Read Codes Research Articles

Can a nation-wide e-cohort of ADHD and ASD in childhood be established using Welsh routinely available datasets?

ObjectivesWe investigated the feasibility and validity of establishing a nationwide e-cohort of individuals with a diagnosis of attention deficit hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) for future longitudinal...

Persistent high prevalence of modifiable cardiovascular risk factors among patients with osteoarthritis in the UK in 1992–2017

ObjectivesTo compare the annual and period prevalence of modifiable cardiovascular risk factors (MCVRFs) between populations with and without osteoarthritis (OA) in the UK over 25 years.Methods215 190 patients aged 35...

Penerapan Metode SAW Untuk Rekomendasi Penentuan Penerimaan Backend Engineer

Determining the acceptance of candidate backend engineers will go through various stages and an assessment process based on certain predetermined criteria or requirements. However, the problem faced at this time is the result of an assessment that has almost the same score weight, close to the same or even exactly same, of course this will make it difficult for the manager concerned to make a decision. Therefore, the implementation of a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method on this problem is one of the right and effective ways. The decision support system created in this study has successfully implemented the SAW method based on candidate backend engineer data which has been processed using 8 criteria, namely Golang, Test Results, Code Readability, Documentation, Unit Tests, Tech Experience, Design System, Code Scalability. And the ranking results have been tested using Spearman Rank correlation calculations and yielded a value of 0.98, which means that the SAW method can be used to determine recommendations for accepting backend engineer candidates

Snippet Comment Generation Based on Code Context Expansion

Code commenting plays an important role in program comprehension. Automatic comment generation helps improve software maintenance efficiency. The code comments to annotate a method mainly include header comments and snippet comments. The header comment aims to describe the functionality of the entire method, thereby providing a general comment at the beginning of the method. The snippet comment appears at multiple code segments in the body of a method, where a code segment is called a code snippet. Both of them help developers quickly understand code semantics, thereby improving code readability and code maintainability. However, existing automatic comment generation models mainly focus more on header comments because there are public datasets to validate the performance. By contrast, it is challenging to collect datasets for snippet comments because it is difficult to determine their scope. Even worse, code snippets are often too short to capture complete syntax and semantic information. To address this challenge, we propose a novel S nippet C omment Gen eration approach called SCGen . First, we utilize the context of the code snippet to expand the syntax and semantic information. Specifically, 600,243 snippet code-comment pairs are collected from 959 Java projects. Then, we capture variables from code snippets and extract variable-related statements from the context. After that, we devise an algorithm to parse and traverse abstract syntax tree (AST) information of code snippets and corresponding context. Finally, SCGen generates snippet comments after inputting the source code snippet and corresponding AST information into a sequence-to-sequence-based model. We conducted extensive experiments on the dataset we collected to evaluate our SCGen . Our approach obtains 18.23 in BLEU-4 metrics, 18.83 in METEOR, and 23.65 in ROUGE-L, which outperforms state-of-the-art comment generation models.

Mmodel: A workflow framework to accelerate the development of experimental simulations.

Simulation has become an essential component of designing and developing scientific experiments. The conventional procedural approach to coding simulations of complex experiments is often error-prone, hard to interpret, and inflexible, making it hard to incorporate changes such as algorithm updates, experimental protocol modifications, and looping over experimental parameters. We present mmodel, a Python framework designed to accelerate the writing of experimental simulation packages. mmodel uses a graph-theory approach to represent the experiment steps and can rewrite its own code to implement modifications, such as adding a loop to vary simulation parameters systematically. The framework aims to avoid duplication of effort, increase code readability and testability, and decrease development time.

Higher rates of non-skeletal complications and greater healthcare needs in achondroplasia compared to the general UK population: a matched cohort study using the CPRD database

BackgroundThe natural history of skeletal complications in achondroplasia (ACH) is well-described. However, it remains unclear how the rates of non-skeletal complications, surgical procedures, healthcare needs and mortality differ between individuals with ACH and the general population. This study aimed to contextualise the extent of these outcomes by comparing event rates across the lifespan, between those with ACH and matched controls in a United Kingdom (UK) population.MethodsThis retrospective, matched cohort study used data from national UK databases: the Clinical Practice Research Database (CPRD) GOLD from primary care, the secondary care Hospital Episode Statistics (HES) databases and the Office of National Statistics mortality records. ACH cases were identified using disorder-specific Read Codes or International Classification of Diseases 10th Revision codes. For each ACH case, up to four age- and sex-matched controls (defined as those without evidence of skeletal/growth disorders) were included. Event rates per 100 person-years were calculated for a pre-defined set of complications (informed by reviews of existing ACH literature and discussion with clinical authors), healthcare visits and mortality. Rate ratios (RRs) with 95% confidence intervals (CIs) were used to compare case and control cohorts.Results541 ACH cases and 2052 controls were identified for the CPRD cohort; of these, 275 cases and 1064 matched controls had linkage to HES data. Approximately twice as many non-skeletal complications were reported among individuals with ACH versus controls (RR [95% CI] 1.80 [1.59–2.03]). Among ACH cases, a U-shaped distribution of complications was observed across age groups, whereby the highest complication rates occurred at < 11 and > 60 years of age. Individuals with ACH had greater needs for medication, GP referrals to specialist care, medical imaging, surgical procedures and healthcare visits versus controls, as well as a mortality rate of almost twice as high.ConclusionsPatients with ACH experience high rates of a range of both skeletal and non-skeletal complications across their lifespan. To manage these complications, individuals with ACH have significantly increased healthcare needs compared to the general population. These results underscore the need for more coordinated and multidisciplinary management of people with ACH to improve health outcomes across the lifespan.

The association between dementia and the risk of hypoglycaemia events among patients with diabetes mellitus: a propensity-score matched cohort analysis.

Hypoglycaemia commonly occurs in patients diagnosed with diabetes mellitus (DM) and dementia. The impact of dementia on hypoglycaemic events is controversial. Thus, we evaluated whether dementia increases the risk of hypoglycaemic events in older patients diagnosed with DM. A retrospective cohort study. We used the IQVIA Medical Research Data (IMRD-UK) database (formerly known as the THIN database). All patients aged ≥55 years and diagnosed with DM who were prescribed at least two prescriptions of antidiabetic medication between 2000 and 2017. Two groups of patients, dementia and non-dementia group, were propensity-score (PS) matched at 1:2. The risk of hypoglycaemia was assessed through a Cox regression analysis. Hypoglycaemic events were determined during the follow-up period by Read codes. From the database, 133,664 diabetic patients were identified, with a mean follow-up of 6.11 years. During the study period, 7,762 diabetic patients diagnosed with dementia were matched with 12,944 diabetic patients who had not been diagnosed with dementia. The PS-matched Cox regression analysis showed that patients diagnosed with dementia were at a 2-fold increased risk for hypoglycaemic events compared with those not diagnosed with dementia (hazard ratio [HR], 2.00; 95% CI, 1.63-2.66). A similar result was shown for a multivariable analysis using all patient data (adjusted HR, 2.25; 95% CI, 2.22-2.32). Our findings suggest that diabetic patients with a diagnosis of dementia have a statistically significant higher risk of experiencing hypoglycaemia.

What you can read is what you can't execute

Due to the address space layout randomization (ASLR), code reuse attacks (CRAs) require memory probes to get available gadgets. Code reading is the basic way to obtain code information. In theory, setting the code to be unreadable can prevent code reading. However, the pages are loaded dynamically, and the existing methods cannot set all code as unreadable at one time. They can only control code permissions page-by-page via time-consuming page tracking. Moreover, since some special users need to read code, turning off the read permission will affect their execution. To solve these problems, this paper proposes a method AntiRead. It rebuilds the buddy system for memory allocation. The new buddy system places code pages in a specific memory pool to manage their read permissions. In the presence of AntiRead, what is obtained by adversaries through code reading is either randomized code or non-executable code. Experiments and analysis show that AntiRead can prevent the code that has been read from being used as gadgets without affecting the normal code reading. In addition, the CPU overhead introduced by AntiRead is 1.8%.

On Using Action Inheritance and Modularity in PDDL Domain Modelling

The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.

Pharmacologically Treated Anxiety and Depression in People Diagnosed with von Willebrand Disease: Matched Cohort Study.

People diagnosed with von Willebrand disease (VWD) have reduced quality of life versus the general population, and there is limited evidence of increased rates of anxiety and/or depression among people diagnosed with VWD. To understand the association between VWD and mental health outcomes. A retrospective cohort study was conducted using the UK Clinical Practice Research Datalink (CPRD) GOLD database (1988-2016). People diagnosed with VWD were matched 1:10 to randomly selected people in the database without VWD based on sex, birth year ±2 years, CPRD record start year ±2 years, and general practice attended. Individuals were followed from VWD diagnosis or match date to censoring (first event date, CPRD end date, or death). Treated anxiety and treated depression were identified by a diagnostic Read Code and a prescription for anxiety/depression medication recorded within 90 days of each other, after VWD diagnosis/match date. Treated anxiety was recorded in 89 of 1119 (8.0%) people diagnosed with VWD and 624 of 10,423 (6.0%) without VWD (age- and sex-adjusted incidence rate ratio [IRR], 1.37; 95% confidence interval [CI], 1.10-1.71). Treated depression was recorded in 119 of 1083 (11.0%) people diagnosed with VWD and 846 of 9845 (8.6%) without VWD (adjusted IRR, 1.35; 95% CI, 1.11-1.63). Females aged 20-39 and 0-19 years were at greatest risk for treated anxiety and treated depression, respectively. Higher rates of treated anxiety and depression were observed among people diagnosed with versus without VWD, predominantly in young females.

Pathways to cancer diagnosis: current state and recommendations.

Diagnosing cancer early is crucial in improving patient outcomes. Primary care networks are encouraged to audit routes to cancer diagnosis, as suggested by the Network Contract Directed Enhanced Service Early Cancer Diagnosis Guidance. We aim to measure how many patients were diagnosed with cancer in the period of April 2021 to March 2022 at an Essex GP practice, and for each of those patients, to ascertain the route of their diagnosis. We also conducted learning event analyses for patients whose diagnoses were not detected through 2-week wait (2WW) or screening. SystmOne Read codes were utilised to identify all patients coded with 'cancer', and 'fast-track cancer referral'. We measured the conversion rate of 2WW referrals to cancer diagnoses. For diagnoses not detected via 2WW or screening, we analysed patient notes for previous consultations and eventual route to diagnosis. In total, 160 2WW referrals were made with a 6.25% conversion rate to cancer diagnoses. In total, 26 patients were diagnosed with cancer. Seventeen patients were diagnosed through 2WW, three through national screening programmes, three through accident and emergency, two through routine referral, and one through incidental finding. For the six patients not diagnosed through 2WW or screening, reasons why included poor patient engagement with healthcare services, referrals requiring chasing, patients passed between specialties, and failure to detect pertinent clinical signs. It is promising that the majority of cancers are diagnosed through 2WW and screening; however, improving patient engagement, streamlining referrals, and thorough clinical examination and documentation will reduce delayed or missed diagnoses.

An data augmentation method for source code summarization

Code comments improve the readability and intelligibility of codes, Unfortunately, code comments are often missing, or outdated in software projects, which negatively affects the efficiency of developers to infer the functionality from source code and affect the efficiency of software maintenance and evolution. To solve this problem, many source code summarization algorithms have been proposed, which automatically generate code comments from source code. However, these methods usually try to collect a large data set which contains the mapping between code comments and source code to train models. However, there are two limitations for the training sets: the insufficient data collection limitation (i.e., generate a large amount of noises-free training data) and data distribution bias limitation (i.e., generate training data for infrequently used methods). To address this issues, we have proposed a data augmentation method for code comments, named CDA-CS. Training models on the augmented dataset, the state-of-the-art algorithms can easily get a further 1.37% to 2.24% improvement in terms of different evaluation metrics (i.e., BLUE-4, METEOR, ROUGH_L).

INVESTIGATING THE CONTRAST OF SURFACE MARKING ON DIFFERENT COLOR CONNECTORS FOR TELECOMMUNICATIONS NEEDS

The development of marking technologies for telecommunications connectors requires increasingly detailed information about their applications. One solution is to use QR codes that contain sufficient information about the connectors' applications. Accurate marking of connectors requires a precise marking system, such as a laser marking system. In this study, a Rofin PowerLine F20 Varia fiber laser was used to mark four different types of ABS plastic connectors in various colors. To achieve optimal marking for all four colors, three experiments were conducted to achieve contrasting marking and high roughness. Easy QR code reading was achieved with an average marking power of 3 W to 4.2 W, a laser marking speed of 300 mm/s to 500 mm/s, and a scanning frequency of 50 kHz to 70 kHz at a constant pulse duration of 8 ns and raster spacing of 50 µm. The microstructural changes and change in roughness were determined using a laser scanning microscope (Olympus OLS5000), which revealed structural changes on the surface and an increase in relative roughness from 39% to 76%. This experiment shows that different parameters of the laser marking mode are required for each color.

Implementation Of The Inter Tk Package, Sub-Process And Os In The Network Management Application Development With Python Programming Language

The development of technology is currently running very rapidly, especially in the field of computer networks that make it possible to connect all people from various places. The need for information triggers the rapid development of network infrastructure technology by several vendors or brands. The need for network infrastructure is of course inseparable from the large number of users who use the internet service, causing new problems because the number of users is not proportional to the number of technicians available. For general users, they can wait for the handling schedule from the technician, while for agencies that need a network to complete their work, they don't have that time. To overcome this, you can use a special program to check the network regularly where everyone can use it so that it can reduce free customer service at network providers. One programming language that can be used open source for the development of these applications is python. Python is a multipurpose interpretive programming language with a design philosophy that focuses on code readability. Python programming is still rarely used because it still uses the terminal as the main access where the user has to type certain code to execute the desired result, such as the Command Prompt Windows (CMD) program. The use of python-based applications can be made more comfortable for users by using a GUI (Graphical user interface) display using the TKInter library, which is a standard Python package for creating GUI displays. Tkinter has an interface to the Tk toolkit that can work as an object-oriented layer on top of Tk. Tkinter has many components that can be used to create user-friendly interfaces. Apart from Tkinter, the application uses a subprocess and os library which functions to access the terminal and execute certain comments in the terminal. The built application has functions for pinging, nslookup, ipconfig, network info, active connection and network processes. Ping and Nslookup require data to be entered in text input on the same line, for ping you can input the IP address of the intended network or website address (requires internet connection) while nslookup can be filled in with the website address.

The burden of COVID‐19 on all‐cause mortality in older adults living in Wales

AbstractBackgroundThe COVID‐19 pandemic has profoundly impacted the lives of people living with dementia (PLWD). Mitigating measures have led to extreme social isolation and reduced or limited capacity within routine health and social care services. Using anonymised individual‐level, population‐scale linked electronic healthcare, demographic and mortality records in Wales, we have examined the impact of the COVID‐19 pandemic on all‐cause mortality in PLWD and in older adults living with other comorbid conditions.MethodUsing the Secure Anonymised Information Linkage (SAIL) Databank (Lyons et al., 2009), we identified six cohorts of individuals aged 50‐101 and living in Wales on or before 1st February 2020, with conditions in the following domains: dementia, cardiovascular, respiratory, metabolic, renal, and cerebrovascular. For each, we identified paired samples matched by age and sex using propensity sampling. Evidence for comorbidities were extracted using ICD‐10 and READ codes. We quantified excess mortality in PLWD during the COVID‐19 period (July 2020 – May 2021 at the point of the analysis) by comparing weekly mortality to a baseline rate (2015‐2019 average) and to the population paired sample. We then extracted retrospective datasets across sixteen‐month periods from 2010‐2020. Finally, we estimated all‐cause mortality odds‐ratios for each period and comorbid domain using logistic regression, controlling for age and sex.ResultPLWD had higher risk of all‐cause mortality compared to a matched sample of individuals without dementia (Figure 1a), especially during the first wave of the pandemic (April 2020, Figure 1b), and in older PLWD (Figure 1c). Examining evidence across other comorbid conditions (Figure 2), logistic regression modelling showed the greatest increase in mortality odds among PLWD (Figure 2f) compared to people without dementia, increasing from 4.47 in 2018 to 5.61 in 2020. The magnitude of the increase in odds among people with cardiovascular, metabolic, renal, and cerebrovascular conditions from 2020‐2021 compared to previous years was smaller compared to the increase in PLWD (Figures 2a, 2c‐e).ConclusionPLWD experienced increased mortality risk compared to those living with other comorbid conditions during 2020. Further work will focus on the composition of death causes and the contribution of other comorbidities to all‐cause mortality among PLWD.

Letter-sound knowledge in Icelandic children at the age 6 years-old

The aim of this study was to examine letter-sound knowledge when children start at school in Iceland. 392 children aged 5–6 years completed assessments of letter-sound knowledge, i.e., the names and sounds of uppercase and lowercase letters of the Icelandic alphabet (uppercase letter-name; uppercase letter-sound; lowercase letter-name; lowercase letter-sound). Whether the child had broken the reading code (could read words) was also recorded. The results revealed no significant difference between girls and boys in the four factors (letter name, letter sound). The results indicated that 56.9 % of the children had broken the reading code when they started school. 58.2 % of the girls and 55.6 % of the boys, not significant difference between the genders. There was a significant difference between the group which had broken the reading code and the group which have not in all the four factors. There was also a high significant correlation between all 4 variables from 0.915 between uppercase letter and lowercase sound to 0.963 between uppercase sounds and uppercase letter.Based on these data, it seems reasonable to advocate learning letter-sound correspondences early in the first year of school to form the best possible basis for breaking the reading code and further reading development.

Enumerator-Arguments as a Language tool for Defining Loops

The new syntactic construction for defining processing loops of collections and series of values in the form of expressions is proposed as part of the development of new programming languages and the improvement of existing languages. Its essence is to use index enumerators as arguments to operators and collection processing functions. Such enumerator-arguments allow you to express operators and functions for processing a slice/entire collection. Translational semantics of enumerator-arguments for indexed and referenced collections is given. A number of examples of using enumerator-arguments for comparison with higher-order functions and list comprehension operators are shown. It is concluded that enumerator-arguments surpass second-order functions in conciseness and readability of the source code, and are not inferior to list comprehensions operators. Further research is aimed at constructing enumerator-arguments of binary trees nodes using a parameter that is expressed as a number. Its binary digits are link ranks and uniquely position a node in the tree.

A graph-based code representation method to improve code readability classification

A graph-based code representation method to improve code readability classification

QR code reading app

QR code reading app

CNN-Based QR Code Reading of Package for Unmanned Aerial Vehicle.

This paper plans to establish a warehouse management system based on an unmanned aerial vehicle (UAV) to scan the QR codes printed on packages. This UAV consists of a positive cross quadcopter drone and a variety of sensors and components, such as flight controllers, single-board computers, optical flow sensors, ultrasonic sensors and cameras, etc. The UAV stabilizes itself by proportional-integral-derivative (PID) control and takes pictures of the package as it reaches ahead of the shelf. Through convolutional neural networks (CNNs), the placement angle of the package can be accurately identified. Some optimization functions are applied to compare system performance. When the angle is 90°, that is, the package is placed normally and correctly, the QR code will be read directly. Otherwise, image processing techniques that include Sobel edge computing, minimum circumscribed rectangle, perspective transformation, and image enhancement is required to assist in reading the QR code. The experimental results showed that the proposed algorithm provided good performance of a recognition rate of 94% for the stochastic gradient descent (SGD) and 95% for Adadelta optimization functions. After that, successful QR code reading was presented.