SNVs in βmys or MYBPC3 survey human populations worldwide. Their protein expression modifies domain structure affecting phenotype and pathogenicity outcomes. When the SNV modified domain locates to inter-protein contacts it could affect complex coordination. Domains involved, one in βmys the other in MYBPC3, form coordinated domains (co-domains). Co-domain bilateral structure implies the possibility for a shared impact from SNV modification in either domain suggesting a correlated response to a common perturbation could identify their location. Genetic divergence over human populations is proposed to perturb SNV probability coupling that is detected by cross-correlation in 2D correlation genetics (2D-CG). SNV probability data and 2D-CG identify three critical sites, two in MYBPC3 with links to several domains across the βmys motor, and, one in βmys with links to the MYBPC3 regulatory domain. MYBPC3 sites are hinges sterically enabling regulatory interactions with βmys. The βmys site is the actin binding C-loop (residues 359-377). The C-loop is a trigger for actin-activated myosin ATPase and a contraction velocity modulator. Co-domain identification implies their spatial proximity suggesting a novel approach for in vivo protein complex structure determination.

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker

Background Mastitis is one of the major diseases causing economic loss to the dairy industry by reducing the quantity and quality of milk. Thus, the objective of this scientific study was to find new biomarkers based on genes for the early prediction before its severity. Methods In the present study, advanced bioinformatics including hierarchical clustering, enrichment analysis, active site prediction, epigenetic analysis, functional domain identification, and protein docking were used to analyze the important genes that could be utilized as biomarkers and therapeutic targets for mastitis. Results Four differentially expressed genes (DEGs) were identified in different regions of the mammary gland (teat cistern, gland cistern, lobuloalveolar, and Furstenberg’s rosette) that resulted in 453, 597, 577, and 636 DEG, respectively. Also, 101 overlapped genes were found by comparing 27 different expressed genes. These genes were associated with eight immune response pathways including NOD-like receptor signaling pathway (IL8, IL18, IL1B, PYDC1) and chemokine signaling pathway (PTK2, IL8, NCF1, CCR1, HCK). Meanwhile, 241 protein-protein interaction networks were developed among overlapped genes. Fifty-seven regulatory events were found between miRNAs, expressed genes, and the transcription factors (TFs) through micro-RNA and transcription factors (miRNA-DEG-TF) regulatory network. The 3D structure docking model of the expressed genes proteins identified their active sites and the binding ligands that could help in choosing the appropriate feed or treatment for affected animals. Conclusions The novelty of the distinguished DEG and their pathways in this study is that they can precisely improve the detection biomarkers and treatments techniques of cows’ Escherichia coli mastitis disease due to their high affinity with the target site of the mammary gland before appearing the symptoms. Graphical abstract

Desain Panduan Audit Tata Kelola Sistem Informasi Boost The Order (SIBORDER) di PT Telekomunikasi Indonesia Menggunakan COBIT 2019

PT Telekomunikasi Indonesia Tbk (Telkom) is engaged in information and communication technology and network services. Information technology (IT) plays an important role in PT Telkom's business processes, so it needs to be managed using the Control Objectives for Business and Related Technology (COBIT) framework. COBIT 2019 accommodates new IT trends in business, so that it can serve as a guide for auditors, users and management to bridge the gap between risk, control, and technical problems at PT Telkom, especially in the management of the Boost The Order (SIBORDER) Information System. IT governance audit is a control mechanism for SIBORDER management. Therefore, before conducting the audit, the auditor needs to make an audit plan to make it easier when allocating resources so that the audit is carried out effectively and efficiently. This research aims to design a SIBORDER governance audit guide using the COBIT 2019 framework. The design begins first, by identifying stakeholder needs, enterprise goals and weighting design factors. The results of stakeholder needs, namely optimizing risk and resources, while enterprise goals, namely EG01, EG05, EG06 and EG13, and the results of domain identification as focus areas, namely BAI 10, DSS 03, DSS 04 and DSS 05. Second, determination of information sources based on the RACI Chart. Third, the creation of an audit worksheet that contains a list of questions for the assessment of the selected domain and the schedule of audit implementation.