Report Files Research Articles

Assaults against health care workers in Sudan: An on-going issue

Background The increasing threat of workplace violence in the health sector in Sudan is a multifactorial problem which displayed lack of trust in doctors and health care workers (HCWs). Objective To study assaults against HCWs employed in Haj Elsafie Teaching Hospital, Khartoum North Sudan. Method An analytical cross-sectional hospital-based study was carried between September 2018 and October 2019. The data was collected through semi-structured questionnaire. Results The prevalence of assaults was 59.6% among 240 participants. Over history females get assaulted most with significant statistical association (p=0.024). Mostly doctors, lab doctors and nurses gone through assault and most of the incidence were happened at medicine department, with a significant statistical association (p=0.038). Verbal assaults were the most frequent among all jobs types, but sexual assault remains high in female. It was found that only 25.8% assault victim filed an official report to the hospital administration. Majority of assault victim explain that they found it unnecessary to report (54.0%), they believed hospital will not take action (30.0%) and assailant will not face any consequences (17.0%). Only, 5.0% disclosed feared from assailant. Conclusion High prevalence of assault incidents among HCWs were found yet official report filing to hospital administration remains low. While poor quality of care was believed to be the main reason for the assault. Training HCWs to deal with patients and teaching them proper communication skills is essential.

Automated HL7v2 LRI informatics framework for streamlining genomics-EHR data integration

While VCF formatted files are the lingua franca of next-generation sequencing, most EHRs do not provide native VCF support. As a result, labs often must send non-structured PDF reports to the EHR. On the other hand, while FHIR adoption is growing, most EHRs support HL7 interoperability standards, particularly those based on the HL7 Version 2 (HL7v2) standard. The HL7 Version 2 genomics component of the HL7 Laboratory Results Interface (HL7v2 LRI) standard specifies a formalism for the structured communication of genomic data from lab to EHR. We previously described an open-source tool (vcf2fhir) that converts VCF files into HL7 FHIR format. In this report, we describe how the utility has been extended to output HL7v2 LRI data that contains both variants and variant annotations (e.g., predicted phenotypes and therapeutic implications). Using this HL7v2 converter, we implemented an automated pipeline for moving structured genomic data from the clinical laboratory to EHR. We developed an open source hl7v2GenomicsExtractor that converts genomic interpretation report files into a series of HL7v2 observations conformant to HL7v2 LRI. We further enhanced the converter to produce output conformant to Epic's genomic import specification and to support alternative input formats. An automated pipeline for pushing standards-based structured genomic data directly into the EHR was successfully implemented, where genetic variant data and the clinical annotations are now both available to be viewed in the EHR through Epic's genomics module. Issues encountered in the development and deployment of the HL7v2 converter primarily revolved around data variability issues, primarily lack of a standardized representation of data elements within various genomic interpretation report files. The technical implementation of a HL7v2 message transformation to feed genomic variant and clinical annotation data into an EHR has been successful. In addition to genetic variant data, the implementation described here releases the valuable asset of clinically relevant genomic annotations provided by labs from static PDFs to calculable, structured data in EHR systems.

The use of the sodium fluorescein and YELLOW 560 nm filter for the resection of pediatric posterior fossa lesions

PurposeThis study aimed to verify the feasibility, safety, and benefit of using fluorescein sodium (FL) and a YELLOW 560 nm filter in posterior fossa tumors in children.MethodsAll cases of pediatric posterior fossa tumors that have undergone surgery using fluorescein (2018–2022) have been included and were examined retrospectively. In those cases where resection of the tumor was planned, a blinded neuroradiologist distinguished gross total resection and subtotal resection according to the postoperative MRI findings. The surgical report and medical files were reviewed regarding the intraoperative staining grade and adverse events. The grade of fluorescent staining of the targeted lesion was assessed as described in the surgical reports. The screening was conducted for any reference to the degree of fluorescent staining: “intense,” “medium,” “slight,” and “no staining.”Results19 cases have been included. In 14 cases, a complete resection was initially intended. In 11 of these cases, a gross total resection could be achieved (78.6%). Staining was described as intense in most cases (58.8%). Except for yellow-colored urine, no side effects obviously related to FL were found throughout the observation period.ConclusionIn combination with a specific filter, FL is a reliable, safe, and feasible tool in posterior fossa surgery in children.

A Cloud-Native Web Application for Assisted Metadata Generation and Retrieval: THESPIAN-NER

Within the context of the Competence Centre for the Conservation of Cultural Heritage (4CH) project, the design and deployment of a platform-as-a-service cloud infrastructure for the first European competence centre of cultural heritage (CH) has begun, and some web services have been integrated into the platform. The first integrated service is the INFN-CHNet web application for FAIR storage of scientific analysis on CH: THESPIAN-Mask. It is based on CIDOC-CRM-compatible ontology and CRMhs, describing the scientific metadata. To ease the process of metadata generation and data injection, another web service has been developed: THESPIAN-NER. It is a tool based on a deep neural network for named entity recognition (NER), enabling users to upload their Italian-written report files and obtain labelled entities. Those entities are used as keywords either to serve as (semi)automatically custom queries for the database, or to fill (part of) the metadata form as a descriptor for the file to be uploaded. The services have been made freely available in the 4CH PaaS cloud platform.

Validation of Natural Language Processing for the Identification of Venous Thromboembolism in Radiologic Reports

Background: Natural Language Processing (NLP) is a software driven method of evaluating information of interest. NLP allows for the rapid identification and distinction between disease states, such as acute and chronic venous thromboembolism (VTE), desirable in large datasets. Methods: The aim of this study was to externally validate the use of NLP algorithms developed and internally validated at Mayo Clinic to identify the presence of acute pulmonary embolism (PE) or acute deep vein thrombosis (DVT) from radiologic reports. A dataset of adults who underwent relevant imaging within 90-days after COVID-19 vaccination between 11/1/2020 and 11/1/2021 was used. Verification was achieved by use of two configuration files for radiologic reports (one with CT reports and one with venous duplex ultrasound reports of the extremities) in conjunction with the open-source software SimpleNLP. The data from the NLP analyses were then compared to a blinded determination if the report showed an acute VTE event performed separately by two individuals (DS, LBK). A random sample of 50 reports determined by the NLP algorithm to be positive and 50 negative reports were reviewed. Results: A total of 3,499 images were identified in patients within 90 days of a COVID-19 vaccination (CT scan, n=2431, ultrasound (n=912, lower extremity =790, upper extremity=122). Of the patients who had a chest CT, 96 were identified by the NLP as positive for acute PE and 2335 as negative. Within the random sample of the radiology reports, 49/50 positive and 50/50 negative scans were confirmed, resulting in 100% sensitivity and 98% specificity. The scan falsely identified with acute PE by the NLP noted "A tiny focus of hypoattenuation ...which could represent a small nodule adjacent to the vessel, although a very tiny pulmonary embolus is possible." Of the patients who underwent US for suspected DVT, 100 were identified as positive. Within the random sample, 49/50 ultrasounds were confirmed positive and 50/50 were confirmed negative for acute DVT resulting in a 100% sensitivity and 98% specificity. The ultrasound that was falsely identified with acute DVT said "No definitive central deep venous thrombus in the right upper extremity. Adjacent to the brachial artery courses a hyperechoic structure with no internal flow. It is possibly though less likely an occlusive thrombus in a paired brachial vein." Conclusion: The PE and DVT NLP algorithms have been externally validated to accurately identify acute VTE and exclude chronic VTE events. Ambiguous imaging results led to limited false positive results. The validated NLP algorithms may provide a more accurate identification of acute VTE than ICD-10 codes and can be used in large datasets.

Rapid and Reliable Data Treatment for the Control of Food Chemical Contaminants by LC-HRMS

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is considered an unavoidable extension of low-resolution LC-MS/MS that stretches the capabilities of multi-residue analysis of chemical contaminants in food. However, LC-HRMS acquisitions generate a massive amount of information available for data processing with supplier software that still miss critical calculation features and adapted reporting tools. Consequently, routine laboratories are still reluctant to switch from LC-MS/MS to LC-HRMS, the latter is still perceived as a cumbersome and demanding technology. In that context, we propose a four-step LC-HRMS workflow to speed-up data processing in situations of multi-residue multi-matrix analysis with the goal to maximize the time spent on data interpretation rather than on data formatting. The first three steps of the workflow imply specific settings on the Orbitrap HRMS associated software (TraceFinderTM) while the fourth step is the novelty i.e. a newly coded R-script capable to translate a raw export file into a comprehensive .xlsx report file in a few seconds. As recommended by various international guidelines and in some official methods, standard addition-based applications are fully embedded in this reporting tool whilst still being the main bottleneck of supplier’s software. The reporting tool also allows appropriate data formatting, filtering, and color-coding options to provide a clear picture of compounds being detected or not, and those requiring specific attention due to unmet quality control criteria as required by European legislation (European Commission SANTE 11312/2021). It is hoped that additional functionalities compatible with R scripts will be soon fully embedded in the supplier’s software for easier data interpretation and reporting.

Analisis Efektivitas dan Efisiensi Pengelolaan Keuangan Desa di Desa Maregam Kecamatan Tidore Selatan Kota Tidore Kepulauan Pada Masa Pandemi Covid-19

This study aims to determine the level of effectiveness and efficiency of Village Fund management in Maregam Village during the Covid-19 Pandemic. This type of research is descriptive quantitative. The data collection technique used in this research is to copy the village budget realization report file. The research method used is descriptive quantitative method using a secondary data analysis approach with nonparametric test equipment using the Wilcoxon Test. The results showed that the level of effectiveness of village financial management based on an average effectiveness ratio of 98.33% was included in the "Effective". Meanwhile, the efficiency level based on the average efficiency ratio is 88.19%, which is included in the "Enough Efficient" category.

Textual Analysis and Future Performance: Evidence From Item 1A and Item 7

Although there is previous research on textual analysis in accounting, little is understood about the effects of the tone and sentiments of the text disclosed in annual report filings (10-K) on the investor assessment of the future performance of the firm. This study inks the tone and sentiments of the text disclosed in the corporate annual reports and expectations regarding the future performance of the firm. We focus on two specific sections of 10-K filings the risk factor disclosures (Item 1A) and the management’s discussion (Item 7) filling a gap in the accounting literature. There are two competing predictions regarding how the tone and sentiments of the text could impact the investor assessment about the future performance of the firm. First, the tone and sentiments of the text in Items 1A and 7 may have an effect on the investor assessment of the future performance of the firm. Second, only the tone and sentiments of Item 7 may have an effect on the investor assessment, given the fact that Item 1A only discusses the general risk factors that are present and not necessarily any specific risk factors to the firm. We find that only the tone and sentiments of the text in Item 7 has an effect on the investor assessment of the firm. This result helps explain the channels through which the tone and sentiments of the text impacts the future performance.

System Monitoring Calibration Oil and Gas Equipment at the Cepu Oil and Gas PPSDM Instrumentation Workshop Using Java Netbeans

Information on calibration reports of oil and gas equipment at the Instrumentation Workshop at the Cepu Oil and Gas Human Resources Development Center (PPSDM Migas) is still not real time, and the filing of reports is still manual in a special cabinet. Often constrained in the process of searching for documents, and confusing information on repair status and recalibration schedule. The purpose of this study was to develop a Calibration Monitoring System for Oil and Gas Equipment at the Instrumentation Workshop at PPSDM Migas Cepu, to facilitate monitoring of the calibration process, search for data, reduce paper usage, and update information on equipment repair status. Research data from calibration reports in 2017 were 113 and in 2018 there were 79 reports. Using UML (Unified Modeling Language) modeling and Java Netbeans programming language. The results of the research are a monitoring system for equipment calibration at the Instrumentation workshop, and it has been tested functionally with blackbox testing, 97% successful in accordance with its function.

R. Chris Davis. Hungarian Religion, Romanian Blood: A Minority’s Struggle for National Belonging, 1920–1945.

R. Chris Davis. <i>Hungarian Religion, Romanian Blood: A Minority’s Struggle for National Belonging, 1920–1945</i>.

ANALISIS DAN STRATEGI MANAJEMEN JEMBATAN PADA SEGMEN JALAN NASIONAL YETTY-UBRUB-YAMBRA-TOWE HITAM

The Yetty-Ubrub-Yambra-Towe Hitam section is one of the important sections in the Papua region because it is the main route to Jayapura which is the capital of Papua Province and this section is included in the national road section. Beside the developing of road pavements, this segment also needs to be supported by the construction and maintenance of bridges. At some points, adequate bridges have been installed. However, at some points it is not sufficient, even the bridge has been badly damaged and the width is only sufficient for one vehicle. This study aims to analyze the bridge management system that has been carried out and then develop a better bridge management strategy for this section. The research location covers the length of the segment and the analytical method used is qualitative analysis. The results indicate that so far the bridge management has not been implemented properly in this section. Therefore, it is necessary to improve the bridge management system that has been carried out. Some things that need to be improved are strategies including implementation time, inspection process, audit staff, reporting, recording of each bridge and filing of reports.

Penerapan Sistem Informasi Manajemen Kredit dan Akuntansi Pada Unit Usaha Kredit BUMDes Catur Eka Amertha

BUMDes Catur Eka Amertha is a business entity owned by Angantaka Village, Abiansemal District, Badung Regency. BUMDes Catur Eka Amertha is the target partner of the team proposing Community Service activities. Partners have problems in the field of credit data management and accounting. Credit data management is important to ensure nominal income generated by credit units. The management system that has been carried out so far has implemented several processes from paper, excel work paper files, and accounting report files. The obstacle experienced is that the resulting information cannot be accessed directly. The constraints on access to information have an impact on the development of business development strategies. The Community Service activities proposer team applies science and technology as a solution to solving problems for partners. In the field of data management, the proposing team designed and built computer-based credit management and accounting information system. Partners are then given training in operating the management information system that has been built. The system has been implemented in the operational process of the credit business unit and has produced credit and accounting reports for BUMDes Catur Eka Amertha. The outputs of Community Service activities are increasing the application of science and technology in the community, the scientific publication of the results of Community Service activities in ISSN journals, and the publication of the results of activities in print or online mass media.

The COPILOT Raw Illumina Genotyping QC Protocol.

The Illumina genotyping microarrays generate data in image format, which is processed by the platform-specific software GenomeStudio, followed by an array of complex bioinformatics analyses that rely on various software, different programming languages, and numerous dependencies to be installed and configured correctly. The entire process can be time-consuming, can lead to reproducibility errors, and can be a daunting task for bioinformaticians. To address this, we introduce the COPILOT protocol, which has been successfully used to transform raw Illumina genotype intensity data into high-quality analysis-ready data on tens of thousands of human patient samples that have been genotyped on a variety of Illumina genotyping arrays. This includes processing both mainstream and custom content genotyping chips with over 4 million markers per sample. The COPILOT QC protocol consists of two distinct tandem procedures to process raw Illumina genotyping data. The first protocol is an up-to-date process to systematically QC raw Illumina microarray genotyping data using the Illumina-specific GenomeStudio software. The second protocol takes the output from the first protocol and further processes the data through the COPILOT (Containerised wOrkflow for Processing ILlumina genOtyping daTa) containerized QC pipeline, to automate an array of complex bioinformatics analyses to improve data quality through a secondary clustering algorithm and to automatically identify typical Genome-Wide Association Study (GWAS) data issues, including gender discrepancies, heterozygosity outliers, related individuals, and population outliers, through ancestry estimation. The data is returned to the user in analysis-ready PLINK binary format and is accompanied by a comprehensive and interactive HTML summary report file which quickly helps the user understand the data and guides the user for further data analyses. The COPILOT protocol and containerized pipeline are also available at https://khp-informatics.github.io/COPILOT/index.html. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing raw Illumina genotyping data using GenomeStudio Basic Protocol 2: COPILOT: A containerised workflow for processing Illumina genotyping data.

Mobilising patients with severe acquired brain injury in intensive care (MAWERIC) – Protocol for a randomised cross-over trial

IntroductionIn the early phase after severe brain injury, patients are often bedridden in an attempt to control intracranial homeostasis; however, prolonged immobilisation may trigger complications. There is limited knowledge about the physiological effects of mobilisation in this early phase. ObjectiveTo investigate changes in brain tissue oxygen tension when patients are mobilised using a Sara Combilizer® in the early phase after severe brain injury, in a randomised cross-over design. MethodsPatients with traumatic brain injury, subarachnoid haemorrhage or intracranial haematoma, will be randomised to early mobilisation or rest (no mobilisation = control) on the first day that the patient is deemed to be fit for mobilisation, and the opposite on the next day. On both days, patients will undergo continuous multimodal monitoring measuring brain tissue oxygen tension (primary outcome), invasive blood pressure, heart rate, middle cerebral artery blood flow velocity by transcranial Doppler ultrasound, intracranial pressure, and microdialysis markers of cerebral oxidative metabolism. DiscussionIntensive care unit patients with acute brain injury are frequently immobilised in the early phase after the ictus. The optimal timing and intensity of mobilisation is unknown. The present study attempts to establish if early mobilisation is safe with respect to intracranial homeostasis.Protocol version 1.1.Date: 19.02.2022.Ethical registration: H-21002728; approved on August 11, 2021.GDPR registration: P-2021 − 105; approved on February 10, 2021.ClinicalTrials.govidentifier:NCT05038930; approved on September 8, 2021.Electronic case report file: REDCap-database; created on August 13, 2021.

Exploration on Data Mining and Application Direction of Land Appraisal Report Filing

Exploration on Data Mining and Application Direction of Land Appraisal Report Filing

Data Mining Software Tools and Methodologies for VLSI Design

Modern VLSI design process employs numerous EDA tools to produce large-size report files. It is time consuming as well as the possibility to miss some violations from EDA report files. We developed two data mining software tools targeting for the timing, noise and power grid analysis report files in one high-performance SOC design project. The software extracts, sorts and displays the key information from EDA report files into HTML forms, which can be viewed by designers using the web browser. Organization of EDA report files, configure files, program execution flows and output HTML forms are described for the developed data mining software tools.

Hertz Rent a Car, Go to Jail

Over 200 lawsuits were filed against the Hertz rental car company by former customers who were arrested as a result of the company’s poor inventory control system and its implementation of two business practices which led to the filing of unsubstantiated stolen car reports with police. According to a whistleblower, these practices essentially meant Hertz was using police “as a repo company and the court system as a collection company” (News Nation 2022, 4:24). Consequences to the individuals who were falsely charged with theft included financial hardship, job loss, reputational damage, child custody problems, the trauma of arrest sometimes at gunpoint, and the traumatic experience of being jailed. This case study calls for students to analyze the company’s actions from the perspectives of ethical theories and decision making, as well as corporate social responsibility.

Domestic Violence Current Legal Status: Psychiatric Evaluation of Victims and Offenders.

Domestic Violence Current Legal Status: Psychiatric Evaluation of Victims and Offenders.

Combining Data Analytics with XBRL: The ViewDrive Case

ABSTRACTThis advisory case is designed to develop data analytics skills using multiple large real-world datasets based on eXtensible Business Reporting Language (XBRL). This case can also be used to introduce students to XBRL concepts such as extension taxonomies. Students are asked to recommend an XBRL preparation software for a hypothetical company (ViewDrive) that is adopting XBRL to satisfy the financial report filing requirements imposed by the Securities and Exchange Commission (SEC). Students perform data-cleansing (extract, transform, load) procedures to prepare large datasets for data analytics. Students are encouraged to think critically, specify assumptions before performing data analytics (using analytic software such as Tableau), and generate visualizations that support their written recommendations. The case is easy to implement, promotes active learning, and has received favorable student and instructor feedback. This case can be used to introduce technology and data analytics topics into the accounting curriculum to help satisfy AACSB's objectives.

CLUSTERING K-MEANS JENIS KATA PADA LAPORAN KEGIATAN KULIAH KERJA NYATA (KKN) UNIVERSITAS LAMPUNG MENGGUNAKAN WORD2VEC

Kuliah Kerja Nyata (KKN) is a form of student service activities for the community, requesting and developing science and technology carried out off-campus within a period, linking work, and special requirements managed by the Badan Pelaksana Kuliah Kerja Nyata (BP-KKN). While carrying out KKN activities, each group of students is required to upload a report of the activities carried out in the village. In uploading the report file, there are several categories in each activity, including socialization, training, and character development. To classify the results of uploading activities one of which can be done using clustering techniques. In this research, a clustering of discussion on KKN student activities will be conducted at the University of Lampung. The text mining method is used to process KKN student activities to be more structured. Information on the KKN student activities was obtained as a feature with the Word2Vec weighting technique. The algorithm used is the K-Mean algorithm which has a high accuracy of the size of the object, so this algorithm is relatively more measurable and efficient for processing large numbers of objects. From the results of research conducted, it has been found that apply the text mining process algorithm for clustering with the K-means method on the Unila KKN Student activity data produces a value of k = 2, a lot of filtered data in the preprocess is 6284 data, using this method has not yet gotten a good association analysis because the results of the second cluster do not show the general types of words, typos and reporting activities by students who are not specifically can affect the results of clustering that is not good.