Collection System Research Articles

Evaluating the safety of bipolar nephrostomy tract cauterization "BNTC" towards a safe tubeless percutaneous nephrolithotomy: a randomized controlled trial.

To assess the safety and effectiveness of tubed versus tubeless percutaneous nephrolithotomy (PCNL) after tract inspection and bipolar cauterization of the significant bleeders. Patients who were scheduled for PCNL were screened for enrollment in this prospective randomized controlled trial. The patients were randomly assigned to one of two groups; Group 1 received tubeless PCNL with endoscopic inspection of the access tract using bipolar cauterization of the significant bleeders only, while Group 2 had a nephrostomy tube was inserted without tract inspection. We excluded patients with multiple tracts, stone clearance failure, and significant collecting system perforation. We recorded blood loss, hemoglobin drop after 6h, postoperative analgesia requirements, hospital stay, and the need for angioembolization. A total of 110 patients completed the study. There were no significant differences between the two groups in in terms of demographic characteristics. Likewise, there was no significant difference in the mean decrease in hemoglobin after 6h and the frequency of blood transfusion. However, the incidence of hematuria within the first 6h (p = 0.008), postoperative pain scale (p = 0.0001), the rate of analgesia requirement (p = 0.0001) and prolonged hospital stay (p = 0.0001) were significantly higher in Group 2. Only 9 cases of tract screened patients (16% of group 1) required cauterization. Tubeless PCNL with tract inspection and cauterization of bleeders can provide a safer tubeless PCNL with less postoperative pain, analgesia requirement, and same-day discharge.

A systematic benchmarking framework for future assessments of soil health: An example from Denmark

Based on current evidence and established critical thresholds for soil degradation indicators, it is concerning that over 60–70% of European soils are unhealthy due to unsustainable management and the impact of climate change. Despite European and national efforts to improve soil health, significant gaps remain. The proposal for a Soil Monitoring and Resilience Law, to be implemented by the European Union, seeks to establish a framework for soil monitoring and promote sustainable management practices to achieve healthy soils by 2050. This requires extensive data collection and soil monitoring systems to accurately estimate soil health across Europe, considering the diversity of soil types, climates, and land uses. To establish a framework for soil monitoring, we must understand the site-specific status of soil and the ranges of soil health indicators across specific pedoclimatic regions. In our study, we evaluated the soil status in agricultural areas in Denmark using soil health indicators and a site-specific benchmarking approach. We compiled nationally representative datasets, combining point and model-informed data of soil parameters such as organic carbon content, bulk density, pH, electrical conductivity, clay-to-soil organiccarbon ratio, water erosion, and nitrogen leaching. By categorizing Danish agricultural soils into monitoring units based on textural classes, landscape elements, and wetland types, we calculated benchmarks for these indicators, considering different cropping systems. Our approach provided detailed point-based results and a spatially explicit overview of the status of soil health indicators in Denmark. We identified areas where soil deviates from the benchmarks of different indicators. Such deviations might indicate soil functions operating outside the normal range, posing potential threats to soil health. This proposed framework could support the establishment of a baseline for assessing the directionality of future changes in soil health. Moreover, it is adaptable for implementation by other countries to support assessments of soil health.

A qualitative study of clinicians' impressions regarding the implementation of a clinical and research data collection system

AbstractBackgroundSystematically collecting data on clientele databases allows for describing the clientele's needs and addressing various clinical research questions. Conducted in a university psychology clinic, this initiative seeks to improve the overall quality of care provided by integrating evidence‐based practices. This study works to bridge the gap between clinical practice and research.AimsThis study aimed to describe the potential repercussions and clinicians' impressions regarding the implementation of this procedure.Research DesignAn inductive qualitative approach, inspired by Husserl's descriptive phenomenology, was used. To be consistent with this approach, data analysis followed Giorgi's five‐step scientific phenomenological method.Data Collection and AnalysisSemi‐structured individual interviews were conducted with 14 volunteer clinicians using an interview guide. The data were analysed to extract central themes using Giorgi's method, which involves collecting verbal data, reading the data, dividing it into units of meaning, organising the data using the language of the discipline and synthesising the results.ResultsFive central themes emerged: barriers to implementation, potential impacts on therapy, recommendations to enhance participation, perceived utility and an attitude of openness.DiscussionThe pilot project provides valuable insights into the feasibility and acceptability of systematic data collection in a clinical setting. Clinician consultation proves to be essential in the implementation process, highlighting the importance of addressing practical and philosophical obstacles.ConclusionUnderstanding clinicians' experiences can guide future implementations of similar systems and improve clinical practice by supporting the integration of systematic data collection. Enhanced communication and training on the data collection system are suggested.

Rational design of a laminate-structured flexible sensor for human dynamic plantar pressure monitoring

Flexible sensors are essential components in emerging fields such as epidermal electronics, biomedicine, and human-computer interactions, and creating high-performance sensors through simple structural design for practical applications is increasingly needed. Presently, challenges still exist in establishing efficient models of flexible piezoresistive pressure sensors to predict the design required for achieving target performance. This work establishes a theoretical model of a flexible pressure sensor with a simple laminated and enclosed structure. In the modeling, the electrical constriction effect is innovatively introduced to explain the sensitization mechanism of the laminated structure to a broad range of pressures and to predict the sensor performance. The experimental results confirmed the effectiveness of the theoretical model. The sensor exhibited excellent stability for up to three million cycles and superior durability when exposed to salt solution owing to its simple laminated and enclosed structural design. Finally, a wearable sensing system for real-time collection and analysis of plantar pressure is constructed for exercise and rehabilitation monitoring applications. This work aims to provide theoretical guidance for the rapid design and construction of flexible pressure sensors with target performance for practical applications.

Enhancing Patient Outcomes Through Integrated Education and Navigation Programs at the Breast Cancer Comprehensive Center, National Cancer Institute, Cairo University.

Breast cancer remains a significant global health challenge, particularly in low- and middle-income countries where disparities in healthcare exacerbate the disease burden. The Breast Cancer Comprehensive Center at the National Cancer Institute, Cairo University, has implemented integrated patient navigation and education programs aimed at enhancing patient outcomes and healthcare quality.This study evaluated the effectiveness of these programs involving 2202 participants over 12 months. The methodology included systematic data collection, material preparation, and the application of tailored educational strategies to facilitate the patient's journey from diagnosis to treatment. The study utilized three-phased patient navigation assistance to provide comprehensive support.The programs significantly improved patient satisfaction, with over 90% of participants reporting high levels of contentment with the services received. Key improvements included enhanced understanding of breast cancer (including risk factors, symptoms, importance of seeking early care, and treatment options), reduction in patient anxiety, improved treatment adherence, and streamlined diagnostic and treatment processes. Notably, the use of audio-visual educational tools effectively bridged the literacy gap among patients.The integration of patient navigation and education systems at BCCC-NCI has proven to be a highly effective model for improving breast cancer care. This model not only enhances patient understanding and treatment compliance but also facilitates a more efficient healthcare process. The study underscores the potential for replicating this approach in similar healthcare settings globally, suggesting that such integrations can significantly improve cancer care outcomes.

Blockchain-enabled architecture for lead acid battery circularity

Widespread use of lead acid batteries (LABs) is resulting in the generation of million tons of battery waste, globally. LAB waste contains critical and hazardous materials, which have detrimental effects on the environment and human health. In recent times, recycling of the LABs has become efficient but the collection of batteries in developing countries is not efficient, which led to the non-professional treatment and recycling of these batteries in the informal sector. This paper proposes a blockchain-enabled architecture for LAB circularity, which ensures authentic, traceable and transparent system for collection and treatment of batteries. The stakeholders—battery manufacturers, distributors, retailers, users, and validators (governments, domain experts, third party experts, etc.)—are integrated in the circular loop through a blockchain network. A mobile application user interface is provided to all the stakeholders for the ease of adoption. The batteries manufactured and supplied in a geographical region as well as the recycled materials at the battery end-of-life are traced authentically. This architecture is expected to be useful for the battery manufacturers to improve their extended producer responsibility and support responsible consumption and production.

The Technology Evolution and Future Trend of Smart Blackboard

As an important tool for educational digitization, the function of the smart blackboard has gradually evolved from a single teaching information-sharing tool to a smart system for knowledge expression, sharing and generation. Smart blackboard technology has been experienced from chalk + blackboard to projection equipment + blackboard, to interactive electronic whiteboard, and then to today's integrated touch, high-definition display and artificial intelligence technology. The evolution process of the smart blackboard is characterized by interactivity, effectiveness and intelligence. At present, the smart blackboard has become a collection of many advanced technologies. It is gradually integrated into modern technologies such as artificial intelligence, cloud computing, big data analysis and the Internet of Things, making remote collaboration and intelligent classroom management possible. It has become a smart system for big data collection, mining and analysis, evaluation and feedback, and teaching decision-making. Looking forward to the future, the smart blackboard will pay more attention to user experience design, provide an immersive learning experience through Augmented Reality and Virtual Reality technology, and optimize personalized teaching content in combination with machine learning, to lay a foundation for building an intelligent and personalized teaching environment.

Bridging the Gap : Aligning Teachers’ Pedagogical Beliefs with Learners’ Preferences of English Language Learning in The Adaptive Learning Era

This study aims to investigate the differing viewpoints of teachers and students regarding classroom participation, material delivery, teaching media, and assessment methods in the adaptive learning era. The study employs quantitative method, which involves the systematic collection and analysis of numerical data through statistical techniques. This study includes 10 teachers and 50 EFL undergraduate students from two universities in Indonesia, using a Likert scale questionnaire to collect data on various aspects of English language learning. The data were analysed using a t-test to find the mean, standards deviation, and p value of the responses in order to ascertained significant differences between the teachers and the students. The results reveal significant disparities between teachers' and students' perceptions across different dimensions of learning. While teachers prioritize delivery strategies and assessment methods, students focus more on delivery modes and traditional assessment types. However, both groups acknowledge the importance of autonomous learning and the effectiveness of diverse teaching media in enhancing engagement and motivation. The findings underscore the need for a balanced approach to learning that integrates both teacher preferences and student needs. Ultimately, understanding and addressing these discrepancies is essential for promoting meaningful and inclusive educational experiences in the adaptive learning era.

Fatal and non-fatal civilian injuries sustained during law enforcement-reported encounters in California, 2016–2021

BackgroundIn 2015, California passed AB 71 to create a state-wide Use of Force Incident Reporting Database (URSUS) to tabulate law enforcement-reported encounters that resulted in serious bodily injury, death or...

Current type 2 diabetes guidelines: Individualized treatment and how to make the most of metformin.

Evidence-based guidelines provide the premise for the delivery of quality care to preserve health and prevent disabilities and premature death. The systematic gathering of observational, mechanistic and experimental data contributes to the hierarchy of evidence used to guide clinical practice. In the field of diabetes, metformin was discovered more than 100 years ago, and with 60 years of clinical use, it has stood the test of time regarding its value in the prevention and management of type 2 diabetes. Although some guidelines have challenged the role of metformin as the first-line glucose-lowering drug, it is important to point out that the cardiovascular-renal protective effects of sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists were gathered from patients with type 2 diabetes, the majority of whom were treated with metformin. Most national, regional and international guidelines recommend metformin as a foundation therapy with emphasis on avoidance of therapeutic inertia and early attainment of multiple treatment goals. Moreover, real-world evidence has confirmed the glucose-lowering and cardiovascular-renal benefits of metformin accompanied by an extremely low risk of lactic acidosis. In patients with type 2 diabetes and advanced chronic kidney disease (estimated glomerular filtration rate 15-30 mL/min/1.73m2), metformin discontinuation was associated with an increased risk of cardiovascular-renal events compared with metformin persistence. Meanwhile, it is understood that microbiota, nutrients and metformin can interact through the gut-brain-kidney axis to modulate homeostasis of bioactive molecules, systemic inflammation and energy metabolism. While these biological changes contribute to the multisystem effects of metformin, they may also explain the gastrointestinal side effects and vitamin B12 deficiency associated with metformin intolerance. By understanding the interactions between metformin, foods and microbiota, healthcare professionals are in a better position to optimize the use of metformin and mitigate potential side effects. The United Kingdom Prospective Diabetes Study and the Da Qing Diabetes Prevention Program commenced 40 years ago provided the first evidence that type 2 diabetes is preventable and treatable. To drive real-world impact fromthis evidence, payors, practitioners and planners need to co-design and implement an integrated, data-driven, metformin-based programme to detect people with undiagnosed diabetes and prediabetes (intermediate hyperglycaemia), notably impaired glucose tolerance, for early intervention. The systematic data collection will create real-world evidence to bring out the best of metformin and make healthcare sustainable, affordable and accessible.

Glass working and recycling in Pompeii: new evidence from the landfill of the Sarno Baths (VIII 2, 17–23)

Forty-six glass finds, including vessel fragments, windows, one inlay and one indicator of production (moil) excavated in the dump of the Sarno Baths in Pompeii were selected for an interdisciplinary technological, typological and chemical study. The identification of the moil demonstrates that a glassblowing workshop most likely existed in Pompeii, thus putting an end to a long-standing scientific debate. The LA-ICP-MS chemical data show that Roman-Mn base glass predominates, along with few Egyptian natron-type glasses and some plant-ash glass of probable Egyptian origin as well. A large proportion of the analysed glass, including the moil, consists of recycled compositions, suggesting the existence of an efficient system of collection and recycling of glass, which was active even at a time when the city had an abundant supply of fresh glass. The demand for raw glass in Pompeii far exceeded the average demand of other Roman towns, because glass containers were essential for the flourishing perfume industry in Pompeii and Campania. The proximity of the Sarno dump to the perfume district in the south-western part of the city and to the horrea of the Sanctuary of Venus suggests the possible location of the glass workshop in this area.

Smart e-waste management: a revolutionary incentive-driven IoT solution with LPWAN and edge-AI integration for environmental sustainability.

Managing e-waste involves collecting it, extracting valuable metals at low costs, and ensuring environmentally safe disposal. However, monitoring this process has become challenging due to e-waste expansion. With IoT technology like LoRa-LPWAN, pre-collection monitoring becomes more cost-effective. Our paper presents an e-waste collection and recovery system utilizing the LoRa-LPWAN standard, integrating intelligence at the edge and fog layers. The system incentivizes WEEE holders, encouraging participation in the innovative collection process. The city administration oversees this process using innovative trucks, GPS, LoRaWAN, RFID, and BLE technologies. Analysis of IoT performance factors and quantitative assessments (latency and collision probability on LoRa, Sigfox, and NB-IoT) demonstrate the effectiveness of our incentive-driven IoT solution, particularly with LoRa standard and Edge AI integration. Additionally, cost estimates show the advantage of LoRaWAN. Moreover, the proposed IoT-based e-waste management solution promises cost savings, stakeholder trust, and long-term effectiveness through streamlined processes and human resource training. Integration with government databases involves data standardization, API development, security measures, and functionality testing for efficient management.

Smart e-waste management: a revolutionary incentive-driven IoT solution with LPWAN and edge-AI integration for environmental sustainability.

Managing e-waste involves collecting it, extracting valuable metals at low costs, and ensuring environmentally safe disposal. However, monitoring this process has become challenging due to e-waste expansion. With IoT technology like LoRa-LPWAN, pre-collection monitoring becomes more cost-effective. Our paper presents an e-waste collection and recovery system utilizing the LoRa-LPWAN standard, integrating intelligence at the edge and fog layers. The system incentivizes WEEE holders, encouraging participation in the innovative collection process. The city administration oversees this process using innovative trucks, GPS, LoRaWAN, RFID, and BLE technologies. Analysis of IoT performance factors and quantitative assessments (latency and collision probability on LoRa, Sigfox, and NB-IoT) demonstrate the effectiveness of our incentive-driven IoT solution, particularly with LoRa standard and Edge AI integration. Additionally, cost estimates show the advantage of LoRaWAN. Moreover, the proposed IoT-based e-waste management solution promises cost savings, stakeholder trust, and long-term effectiveness through streamlined processes and human resource training. Integration with government databases involves data standardization, API development, security measures, and functionality testing for efficient management.

A Reference Paper Collection System Using Web Scraping

Collecting reference papers from the Internet is one of the most important activities for progressing research and writing papers about their results. Unfortunately, the current process using Google Scholar may not be efficient, since a lot of paper files cannot be accessed directly by the user. Even if they are accessible, their effectiveness needs to be checked manually. In this paper, we propose a reference paper collection system using web scraping to automate paper collections from websites. This system can collect or monitor data from the Internet, which is considered as the environment, using Selenium, a popular web scraping software, as the sensor; this examines the similarity against the search target by comparing the keywords using the Bert model. The Bert model is a deep learning model for natural language processing (NLP) that can understand context by analyzing the relationships between words in a sentence bidirectionally. The Python Flask is adopted at the web application server, where Angular is used for data presentations. For the evaluation, we measured the performance, investigated the accuracy, and asked members of our laboratory to use the proposed method and provide their feedback. Their results confirm the method’s effectiveness.

A collaborative WSN‐IoT‐Animal for large‐scale data collection

AbstractIn recent years, large‐scale data collection systems have developed rapidly in many fields, including agriculture, transport and many others. The internet of things (IoT), whose main platform is wireless sensor networks (WSNs), is behind this development. Comprising thousands of sensors of different kinds, their main purpose is to collect and transmit data. Several data collection techniques have been proposed, including static, mobile and hybrid approaches. The challenges faced by these techniques are considerable, and include energy conservation, planning and trajectory optimisation during data collection, most importantly, the challenges related to the communication between the static sensors generally distributed in a more or less large geographical space and the mobile data collection system (UAV, vehicle, robot etc.). Not to mention the cost, which remains enormous for the agricultural sectors. A hybrid WSN‐IoT‐Animal that is self‐configured to improve data acquisition over large agricultural areas is presented. The main objective and originality of the heterogeneous semi‐modern scheme proposed here oscillating between traditional agriculture and precision agriculture is the use of animals as data collection tools. The main contribution here is the design of a simple and efficient model of data collection that is easily accessible by farmers by adapting the available resources. This model describes and adopts a sensor deployment method based on the notion of the hypergraph, which provides adequate coverage and ensures communication between the mobile sink and a subset of peripheral sensors chosen in alternation. Simulation results verify the effectiveness of the proposed protocol in terms of network lifetime compared to other works. In addition, the amount of data received by the mobile sink demonstrates the importance of this approach in terms of connectivity for large‐scale data collection.

Association between early pregnancy maternal blood pressure and risk of congenital heart disease in offspring

Objective: To analyze the association between maternal blood pressure and congenital heart disease (CHD) in offspring. Methods: From February 2018 to December 2020, pregnant women who participated in the China birth cohort study in Beijing Obstetrics and Gynecology Hospital, Shenzhen Maternal and Child Healthcare Hospital and Chengdu Women's and Children's Central Hospital were enrolled in this study. The baseline and follow-up information were collected using an electronic data collection system. Stepwise logistic regression model was used to analyze the association between maternal blood pressure including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure difference (PP) in the first trimester of pregnancy and the risk of CHD in the offspring. A restrictive cubic spline curve was used to draw the dose-response curve between maternal blood pressure and CHD. Results: A total of 55 552 participants were included in this study. Of them, 31 038, 15 375 and 9 139 pregnant women were enrolled in Beijing Obstetrics and Gynecology Hospital, Shenzhen Maternal & Child Healthcare Hospital and Chendu Women's and Children's Central Hospital, respecitively. The age of pregnant women was (31.3±4.0) and the incidence of CHD in the offspring was 0.78% (435/55 552). Multivariable logistic regression model analysis showed that the increase of SBP (OR=1.01, 95%CI: 1.00-1.02), DBP (OR=1.01, 95%CI: 1.00-1.03) and MAP (OR=1.02, 95%CI: 1.00-1.03) in the first trimester were significantly associated with the risk of CHD in the offspring. The restrictive cubic spline analysis showed a positive linear association of SBP (Ptotal<0.001; Pnon-liear=0.315), DBP (Ptotal<0.001; Pnon-liear=0.928) and MAP (Ptotal<0.001; Pnon-liear=0.929) with the risk of CHD in the offspring. Conclusion: Maternal SBP, DBP and MAP in the first trimester of pregnancy were positively associated with the risk of CHD in the offspring.

Does bilateral Wilms' tumor involving the collecting system in children have a worse prognosis?

The literature on nephron-sparing surgery (NSS) in children with bilateral Wilms' tumors (BWT) involving the collection system is mostly comprised of case reports. The present study aimed to summarize the clinical characteristics, treatments, and prognosis of children with BWT involving the collecting system admitted to our pediatric surgery center compared with those whose tumors did not involve the collecting system. A secondary aim was to discuss how to preserve more kidney parenchyma and prevent long-term renal failure under the premise of preventing tumor recurrence. Patients with BWT admitted to our pediatric surgery center between January 2008 and June 2022 were reviewed. All included patients were grouped according to the relationship between the tumor and collecting system according to the intraoperative findings. Group I included children with tumor infiltrating the collecting system, group II included children with tumor growing into the collecting system, and group III included children whose tumor did not involve the collecting system. The clinical features, treatments and prognosis of the patients were analyzed. Seventy patients were enrolled, including 20 patients with 25 sides of tumors infiltrating the collecting system in group I,10 patients with 13 sides of tumors growing into the collecting system in group II, and 40 patients in group III. There was no significant difference in patients age and gender between group I and group II. In total, 20 patients in group I and 9 patients in group II had partial response (PR) after neoadjuvant chemotherapy. In group I, 22 of 25 sides of tumors underwent NSS; in group II, 11 of 13 sides of tumors underwent NSS. During an average follow-up of 47 months, in group I, 6/20 patients relapsed and 2/20 patients died; in group II, 3/10 patients relapsed and 1/10 patient died. There was no significant difference in 4-year overall survival (OS) rate among groups I, II and III (86.36% vs. 85.71%vs. 91.40%, P = 0.902). To preserve renal parenchyma, NSS is feasible for children with BWT involving the collecting system. There was no significant difference in postoperative long-term OS between patients with BWT involving the collecting system and not involving the collecting system.

Surveillance of Antimicrobial Resistance in the ECOWAS Region: Setting the Scene for Critical Interventions Needed

Antimicrobial resistance poses a significant challenge to public health globally, leading to increased morbidity and mortality. AMR surveillance involves the systematic collection, analysis, and interpretation of data on the occurrence and distribution of AMR in humans, animals, and the environment for action. The West African Health Organization, part of the Economic Community of West African States (ECOWAS), is committed to addressing AMR in the region. This paper examines the status of AMR surveillance in ECOWAS countries using available WHO data from the TrACSS survey and GLASS enrollments. The analysis reveals that while progress has been made, significant challenges remain. Twelve of the fifteen ECOWAS countries are enrolled in GLASS, and ten have developed national action plans (NAPs) for AMR. However, there is a need to ensure all countries fully implement their NAPs, continue reporting to GLASS, and use the data for evidence-based actions and decision making. Surveillance systems for AMR and antimicrobial consumption/use vary across countries with some demonstrating limited capacity. All countries, except Cabo Verde, reported having a reference laboratory for AMR testing. Strengthening laboratory capabilities, data management and use, and multisectoral coordination are crucial for effective AMR surveillance and response. Based on the findings and the regional context, it is essential to prioritize capacity building, data utilization, and the adoption of standardized guidelines for AMR surveillance. Collaboration among ECOWAS countries, the WAHO, and international partners is essential to address AMR comprehensively. Ensuring a consistent supply of essential antimicrobial medications and reagents is vital.

An Intelligent Manufacturing Management System for Enhancing Production in Small-Scale Industries

Industry 4.0 integrates the intelligent networking of machines and processes through advanced information and communication technologies (ICTs). Despite advancements, small mechanical manufacturing enterprises face significant challenges transitioning to ICT-supported Industry 4.0 models due to a lack of technical expertise and infrastructure. These enterprises commonly encounter variable production volumes, differing priorities in customer orders, and diverse production capacities across low-, medium-, and high-level outputs. Frequent issues with machine health, glitches, and major breakdowns further complicate optimizing production scheduling. This paper presents a novel production management approach that harnesses bio-inspired methods alongside Internet of Things (IoT) technology to address these challenges. This comprehensive approach integrates the real-time monitoring and intelligent production order distribution, leveraging advanced LoRa wireless communication technology. The system ensures efficient and concurrent data acquisition from multiple sensors, facilitating accurate and prompt capture, transmission, and storage of machine status data. The experimental results demonstrate significant improvements in data collection time and system responsiveness, enabling the timely detection and resolution of machine failures. Additionally, an enhanced genetic algorithm dynamically allocates tasks based on machine status, effectively reducing production completion time and machine idle time. Case studies in a screw manufacturing facility validate the practical applicability and effectiveness of the proposed system. The seamless integration of the scheduling algorithm with the real-time monitoring subsystem ensures a coordinated and efficient production process, ultimately enhancing productivity and resource utilization. The proposed system’s robustness and efficiency highlight its potential to revolutionize production management in small-scale manufacturing settings.

Identity categories and colonial legacies in the British urban space

ABSTRACT This article advances conceptual debates regarding identity and marginalisation in valuable ways and informs methodological improvements for representation within data collection systems. It discusses findings from a study exploring the inclusion – and exclusion – of identity categories within official data collection exercises. A theme that emerged from the research was how intricacies present within the lived experiences of ethno-linguistic groups can be ignored through the application of broad – and more politically visible – identity categories, such as Muslim. Furthermore, some participants felt that identity categories were discouraged based on colonial legacies and British government priorities for diplomatic relations. One such identity category discussed here is Kashmiri, which despite an ongoing campaign for official recognition, remained absent from the list of ethnic categories used for quantifying populations in the United Kingdom. Furthermore, within the research findings, Somalis and Pashtuns were also highlighted as groups, who despite being recognised as distinct communities within the urban space and thus acknowledged categories of practice in daily interactions within neighbourhoods in the UK, remain ‘unofficial’.