47 research outputs found
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Tyrosine phosphorylation of histone H2A by CK2 regulates transcriptional elongation and DNA damage repair
No full textIn eukaryotes, genomic DNA is packaged into histone proteins, which can undergo post-translational modifications that are in turn critical in regulating transcription, the cell cycle, DNA replication, and DNA damage repair. In this study, we identify a novel tyrosine phosphorylation in histone H2A (Y57) that is conserved from yeast to mammals. Surprisingly, the phosphorylation is mediated by an unsuspected tyrosine kinase activity of casein kinase 2 (CK2). Mutation of the Y57 residue or inhibition of CK2 activity impairs transcriptional elongation, marked by a decrease in the recruitment of RNA polymerase II across active genes in yeast as well as mammalian cells. Genome-wide binding analysis reveals that CK2 alpha, the catalytic subunit of CK2, binds across RNA polymerase II-transcribed coding genes and active enhancers. Mutation of Y57 causes a defect in transcriptional elongation and DNA damage repair. At the molecular level, Y57 mutation causes a dramatic loss of H2B mono-ubiquitylation as well as H3K4me3 and H3K79me3 (histone marks associated with active transcription), a decrease in H2A mono-ubiquitylation and an increase in H2A S128 (H2AX S139 in mammals) phosphorylation (histone mark associated with DNA damage). Mechanistically, both CK2 inhibition and H2A-Y57F mutation antagonize the H2B deubiquitylation activity of the SAGA complex, suggesting a critical role of this novel phosphorylation event in coordinating the activity of the SAGA complex during transcription and DNA damage repair. Together, these results identify a new component of regulation in transcriptional elongation and DNA damage repair based on CK2-dependent tyrosine phosphorylation of the globular domain of H2
Assessment of the Required Subdivision Index for autonomous ships based on equivalent safety
No full textIn recent years, a significant amount of research has been conducted on autonomous ships. Since it is assumed that these ships will sail with a significantly reduced crew or even without people on board, the design of the ship needs reconsideration. The absence of people on board and the associated safety measures could result in a more efficient design. However, to achieve the required design freedom, the existing regulatory framework will have to be amended. In this article, we will focus on potential changes in the Convention for Safety Of Life At Sea (SOLAS) and in particular on the Required Subdivision Index. The evaluation is performed by using the principle of equivalent safety, which will ensure that unmanned ships will be at least as safe as manned ships. The index gives a requirement for the allowed probability of sinking when a ship is damaged due to collision or contact. The safety level is related to the safety of ship, cargo, environment and crew. If the crew is no longer present, the consequences of an incident will be less severe, since the probability of casualties is no longer present. If the principle of equivalent safety is applied, a lower subdivision index can be accepted for unmanned autonomous vessels. In this article, the level of risk that a manned ship is subjected to will be derived by means of a risk analysis. In this risk analysis all logical consequences of a collision will be taken into account, covering both the probability of losing the entire ship and the consequences of the cases where the ship will not sink. Thereafter, the Required Subdivision Index for unmanned ships, which ensures an equivalent safety level to an equivalent manned ship, is established. The sensitivity of the result to changes in the data is discussed as well.Ship Design, Production and Operation
OPTIMALISASI PERSEDIAAN BAHAN BAKU MULTI-ITEM MULTI-SUPPLIER DENGAN MENGGUNAKAN MODIFIED BASNET AND LEUNG FORMULATION (Studi Kasus: PT. Petrokimia Gresik)
No full textJika membutuhkan abstrak atau isi jurnal silahkan menghubungi author melalui email [email protected], [email protected], [email protected] Terima kasi
The measurement of internal supply chain integration
No full textPurpose: Internal supply chain refers to the chain of activities within a company that concludes with providing a product to the customer. This process involves multiple functions within companies such as sales, production, and distribution. It is obvious that a company's performance would be enhanced by the integration of these functions. However, there is no consensus yet on how integration is to be defined and measured. The purpose of this paper is to present research that was conducted with the goal of developing an instrument for the measurement of internal supply chain integration. Design/methodology/approach: Scale items were identified from current literature and the resulting survey instrument was sent out to a sample of New Zealand manufacturers. Statistical analysis was conducted to purify and validate the instrument. Findings: In total, three dimensions of integration were identified, labelled coordination, communication, and affective relationship. This paper makes a contribution towards developing a consensus in the understanding and measurement of the integration construct. Research limitations/implications: The selection and exclusion of measurement items for the survey have followed established principles of survey research, but may have been affected by the personal bias of the author. While every attempt has been made to comprehensively capture the state of the research up to the time of the study, there may be some omissions. The sample for the survey was drawn from a database of New Zealand businesses, thus the results are generalizable only to the extent that these businesses represent the population of all businesses. Another limitation is that no prior survey/case studies were carried out to collect practitioner's definitions/measures for integration. Practical implications: The authors hope to have made a contribution here towards building a consensus among practitioners and researchers in defining and measuring internal supply chain integration. For practitioners, the measurement instrument offers a self-assessment tool for internal supply chain integration. This should help them in identifying areas for improvement. Originality/value: The contribution of this paper consists of: development of an instrument for the measurement of integration, validating the instrument against a criterion, and the identification of three dimensions of integration - communication, coordination, and affective relationship. The unique contributions of this paper are the validation of the instrument against a criterion and the identification of "affective relationship" as a dimension of internal supply chain integration
Correlation of Fine Needle Aspiration Cytology and Histopathology of the Neck Swellings Presenting at National Academy of Medical Sciences, Kathmandu, Nepal
No full textIntroductionNeck masses are frequently found in clinical practice. A spectrum of pathological lesions ranging from inflammation to benign and highly malignant manifestation is observed. Fine needle aspiration cytology (FNAC) of neck masses is a quick, easy, safe and cheap technique in the diagnosis which has been a well-accepted procedure in diagnosing various swellings. Histopathology is a gold standard technique in diagnosing any swelling which also provide detail architecture, however it also requires OT setings, more manpower, expensive, time consuming, more traumatic and can sometimes become difficult.ObjectiveThe objective of our study was to evaluate the frequencies of neck swellings and how efficacy FNAC is in diagnosing neck masses by correlating the gold standard histopathological examination.MethodologyA Hospital based descriptive cross sectional prospective study was conducted in 50 patients with neck swellings presenting in the surgery OPD and admitied patient for some other reasons. FNAC and histopathological examinations were done from those lesions and were compared. The sensitivity, specificity and accuracy rates were calculated. Data entry and analysis was performed using SPSS.ResultsA total of 50 patient were subjected to both FNAC and histopathology examination (HPE). Out of 50 cases, 25 were male and 25 were female. The age ranged from 16 to 82 years. Lymph nodes 22 (44%) was the most common case, followed by thyroid 17 (34%), salivary glands 10 (20%) and soft issue 1 (2%).Among all Tubercular lymphadenitis (18%) followed by papillary carcinoma of thyroid (14%),metastatic carcinoma of lymph node, NHL, and pleomorphic adenoma 10% each. The sensitivity of FNAC in diagnosing neck masses is 90.08%, specificity is of 98.53%, and diagnostic accuracy is of 87.64%.ConclusionFNAC is a simple, fast, inexpensive, and minimally invasive technique which can be used as the first line investigation in diagnosing neck swellings.Birat Journal of Health SciencesVol.2/No.1/Issue 2/ Jan - April 2017, page: 206-210</jats:p
Research on risk, safety, and reliability of autonomous ships: A bibliometric review
No full textThe safety and reliability of autonomous ships are critical for the successful realization of an autonomous maritime ecosystem. Research and collaboration between governments, industry, and academia are vital in achieving this goal. This paper conducts a bibliometric review of the research on the risk, safety, and reliability of autonomous ships aiming to provide researchers and maritime stakeholders with a structured overview of the topics, development trends, and collaboration networks in this research field. 417 papers published between 2011 and 2022 were identified covering 940 authors, 31 countries, and 227 journals. Three main themes were determined in this research domain: “safety engineering and risk assessment for decision making”, “navigation safety and collision avoidance”, and “cybersecurity risk analysis”. Meanwhile, it was identified that research on cybersecurity in autonomous shipping is moving to overlap with safety, which requires future co-analysis methods. Additionally, the analysis of the most cited 30 papers suggests that further research is needed in the topics of unmanned machinery operation risks, online risk tools, system-theoretic safety analysis, human factor, and the determination of suitable risk acceptance criteria for safety assessment of autonomous ships. Furthermore, the analysis revealed that the development of unambiguous COLREGs regulation is crucial for the development of safe collision avoidance algorithms for MASS. It was identified that the publication by Fan et al., (2020) is a key publication in this research field, while the journals of Ocean Engineering, Reliability Engineering & System Safety, and Safety Science are the key journals publishing on autonomous ship safety and reliability.Safety and Security Scienc
A Master’s Project Presented to Department of Network and Computer Security in Partial Fulfillment of the Requirements for the Master of Science Degree
No full textToday, the wireless network devices are growing rapidly, and it is of utmost importance for securing those devices. Attackers or hackers use new methods and techniques to trick the system and steal the most important data. Intrusion Detection Systems
detect the attacks by inspecting the network traffics or logs. The work demonstrated the effectiveness of detecting the attacks
using machine learning techniques on the AWID dataset, which is produced from real wireless network logging. The author of the AWID dataset may have used several supervised learning models to successfully detect the intrusions. In this paper, we propose a newer approach for intrusion detection model based on dense neural networks, and long short-term memory networks (LSTM) and evaluate the model against the AWID-CLS-R subset. To get the best results from the model, we applied feature selection by replacing the unknown data with the value of “none”, getting rid of all repeated values, and kept only the important features. We did preprocess and feature scaling of both training and testing dataset, additional we also change the 2-dimensional to the 3- dimensional array because LSTM takes an input of 3-dimensional array, and later we used flatten layers to change into a 2-dimensional array for output. A comprehensive evaluation of DNN and LSTM networks are used to classify and predict the attacks and compute the precision, recall, and F1 score. We perform binary classification and multiclass classification on the dataset using neural networks and achieve accuracy ranging from 86.70 % to 96.01%
A Master’s Project Presented to Department of Network and Computer Security in Partial Fulfillment of the Requirements for the Master of Science Degree
No full textToday, the wireless network devices are growing rapidly, and it is of utmost importance for securing those devices. Attackers or hackers use new methods and techniques to trick the system and steal the most important data. Intrusion Detection Systems detect the attacks by inspecting the network traffics or logs. The work demonstrated the effectiveness of detecting the attacks using machine learning techniques on the AWID dataset, which is produced from real wireless network logging. The author of the AWID dataset may have used several supervised learning models to successfully detect the intrusions. In this paper, we propose a newer approach for intrusion detection model based on dense neural networks, and long short-term memory networks (LSTM) and evaluate the model against the AWID-CLS-R subset. To get the best results from the model, we applied feature selection by replacing the unknown data with the value of “none”, getting rid of all repeated values, and kept only the important features. We did preprocess and feature scaling of both training and testing dataset, additional we also change the 2-dimensional to the 3- dimensional array because LSTM takes an input of 3-dimensional array, and later we used flatten layers to change into a 2-dimensional array for output. A comprehensive evaluation of DNN and LSTM networks are used to classify and predict the attacks and compute the precision, recall, and F1 score. We perform binary classification and multiclass classification on the dataset using neural networks and achieve accuracy ranging from 86.70 % to 96.01%.NASUNY Polytechnic InstituteCollege of Engineering, Department of Network and Computer SecurityM
Is Self-Assessment Effective in Enhancing Student Learning?
No full textIt has been argued that self-assessment deepens student learning. This study examined that proposition through online assessment of an assignment in a first year course, with a large percentage (85%) of students enrolled in a distance mode. The aim of the study was to examine the effectiveness of self-assessment in student learning. One hundred and fifty-two students completed a self-assessment of their assignment using assessment guidelines, a marking rubric and model answers. The learning effectiveness of self-assessment was appraised through content analyses of student comments in the self-assessment, and in a survey. In this study, self-assessment of the assignment was found to be effective in enhancing student self-awareness and engaging students in metacognitive processes. Most survey respondents agreed that self-assessment helps students identify the strengths and the weaknesses of assignment answers and highlights areas where performance could be improved. Overall, self-assessment of the assignment was shown to be effective in positively influencing student learning in this learning environment
