Coding System Research Articles

Blood Management System Using Java with GUI and Array List-based Database

This research paper presents the development of a Blood Management System (BMS) using Java with a graphical user interface (GUI), ArrayList as a data structure for managing records, and file handling for persistence. The system provides an efficient and user-friendly platform for blood donation management, focusing on functionalities accessible to an administrative user (admin) only. Key features include donor data management (adding, updating, searching, deleting), stock management of blood groups, and essential application controls like login/logout and exit functionalities. This system aims to streamline the management of blood banks by providing quick access to critical information such as donor location, blood group, and stock availability. The source code for the Blood Management System is accessible at https://github.com/BloodBankManagment.

Abstract 4144555: Atrial Fibrillation Catheter Ablation among Patients with Mediastinal Radiation; Insight from The National Inpatient Database (2015-2020)

Introduction/Background: Radiation therapy (RT) is one of the most common treatment modalities for mediastinal cancers. RT has multiple adverse cardiovascular effects and it has been identified as an independent risk factor for atrial fibrillation (AF). The efficacy of catheter ablation in AF is well established, however there is limited data on procedural safety and outcomes in patients with mediastinal cancers and history of radiation Methods: The National Inpatient Sample (NIS) was analyzed from 2015-2020 to identify admissions for AF catheter ablation among patients with previous history of mediastinal radiation exposure using the 10-PCS (International Classification of Diseases, procedure coding system) codes. Baseline characteristics were compared between the two groups and multivariate logistic regression was used to analyze hospitalization outcomes. Results: We identified 257,240 admissions for AF catheter ablation of which 1720 patients (0.67%) had a history of mediastinal radiation exposure. In the adjusted analysis, the odds of in-hospital mortality (aOR 0.639, 95% CI 0.34-1.20, p 0.1637), major complications (aOR 0.876, 95% CI 0.73-1.05, p 0.1443), any gastrointestinal or hematological complication (aOR 0.853, 95% CI 0.63-1.15, p 0.3017), renal complications (aOR 1.017, 95% CI 0.88-1.18, p 0.0509) were similar in both cohorts. The odds of any cardiovascular complication (aOR 0.825, 95% CI 0.70-0.97, p 0.0208) was lower and odds of any pulmonary complication (aOR 1.433, 95% CI 1.27-1.62, p<.001) was higher in the mediastinal radiation cohort. Conclusion: AF catheter ablation in patients with history of mediastinal radiation is a safe treatment modality. It is not associated with higher in-hospital mortality or cardiac complications in a nationwide registry.

Transfibular Total Ankle Arthroplasty: Clinical, Functional, and Radiographic Outcomes and Complications at a Minimum of 5-Year Follow-up.

The Trabecular Metal Total Ankle Implant differs from other newer-generation implants in the transfibular approach, multiplanar external frame for alignment, tantalum trabecular metal interfaces, curved geometry, and shallow resection depths. The primary aim of this study was to report midterm clinical and radiographic results, as well as survivorship and adverse events at a minimum of 5-year follow-up. A total of 83 ankles (81 patients, average age 60.6 years old, 50.6% females) with average 6.3 years' (range, 5.0-10.1) follow-up were included. Postoperative patient-reported outcome measures (PROMs) included SF-12 physical (PCS) and mental component summary (MCS) scores, Ankle Osteoarthritis Scale (AOS), pain visual analog scale (VAS). Radiographic outcomes included postoperative range of motion (ROM) and coronal/sagittal alignment. Adverse events were reported using the Canadian Orthopaedic Foot and Ankle Society Reoperation Coding System (CROCS). Preoperative tibiotalar coronal deformity included 27 valgus (10 degrees, range 2-20 degrees) and 25 varus ankles (-9 degrees, range -2 to -25 degrees), corrected to neutral postoperatively. Postoperative tibiopedal ROM was 17.8 degrees dorsiflexion and 21.8 degrees plantarflexion. Adverse events occurred at average 28.7 months, most commonly gutter debridement (n = 17, 16.7%) and subsequent operative treatment unrelated to metal components (n = 10, 12.0%). There were 2 cases (2.4%) of acute deep infection treated with irrigation and debridement, polyethylene exchange, and retention of metal components without recurrence of infection. There were no cases of fibular nonunion, septic or aseptic loosening, or implant subsidence. Postoperative PROMS included SF-12 PCS: 40.4; SF-12 MCS: 56.0; VAS: 2.3; AOS Pain: 17.0; and AOS Disability: 24.9. Overall implant survival, defined by retention of the metal components, was 100% at final follow-up. At a minimum of 5 years, patients who underwent TM TAA reported minimal ankle pain and regained neutral ankle alignment and mobility, without septic or aseptic implant loosening. Although having certain limitations, this study suggests that TM TAA is a viable option for the treatment of end-stage ankle arthritis.

Enhanced HS Code Classification for Import and Export Goods via Multiscale Attention and ERNIE-BiLSTM

Accurate classification of import and export goods’ Harmonized System (HS) codes is essential for ensuring tax security. Applying text classification technologies for HS code classification can significantly enhance the prevention and control of customs tax risks. However, the goods text is a semi-structured one that involves multi-domain Chinese professional vocabulary, which poses challenges for current classification models. These models often suffer from inadequate text representation and imprecise feature extraction. To address these challenges, we propose a novel classification model ERNIE-BiLSTM-Channel attention–Spatial attention (EBLCS). This model integrates ERNIE (Enhanced Representation through Knowledge Integration) with a Bidirectional Long Short-Term Memory Network (BiLSTM) and employs multi-scale attention mechanisms. The ERNIE-BiLSTM model provides a more comprehensive and accurate representation of the goods text, effectively capturing the global features of the text. By introducing channel attention and spatial attention mechanisms, greater weights are assigned to important words and word embedding dimensions, significantly enhancing the model’s ability to perceive key information. The experimental results on a customs dataset demonstrate that the EBLCS model consistently outperforms various baseline models across all evaluation metrics, effectively enhancing the performance of HS code classification.

UOWC spatial diversity techniques over hostile maritime environments: an approach under imperfect CSI and per-source power constraints

Optical communication in submarine environments has emerged as a novel technology that enables high bandwidth and high data rate links. However, the unique characteristics of the underwater channel impose new challenges, such as mitigating the remarkable absorption and scattering of hostile maritime environments. For the first time, we consider a per-source optical power constraint based on eye-safety regulations, which has never before been taken into account in Multiple-Input/Single-Output (MISO) systems within underwater optical wireless communication (UOWC) scenarios. Hence, we introduce an innovative spatial repetition coding (SRC) system model, which enables the analysis of an SRC scheme operating under either a per-source or a per-transmitter power constraint. In addition, a tractable generalized transmit laser selection (GTLS) model is presented in order to consider the impact of erroneous selections of the best laser source due to imperfect channel state information (CSI) at the transmitter, prevalent in underwater scenarios with dynamic fluctuations from water currents. Novel bit error rate closed-form expressions and asymptotic results are derived. The presented results demonstrate that an SRC system, when appropriately designed under a per-source power constraint, outperforms the TLS system by effectively mitigating the adverse effects of underwater links. Conversely, in situations where compact transmitters necessitate constraints that significantly modify eye-safety, TLS schemes are superior.

Detecting Autism from Head Movements using Kinesics.

Head movements play a crucial role in social interactions. The quantification of communicative movements such as nodding, shaking, orienting, and backchanneling is significant in behavioral and mental health research. However, automated localization of such head movements within videos remains challenging in computer vision due to their arbitrary start and end times, durations, and frequencies. In this work, we introduce a novel and efficient coding system for head movements, grounded in Birdwhistell's kinesics theory, to automatically identify basic head motion units such as nodding and shaking. Our approach first defines the smallest unit of head movement, termed kine, based on the anatomical constraints of the neck and head. We then quantify the location, magnitude, and duration of kines within each angular component of head movement. Through defining possible combinations of identified kines, we define a higher-level construct, kineme, which corresponds to basic head motion units such as nodding and shaking. We validate the proposed framework by predicting autism spectrum disorder (ASD) diagnosis from video recordings of interacting partners. We show that the multi-scale property of the proposed framework provides a significant advantage, as collapsing behavior across temporal scales reduces performance consistently. Finally, we incorporate another fundamental behavioral modality, namely speech, and show that distinguishing between speaking- and listening-time head movementsments significantly improves ASD classification performance.

Supplemental oxygen prescriptions after hospitalization for coronavirus disease 2019

BackgroundThe role of home oxygen therapy for patients recovering from Coronavirus Disease 2019 (COVID-19) pneumonia, characterized by impaired gas exchange, is not well-defined. ObjectivesTo compare the characteristics, duration, odds of receiving, and continuing to receive home oxygen prescriptions between patients discharged home after COVID-19 pneumonia hospitalization and those discharged after non-COVID-19 pneumonia. MethodsFrom April 2020 to March 2021, 52,951 patients with COVID-19 pneumonia (53.6 % women, 64 % White) were identified, and from January 2019 to December 2019, 26,701 patients with non-COVID pneumonia (53.9 % women, 76.7 % White) were identified, using the Optum Clinformatics Data Mart Database. New oxygen prescriptions were identified through Healthcare Common Procedure Coding Systems codes. Propensity score matching adjusted for confounders, and Cox regression analysis was conducted to compare post-discharge oxygen use. ResultsFollowing hospitalization, oxygen was prescribed to 52,951 patients with COVID-19 pneumonia and 26,701 patients with non-COVID pneumonia in the United States. The COVID-19 pneumonia group were four times more likely to be prescribed supplemental oxygen compared to the non-COVID-19 pneumonia group (OR 4.22; 95 % confidence interval [CI] 3.76–4.74). This trend persisted in sensitivity analyses: ICU patients (OR 4.05; 95 % CI 3.36–4.88) and those who received both ICU admission and mechanical ventilation (OR 3.84; 95 % CI 2.32–6.37). Hispanic patients had the highest likelihood of receiving a supplemental oxygen prescription after discharge (OR 6.75; 95 % CI 5.03–9.05). ConclusionsPost-hospitalization, one in five patients with COVID-19 received prescriptions for supplemental oxygen, which was significantly higher than the proportion of patients with non-COVID-19 pneumonia.

Contribution of transient heat transfer to overpressure protection in a passive Boiling Water Reactor

The BWRX-300 reactor is a small modular reactor with 300 MW nominal electric power output. As the abbreviation indicates, the reactor is a boiling type reactor using water as the coolant. The main operating principle of the reactor model is the use of natural circulation of the coolant for both steady-state operation and emergency cooling of the reactor. Isolation Condenser Systems (ICS) have been used in early BWRs and were reintroduced in the 1990s to implement passive safety.Modern technologies enable effective simulation of objects of various complexity. In this study, the thermal-hydraulic system code TRACE v.5 is used to simulate BWRX-300 reactor plant operation. The software enables calculation of a system consisting of the reactor pressure vessel and ICS in both steady-state and transient operation.The ICS is an emergency cooling system borrowed from the previous generation of GE Hitachi BWRs, the ESBWRs, and it consists of a vertical tube bundle heat exchanger immersed in a water tank. Although this system design remains unchanged, its purpose is different. The BWRX-300 design completely eliminates safety and relief valves. This is why the ICS must perform both overpressure protection and long term heat dissipation functions.Three reactor plant operation states were simulated: normal operation with nominal parameters; reactor isolation; and the transient process into the cooling down mode by reactor shutdown and ICS activation. The results demonstrate that the ICS is capable to mitigate overpressure transients. Upon ICS startup, its metallic structures absorb heat well in excess of its nominal steady-state rating. Initial thermal inertia of the system is important for overpressure mitigation in transients.

Hybrid Window Decoding for Joint Source Channel Anytime Coding System

Hybrid Window Decoding for Joint Source Channel Anytime Coding System

The effectiveness of a sentence-building treatment protocol based on Colorful Semantics

This study investigated the effectiveness of a color-coding system on the sentence-construction skills of a Greek child with Down syndrome. A five-stage single-subject design was implemented, consisting of assessment, baseline, treatment, post-treatment and follow-up phases. The treatment protocol was devised based on the Colorful Semantics program (Bryan, 2003). It focused on the construction of SVO clauses in the context of a picture-description task. The sentence-building process involved the segmentation of the target utterance into its basic syntactic constituents, facilitated by color-coding information of the subject, the verb and the object, and the use of wh- questions. Evidence based on an extensive assessment battery guided the selection and the design of the treatment program. During the baseline, post-treatment and follow-up phases, the child described the same set of action images for comparison purposes, whereas the sentence-coding protocol was introduced and implemented within two 45-minute sessions in a single week. In the baseline session, the child produced a full utterance in response only to 2/16 target pictures. After two treatment sessions, the child was able to describe almost all target pictures using full sentences, while adopting the coding system independently, without the aid of the clinician. Additionally, at 8 weeks post-treatment, the child was still able to describe nearly 50% of the pictures correctly, while using full clauses without the aid of the sentence-coding system. Conclusively, these results not only demonstrate the effectiveness of the designed treatment protocol, but also its efficiency and long-term effects. Given that the protocol was applied to a single participant, findings cannot be generalized without conducting a more extensive investigation.

Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions

Large-scale generative models have enabled the development of AI-powered code completion tools to assist programmers in writing code. Like all AI-powered tools, these code completion tools are not always accurate and can introduce bugs or even security vulnerabilities into code if not properly detected and corrected by a human programmer. One technique that has been proposed and implemented to help programmers locate potential errors is to highlight uncertain tokens. However, little is known about the effectiveness of this technique. Through a mixed-methods study with 30 programmers, we compare three conditions: providing the AI system's code completion alone, highlighting tokens with the lowest likelihood of being generated by the underlying generative model, and highlighting tokens with the highest predicted likelihood of being edited by a programmer. We find that highlighting tokens with the highest predicted likelihood of being edited leads to faster task completion and more targeted edits, and is subjectively preferred by study participants. In contrast, highlighting tokens according to their probability of being generated does not provide any benefit over the baseline with no highlighting. We further explore the design space of how to convey uncertainty in AI-powered code completion tools and find that programmers prefer highlights that are granular, informative, interpretable, and not overwhelming. This work contributes to building an understanding of what uncertainty means for generative models and how to convey it effectively.

On the performance of optical codes for FSO systems using SAC-OCDMA technique to improve system performance

On the performance of optical codes for FSO systems using SAC-OCDMA technique to improve system performance

Digitalising the past decades: automated ICD-10 coding of unstructured free text dermatological diagnoses

BackgroundCurrent digital medical databases record systematically coded diagnoses, but many legacy databases are full of hand-written, free text diagnoses, which can only be meaningfully analysed after mapping them to a coding system. While diagnoses can be extracted from full medical notes with good accuracy, no algorithm using only an unstructured free text diagnosis with no additional data has been published to date.Objectives/methodsTherefore, we sought to create an algorithm which maps hand-written German diagnoses from our clinical photography database to ICD-10 diagnosis codes, validate its output manually by dermatologists and analyse diagnosis counts over time as a proof-of-concept of its application.ResultsOur rule-based algorithm mapped 50,884 unprocessed hand-written German free-text diagnoses covering five decades to ICD-10 codes, while reaching an accuracy of 82% against 817 dermatologist-validated diagnoses. Out of 41,021 data points with the highest algorithm confidence the top 3 identified diagnosis classes were psoriasis, eczema, and non-melanoma skin cancer. The number of ICD-10 codes belonging to chronic inflammatory diseases showed a seasonal pattern with peaks in July, and when analysed aggregated by year, peaks correlated to events such as new therapy classes for these diseases.ConclusionUsing the presented algorithm, it is possible to reliably match hand-written free text of German dermatological diagnoses to ICD-10 codes, thus enabling systematic analysis of legacy databases, making past medical knowledge accessible to today’s patient care.

Zoographics in the Journal of the Experimental Analysis of Behavior: Increasing inclusion of female animals.

We examined the zoographics, or the characteristics of nonhuman animal subjects, reported for the entirety of the Journal of the Experimental Analysis of Behavior (JEAB) through the most recent complete year (1958-2023). Animal sex in particular was evaluated to determine whether the lack of inclusion of female subjects in other disciplines extends to JEAB. Through systematic coding of all nonhuman empirical articles, we found consistent underreporting of most zoographics and a disproportionate use of male subjects relative to female subjects. Additionally, animal sex was commonly unreported and the inclusion of both male and female subjects was sparse. Recent years show some improvement, but greater inclusion is required. Lack of female subjects in research as well as underreporting of zoographics can generate unrepresentative results and hamper replication, generalization, and translation. We provide resources to guide future research and reporting suggestions such as equal inclusion and disaggregation of data by sex. We also clarify misunderstandings about the use of both sexes in research such as beliefs that it necessarily increases the cost of research.

Comparing Italian hospital discharge and mortality data: implications for epidemiological research

Abstract Background In Italy, regional governments maintain data warehouses of linked administrative health data (AHD) linked to demographic information including mortality. Legal reporting pathways for death certificate detail bypass the Region, resulting in significant amounts of missing data on cause and location of death in regional AHD warehouses and limiting epidemiological research on mortality and incidence. In this study, we determine for the first time in Italy the degree of agreement between last hospital diagnosis and primary cause of death, and how that agreement changes over time. Previous studies have found agreement ranging from 40% to 60%. Methods The COV-CVD cohort is comprised of 7.3 million adults aged 30+ from the Lombardy region of northwest Italy, representing all Lombardy residents registered with the health system as of 31 December 2019. Concordance was assessed using the first three characters of the reported cause of death (ICD-10 codes) and primary diagnosis at last hospitalization (converted from ICD-9CM). Results In the COV-CVD cohort there were 401,085 deaths between 1 January 2020 and 23 June 2023. Cause and location of death is missing for 50% and 54% of these deaths, respectively. 60% of deceased individuals had a hospitalization in the year before their death. Agreement between primary diagnosis at last hospitalization and cause of death was 27% overall and 40.5% for deaths in hospital. Missing location of death was reduced from 54% to 26%. Conclusions When using AHD from Italy, primary diagnosis at last hospitalization prior to death is not an appropriate proxy for cause of death, even when the death occurred in hospital. Different coding systems (ICD-10, ICD-9CM) further complicate comparisons and definitions in observational studies. Key messages • In Italy, primary diagnosis at last hospitalization before death is not an appropriate proxy for cause of death. • Poor linkage of mortality and health data limits epidemiological research.

Web-Based Nursing Care Documentation for Students to Support Online Learning

Nursing care is the most critical element in nursing services, which aims to improve the patient’s health status. Ineffective and inefficient care documentation can impact the quality of nursing services. However, the increasingly advanced development of technology provides freedom for the health world to improve the quality of patient-centered services. Educational institutions have also used information technology in learning process activities. As prospective health professionals, students must be equipped with competencies to support their performance. In this study, a web-based nursing care information system was developed to assist students in documenting care activities. The website application was designed to increase student competency in nursing documentation activities to provide high-quality nursing services even though learning is online. The waterfall model approach was used in application design. The design stage started with analyzing application requirements, followed by system design and coding. Next, using a Likert-scale questionnaire, a usability test was performed on 15 beta users to assess the functionality of the application. The results showed that the nursing care website application was easy to use and that students felt satisfied. It is hoped that the website application can be made more attractive by including a decisional support system to make it easier for students to enforce nursing diagnoses on patients.

Machine Learning Approach to Injury Monitoring in Children and Adolescents

Abstract Pediatric injuries are common and associated with individual suffering and costs for the healthcare systems and society. The incidence of injuries among children in Switzerland has so far been insufficiently monitored. Emergency department patient records can be a valuable database to assess medically relevant injuries and gain information for monitoring and evidence-based prevention. The talk will outline our stepwise development of a machine-learning program for a pediatric injury monitoring system and lessons learnt. In this feasibility study we draw on electronic case histories of children treated for injuries between 2018 and 2022 at the University Children’s Hospital Zürich emergency department (N= to 30’884). The ML- approach follows different steps: step 1. utility evaluation of electronic pediatric patient records regarding ML and injury monitoring and prevention requirements in a test-sample of 100 electronic pediatric case histories; step 2. choice/adaptation of coding tree; step 3. coder training and inter-coder reliability testing; step 4. manual annotation of a sub-sample (n 1000) of the electronic pediatric patient records, step 5. design and testing of the ML program in an iterative process, and step 6. performance testing in a random sample of pediatric patient records. First lessons learnt indicate that electronic case history data contain relevant data and fulfill requirements for monitoring and prevention purposes. The IDB coding system proved too complex and detailed for the pediatric data base, providing too few examples for the ML-learning process, and needed to be adapted. Initial data analyses indicate the majority of cases are classified as less severe (73%) and only few (<1%) as very severe but the later provide the most detailed data. ML is a promising approach and makes use of hospital data for a national monitoring of pediatric injuries in Switzerland.

Language Development Opportunities in Curricular and Trade Books: A Content Analysis

ABSTRACTThis content analysis explored children's fictional storybooks and informational science books to determine their differences in high‐quality text features that support oral language (OL) development. We also explored the opportunities for OL development in curricular books compared to trade books. Using systematic coding procedures, we evaluated the genre, vocabulary, syntactic variety, supportive visuals and cultural sensitivity in books from three kindergarten and Grade 1 reading curricula (n = 521) as well as a sample of commercially‐available trade books (n = 48). Descriptive information was averaged to determine the percentage of high‐quality text features included in each book type and genre. Results indicated that informational science trade books offered more opportunities for rich language experiences than their curricular counterparts or any of the fictional books. Thus, there is reason to believe that informational science trade books with high‐quality text features may promote OL development and enhance the learning of young students.

Assessment of the Choked Flow Model of RELAP5 for Application of Inverse Quantification Methods

In the framework of deterministic safety analysis, best estimate plus uncertainty methodologies can provide a more informative detailed analysis of transients than conservative approaches. However, one important step in the application of such methodologies is derivation of uncertainty of the physical models. Probability density functions of the physical model parameters are obtained by applying inverse uncertainty quantification (IUQ) methods to experimental data. The present work deals with evaluation of the experimental database and assessment of the simulation model, which are required steps prior to the application of IUQ methods. The U.S. Nuclear Regulatory Commission system code RELAP5 has been applied for simulation of three experimental databases on choked/critical flow: Sozzi-Sutherland, Super MobyDick, and Marviken Critical Flow Tests. First, the adequacy of the experimental data to the specific target domain is carried out, to then proceed to calibration of the input model parameters by combining the use of Gaussian Process metamodels and optimization schemes. The assessment of the simulation models is performed by evaluating independently accuracy, precision, and consistency through four statistical indicators, including a novel indicator to evaluate the consistency of the results. The final results indicate that the model is capable of reproducing the selected experimental database and overall average accuracy, precision, and consistency below the 10% threshold and can be used for application of IUQ methods.

A Smart QR: Based Library Management System

This research is important since libraries are becoming more technologically advanced. For thousands of people, libraries continue to be the main source of information, even in the age of digital information. This research goal is aimed to provide a smart, easy and user- friendly method for managing library materials using QR code system. Currently, the majority of library management systems need a lot of finance, resources, supervision, and human work. With the implementation of this Quick response (QR) code management system, lots of challenges and efforts is reduced drastically ranging from; money, time, energy and other resources. Users of libraries can access a single application that powers this management system. Users can use the system to issue, return, and manage library materials with little to no help from library staff, thanks to the QR code capability. The developed management system streamlines operations, maintains an audit trail, and increases user accessibility to the library.