Types Of Users Research Articles

Comparison of School-Attending Adolescent Areca Nut Users with Tobacco-Only Users and Those Using Both Substances on Demographic Variables and Behavioral Determinants.

Consumption of areca nut and tobacco, often initiated in adolescence, are important causes of oral cancers in India. Areca nut prevention, often subsumed into school tobacco prevention programs, assumes that users are similar. However, differences in gender or age of users could necessitate unique approaches. The study aimed to find if adolescent areca nut-only users are different from tobacco-only users and users of both areca and tobacco. A cross-sectional survey with school-students attending grades 7, 8, 9 was used to compare differences in age, gender, knowledge, and attitudes among areca nut only users, tobacco-only, users of both, and non-users. Of 1909 respondents, 464 (24.3%) used only areca nut, 25 (1.3%) used only tobacco, 177 (9.3%) used both, and 1243 (65.1%) were never-users. Females, overwhelmingly, consumed only areca nut. Users of both substances, in greater proportions, were male, older in age, and more than half believed that tobacco-users had more friends. A third of tobacco-only and users of both substances found it hard to turn down a friend's request to use compared to a fifth of areca-only and non-users. Differences in gender, age, and behavioral determinants such as subjective norms and perceived behavioral control between the different types of users underlines the need for prevention and cessation programs and policies that are specific to and tailored to their unique profiles and needs.

Optimizing Coagulation Profile E-Reporting: A Design Thinking Perspective on Healthcare and Technological Integration

The coagulation profile report is crucial for assessing blood clots and diagnosing various bleeding disorders. Key metrics in these reports include the international normalized ratio (INR), activated partial thromboplastin time (APTT), platelet count, and fibrinogen levels. Traditionally, these reports have been delivered through paper-based methods, which often face significant challenges such as human errors, delays in distribution, and limited accessibility. To address these issues, this preliminary investigation explores integrating technology into the reporting process for coagulation profiles. By leveraging a design-thinking approach, the study aims to understand the needs and preferences of stakeholders and users. This approach includes creating personas to represent different user types, mapping their experiences through empathy and journey maps, and generating and testing ideas through ideation and prototyping. The core objective of the study is to develop a mobile application that simplifies and enhances the reporting process of coagulation profiles. This application is designed to integrate seamlessly with Electronic Medical Record (EMR) systems, providing real-time notifications to healthcare providers when laboratory results are available. The proposed solution aims to improve the timeliness and accuracy of reporting, facilitating better patient care and more efficient workflows. The paper details the components of this solution, including the prototype design and the validation procedures used to ensure its effectiveness. The study seeks to revolutionize how coagulation profiles are documented and communicated in healthcare by adopting a digital reporting system.

Road Fatalities in Children Aged 0-17: Epidemiological Data and Forensic Aspects on a Series of Cases in a Single-Centre in Romania.

Road Traffic Accidents (RTAs) are the leading cause of premature death in young people aged 5-29. Globally, 186,300 children aged 9 years and under die from RTAs each year. Romania had the highest mortality rate in children aged 0 to 14 for 2018-2020. This study aimed to assess the involvement of children aged 0-17 years in fatal RTAs by analyzing medico-legal autopsy records in a 5-year period at Timisoara Institute of Legal Medicine (TILM), Romania. A retrospective analysis of medico-legal autopsy records of road fatalities in children aged 0-17 years, from TILM in a 5-year period (2017-2021), was conducted. Of all medico-legal autopsies in the 5-year period, 23 cases (5.8%) involved road fatalities in children aged 17 and under. Preschoolers accounted for 10 cases, followed by the age group 15-17 years (n = 9). Most children sustained fatal injuries as passengers (n = 13), followed by child pedestrians (n = 7). This research follows four representative cases, each being a different type of child road fatality regarding the type of road user, the age of the victim, and the involvement of other risk factors. Our findings emphasize the tragedy of road fatalities in children and the need to determine risk factors and prevention strategies to reduce the enormous global crisis involving these vulnerable victims.

Non-Intrusive Load Monitoring Based on Dimensionality Reduction and Adapted Spatial Clustering

Non-invasive load monitoring (NILM) deduces changes in energy consumption patterns and operational statuses of electrical equipment from power signals in the feed line. With the emergence of fine-grained power load distribution, the importance of utilizing this technology for implementing demand-side energy management in smart grid development has become increasingly prominent. To address the issue of low load identification accuracy stemming from complex and diverse load types, this paper introduces a NILM method based on uniform manifold approximation and projection (UMAP) reduction and enhanced density-based spatial clustering of applications with noise (DBSCAN). Firstly, this paper combines the characteristics of user load under transient and steady-state conditions and selects data with significant differences to construct a load-characteristic database. Additionally, UMAP is employed to reduce the dimensionality of high-dimensional load features and rebuild a load feature database. Subsequently, DBSCAN is utilized to categorize typical user loads, followed by a correlation analysis with the load-characteristic database to determine the types or classes of loads that involve switching actions. Finally, this paper simulates and analyzes the proposed method using the electricity consumption data of industrial users from the CER–Electricity–Data dataset. It identifies the electricity load data commonly utilized by users in a specific area of Zhejiang Province in China. The experimental results indicate that the accuracy of the proposed non-invasive load identification method reaches 95%. Compared to the wavelet transform, decision tree, and backpropagation network methods, the improvement is approximately 5%.

Development of real-time energy monitoring system using IoT base

This paper aims to develop a real-time energy monitoring system based on smart metering to enhance energy efficiency in the single-phase residential sector. Based on the concept of low-cost IoT devices, this intelligent meter system is designed to monitor household energy consumption. It provides real-time information on a graphical Node-RED Dashboard, making it easy for households to track and manage their energy usage. The hardware of the power metering system included the Node MCU ESP8266, the PZEM-004T, and a cloud server built on the Raspberry Pi for storing electricity consumption data by using Node-RED to connect devices via an application programming interface system. This system can help analyze the electricity consumption behavior in the residential sector. It is a guideline for selecting the electricity rate between the TOD and TOU rates. The results found that in the electrical energy measurements of households 1 and 2, the mean deviations were 0.8758% and 0.5523%, respectively. The electricity cost-saving results when changing the electricity tariff from the TOD rate of households 1 and 2 to the TOU rate. It was found that electricity costs can be saved by 0.2807% and 1.0936%, respectively. The most critical variable is electricity consumption during peak periods. In the case study of household 1, if the electricity consumption during the peak period is less than 13%, it will be appropriate to select the Time of Use rate. In household 2, if there is electricity consumption during the peak period, less than 38% would be appropriate to choose the type of electricity user with a TOU rate.

Contemporary Uses of Vilca (Anadenanthera colubrina var cebil): A Major Ritual Plant in the Andes.

Vilca or cebil (Anadenanthera colubrina var. cebil) is a species known for its psychoactive properties and its widespread use among the pre-Hispanic peoples who inhabited the southern Andean area (southern Peru, Bolivia, northern Chile and northwest Argentina). Studies on this species, as well as on medicinal, psychoactive, or magical plants in general, tend to consider its use in post-Spanish conquest times to be scarce or irrelevant in the Andes of South America. However, based on an in-depth review of the existing literature and on ethnobotanical research conducted in markets in Argentina, Bolivia, and Peru, this paper provides an updated overview affirming the continuity of the use of this species. The results indicate a significant diversity in terms of usage types, plant parts used, treatments, and conditions in which it is applied, along with new records of vernacular names. This paper also offers an interpretation from the perspective of Andean logics, highlighting the current therapeutic effectiveness of the seeds of this plant, facilitated through a series of "movements" that aim to restore the affected person's health.

Path to Net Zero: Understanding the Building Energy Efficiency in Different Climates across Various Building Types

This study analyses the determinants of building energy efficiency in different climate zones and user types. The energy consumption of buildings in different climate zones can be affected by well-known determinants in different ways. So do the buildings with different user types. The primary aim of this study is to investigate how building energy efficiency is determined in five major climate zones and four main property types. This study uses the global building data (Points Achieved dataset) from the Leadership in Energy and Environmental Design (LEED) rating system 2010 to conduct three cross-sectional tests with logit regression models. The results confirm that the determinants of building energy efficiency are the location of the building, adoption of Building Energy Codes (BECs), climate zones, building types, regional economic development level (namely Gross National Income—GNI, Purchasing Power Parity—PPP) and population density. However, the impact of the determinants varies considerably in different climate zones or for different building types. This is the first empirical study exploring building energy efficiency and how it is determined in different climate conditions and user types. The findings are helpful for the stakeholders, such as policymakers, developers, and local authorities, when they hope to implement measures to improve building energy efficiency and the policy/regulation to boost it. Each building requires specific measures that suit its different climate zones or building types to enhance energy efficiency.

A survey on personalized document-level sentiment analysis

Personalized document-level sentiment analysis (PDSA) plays an important role in many real-world applications. So far, various deep learning models for PDSA have been proposed. However, there has been no systematic survey in this area. To address this issue, in this paper, we overview the existing methods of PDSA, and propose a novel two-dimensional PDSA taxonomy. Specifically, in the dimension of attribute usage type, PDSA works are divided into two groups: (1) user-based and (2) user and product-based models. In the dimension of attribute processing method, PDSA works are divided into two groups: (1) feature-based and (2) relation-based models. To fill in the research blank indicated by the taxonomy, we further propose an architecture named User Correlation Mining (UCM) for PDSA. Specifically, UCM contains two components, namely Similar User Cluster Module (SUCM) and Triple Attributes BERT Model (TABM). SUCM is responsible for user clustering, and TABM aims to classify the user’s sentiment based on the information of users, products, user clusters and user reviews. To evaluate the performances of the existing works as well as UCM, we conduct extensive experiments on three real-world datasets. The experiment results show that our proposed architecture UCM outperforms the other state-of-the-art methods.

A novel framework for crash frequency prediction: Geographic support vector regression based on agent-based activity models in Greater Melbourne

The field of spatial analysis in traffic crash studies can often enhance predictive performance by addressing the inherent spatial dependence and heterogeneity in crash data. This research introduces the Geographical Support Vector Regression (GSVR) framework, which incorporates generated distance matrices, to assess spatial variations and evaluate the influence of a wide range of factors, including traffic, infrastructure, socio-demographic, travel demand, and land use, on the incidence of total and fatal-or-serious injury (FSI) crashes across Greater Melbourne’s zones. Utilizing data from the Melbourne Activity-Based Model (MABM), the study examines 50 indicators related to peak hour traffic and various commuting modes, offering a detailed analysis of the multifaceted factors affecting road safety. The study shows that active transportation modes such as walking and cycling emerge as significant indicators, reflecting a disparity in safety that heightens the vulnerability of these road users. In contrast, car commuting, while a consistent factor in crash risks, has a comparatively lower impact, pointing to an inherent imbalance in the road environment. This could be interpreted as an unequal distribution of risk and safety measures among different types of road users, where the infrastructure and policies may not adequately address the needs and vulnerabilities of pedestrians and cyclists compared to those of car drivers. Public transportation generally offers safer travel, yet associated risks near train stations and tram stops in city center areas cannot be overlooked. Tram stops profoundly affect total crashes in these areas, while intersection counts more significantly impact FSI crashes in the broader metropolitan area. The study also uncovers the contrasting roles of land use mix in influencing FSI versus total crashes. The proposed framework presents an approach for dynamically extracting distance matrices of varying sizes tailored to the specific dataset, providing a fresh method to incorporate spatial impacts into the development of machine learning models. Additionally, the framework extends a feature selection technique to enhance machine learning models that typically lack comprehensive feature selection capabilities.

Efficient resource allocation using whale optimization for cell-free massive MIMO networks in 6G HetNet

The increase in data rate demands has driven the development of Cell-Free massive Multiple-Input Multiple-Output (CFmMIMO) technology in 6G Heterogeneous Networks (HetNets). This paper proposes an integration of Unmanned Aerial Vehicles (UAVs) and Device-to-Device (D2D) communication in CFmMIMO, aiming to enhance network capacity, coverage, and service delivery in next-generation wireless networks. The paper investigates uplink transmission in a network where Access Points (APs) have imperfect channel state information. It considers Cell-free User Equipment (CUE), UAVs, and D2D pairs, deriving closed-form uplink achievable rates for each user type. Moreover, two optimization problems are formulated to enhance user data rates: one focuses on maximizing the sum data rate through pilot assignment, while the other aims to achieve weighted max–min power control through power allocation. Furthermore, to address these problem, we propose a Modified Whale Optimization Algorithm (MWOA) and a novel Pilot Assignment based on Whale Optimization Algorithm (PAWOA). Performance studies demonstrate significant improvements over state-of-the-art algorithms.

Correcting misperceptions about very low nicotine cigarettes for cigarette-only smokers, dual/poly smokers, other tobacco users, and non-tobacco users

BackgroundThe U.S. Food and Drug Administration authorized the sale and marketing of two very low nicotine cigarettes (VLNC) as modified risk tobacco products. The misperception that VLNC are healthier than regular cigarettes is common. This study explores effective message strategies to inform the public about health risks associated with VLNC use, encourage cigarette smokers to try VLNC, and prevent other tobacco users and non-users from product initiation. MethodsFollowing the Reasoned Action approach, a VLNC educational message was developed based on the salient beliefs associated with behavioral intention. The message was tested in an online survey conducted in 2018, where 410 participants were randomly assigned to one of the two message conditions (no-message, VLNC message). Message effects were assessed across four tobacco-use groups (non-tobacco users, cigarette-only smokers, cigarette dual/poly smokers, other tobacco users). ResultsCompared to the no-message control, the VLNC message condition showed lower nicotine risk perception for all participants, lower misbelief in VLNC safety for non-users and cigarette-only smokers, higher belief in VLNC carcinogenicity for other tobacco users, stronger belief in second-hand smoke harm for cigarette dual/poly smokers and other tobacco users, and higher VLNC intention for cigarette-only smokers. ConclusionsDifferent messages are needed for different types of tobacco users. Both cigarette smokers and other tobacco users could benefit from messages that acknowledge the non-addictiveness but emphasize the health risks of VLNC. Regulators could consider making physical harm statements a requirement for VLNC packaging and marketing. New strategies need to be explored to inform cigarette dual/poly smokers.

Novel suppressor for damascene copper electrodeposition: Thioether-modified polyether with enhanced adsorption through an adjustable synthesis strategy

The void-free deposition of small-sized and high-aspect ratio interconnect structures requires stronger suppressors than conventional polyethers. In this work, thioether was introduced into polyether to develop novel suppressors with improved adsorption on electrode. The structure of thioether-modified polyether can be easily tailored by choosing proper polyether and thiol compound, thus providing a simple way to regulate electrochemical properties of the suppressor. The electrochemical and copper filling performance related to the molecular structure of novel suppressors were systematically investigated. Thioether-modified polyether, which retains the strong polarizability of typical suppressor and exhibits high resistance to accelerator desorption, can significantly suppress copper deposition on feature sidewalls. This enabled defect-free filling of narrower features at a concentration much lower than the typical usage concentration of suppressor. The modified polyethers with ethylene-propylene-ethylene (EPE) oxide triblock ether chains exhibited higher polarization strength and concentration dependence, facilitating the higher deposition current at the bottom during filling. The length and block ratio of ether chain further influenced the anti-desorption ability of the modified polyether, thereby impacting their suppression on sidewalls, which is crucial in filling process. The convenient structural adjustments for thioether-modified polyether, combined with the derived structure-property relationship, contribute to the development of new suppressors with strong adsorption performance.

Optimizing Customized Bus Lines Considering Users' Transfer Willingness under Cooperative and Competitive Relationship between Metro and Online Car-hailing

In the context of ‘carbon peak’ and ‘carbon neutrality’, coordinating individual travel demand through multi-modal transportation and guiding travelers towards new shared public transportation (PT) modes is increasingly important. In this paper, we analyze the competitive and cooperative relationship between online car-hailing (OCH) services and metro systems in Nanning, China, and conduct aquestionnaire survey among different types of OCH users. A mixed choice model that considers psychological latent variables is constructed to investigate OCH users’ attitudes and cognitions toward customized buses (CBs). An improved adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is proposed to identify potential carpooling station sets, and a hybrid genetic-ant colony algorithm (GACA) is designed to solve bi-level programming model for CB line optimization. Case study results indicate an 83.8% overall transfer rate from OCH users to CBs, with the optimized scheme achieving a 69.68% reduction in carbon emissions.

Rapid implementation of blood culture stewardship: institutional response to an acute national blood culture bottle shortage.

We describe our approach to addressing a nation-wide supply issue for blood culture bottles. Aerobic blood culture bottles received from our distributor July 1-15, 2024 was <1% of typical usage. Through education and ordering restrictions blood culture designed to minimize risk, orders were reduced by 49% over a one-week period.

Aggressive Behavior in the Perspective of Extroverted and Introverted Personality Types of Online Game Users

This study aimed to investigate the relationship between extroverted and introverted personality types and aggressive behaviour in online game users. The research focuses on teenagers who are avid players of the popular online game Player Unknown's Battlegrounds (PUBG). This research method uses a quantitative-descriptive approach with 127 adolescents aged 12-16 years who have played or are playing online games. We took samples based on incidental sampling techniques found in game centers. The results showed that extroverted and introverted personality types contributed to aggressive behaviour in adolescent online game users both partially and simultaneously.

A human centred innovative approach based on persona in hereditary angioedema

BackgroundHereditary Angioedema (HAE) due to C1-inhibitor deficiency (C1INH) is a rare condition, clinically characterised by recurrent swelling. The unpredictability of attacks affects the patients’ quality of life (QoL). HAE patients and their families have vast unmet physical, psychological, and social needs. A human-centred design (HCD) approach to describing the needs of different user types is to utilise personas, a data-driven narrative tool for communicating user archetypes that capture the individuals’ attitudes, goals, and behaviours. The aim of this study was to create and analyse personas based on HAE patients’ and their caregivers’ interviews. Semi-structured interviews were conducted through anthropological conversations with patients, patient-caregivers (double role of patient and caregiver), and non-affected caregivers. Qualitative and quantitative insights from analyses formed the basis to create personas.ResultsWe enrolled 17 subjects: 15 patients (6 of them were patient-caregivers) and 2 non-affected caregivers. The mean age of participants was 50.3 ± 14.4 years. Eight patients were on treatment with prophylactic therapy. The mean percentage score of Angioedema Quality of Life (AE-QoL) for HAE patients was 19.8 ± 12.0. Six personas were identified describing the participants’ personal history, disease management, and needs: four personas referred to patients, one to patient-caregivers, and one non-affected caregiver personas were identified. Across patient personas, the most expressed needs were psychological support and better awareness amongst healthcare professionals. Caregivers, on their side, desired better information about the disease, including the latest therapies, and higher awareness within the community.ConclusionA Human Centred Innovative Approach Based on Persona extends beyond the physical symptoms to encompass the psychological and social aspects of the individual's well-being also including the family in the evaluation.

Using Discrete-Event Simulation to Model Web-Based Crisis Counseling Service Operation: Evaluation Study.

According to the Organisation for Economic Co-operation and Development, its member states experienced worsening mental health during the COVID-19 pandemic, leading to an increase of 60% to 1000% in digital counseling access. Hong Kong, too, witnessed a surge in demand for crisis intervention services during the pandemic, attracting both nonrepeat and repeat service users during the process. As a result of the continuing demand, platforms offering short-term emotional support are facing an efficiency challenge in managing caller responses. This aim of this paper was to assess the queuing performance of a 24-hour text-based web-based crisis counseling platform using a Python-based discrete-event simulation (DES) model. The model evaluates the staff combinations needed to meet demand and informs service priority decisions. It is able to account for unbalanced and overlapping shifts, unequal simultaneous serving capacities among custom worker types, time-dependent user arrivals, and the influence of user type (nonrepeat users vs repeat users) and suicide risk on service durations. Use and queue statistics by user type and staffing conditions were tabulated from past counseling platform database records. After calculating the data distributions, key parameters were incorporated into the DES model to determine the supply-demand equilibrium and identify potential service bottlenecks. An unobserved-components time-series model was fitted to make 30-day forecasts of the arrival rate, with the results piped back to the DES model to estimate the number of workers needed to staff each work shift, as well as the number of repeat service users encountered during a service operation. The results showed a marked increase (from 3401/9202, 36.96% to 5042/9199, 54.81%) in the overall conversion rate after the strategic deployment of human resources according to the values set in the simulations, with an 85% chance of queuing users receiving counseling service within 10 minutes and releasing an extra 39.57% (3631/9175) capacity to serve nonrepeat users at potential risk. By exploiting scientifically informed data models with DES, nonprofit web-based counseling platforms, even those with limited resources, can optimize service capacity strategically to manage service bottlenecks and increase service uptake.

Social and Personal Determinants of Herbal Supplement Use in Metro Cebu, the Philippines

The present study identified herbal supplement usage patterns in Metro Cebu and comprehensively examined consumer education and behavior regarding these supplements. A cross-sectional online survey was conducted from March–July 2023 involving 316 respondents, selected through purposive sampling. The study collected data on demographic characteristics, usage patterns, sources of information, and potential hesitations related to herbal supplement use. Results indicate that the typical Metro Cebu herbal supplement user is more likely to be female, possess higher education, earn above the minimum wage, and primarily reside in Cebu City (n = 202, 63.9%). Usage of herbal supplements is driven by proactive health behaviors often influenced by social networks. Respondents generally hold a positive view of herbal supplement use, particularly those who consume them daily, attributing their preference to natural products, and their perceived cost-effectiveness and potential health benefits compared to conventional medicines. The following subgroups also tend to have more positive views about herbal supplements: [a] older age, [b] employed, [c] at a lower level of education, [d] have known illnesses, and [e] have used the product for 1-5 yr. While respondents actively verify information (n = 243, 76.9%) and inform healthcare providers (n = 180, 57%) about their supplement use, the extent to which they rely on healthcare professionals and scientific sources for guidance in shaping their behavior and product choices is limited. The study underscores the need for enhanced guidance and surveillance from healthcare providers. Furthermore, it highlights a regulatory gap in the governing framework for herbal supplement use and marketing, emphasizing the importance of revisiting or introducing regulations and guidelines to ensure safe and informed consumption practices.

Aggression of electric bike riders in China: comparisons of the Cycling Anger Expression Inventory toward drivers, pedestrians, and other riders

ABSTRACT Electric bikes (e-bikes) account for an unexpected proportion of traffic crash injuries and deaths in China. There is an urgent need to study the factors influencing the aggressive behaviours of e-bike riders and reduce their potential involvement in crashes. In addition, aggression varies when directed at different types of road users, particularly when expressed by vulnerable groups. This study aimed to validate the Cycling Anger Expression Inventory (CAX) for e-bikers and explore whether the expression of aggression in e-bikers differs depending on the recipients, such as drivers, pedestrians, or other riders. The analysis examined the aggression specificity of e-bikers by employing tests of measurement invariance (MI). These findings indicate that adaptive/constructive expression has emerged as a mainstream strategy for managing e-biker anger. E-bikers exhibited the highest levels of aggression toward drivers. These results provide a strong basis for the prevention and intervention of aggression and accidents among Chinese e-bikers.

Flexible blind quantum computation with unnecessarily universal quantum servers

Blind quantum computation (BQC) allows clients with limited quantum capabilities to delegate their tasks to powerful quantum servers and still keep their inputs, algorithms, and outputs private. However, in the noisy intermediate-scale quantum (NISQ) era, quantum computers as servers only control limited number of qubits and are not powerful enough. In addition, each of current BQC models is usually suitable for only one type of users. Therefore, this paper offers a flexible BQC (BQCf for short) model for two types of users with different quantum capabilities where any one of two types of users can complete BQC tasks with the help of the other type of users and quantum servers. To be more specific, we propose two BQCf protocols by using the given model. In the first protocol, one user Alice only with the ability to prepare single-qubit states can realize BQC tasks by cooperating with another user Bob who is just capable of performing single-qubit measurements and a quantum server Charlie. Similarly in the second one, Bob can realize BQC tasks by cooperating with Alice and Charlie. In both protocols, the server Charlie only requires a quantum register of small size and performing CZ gates and thus it is unnecessary to be universal and may be less difficult to realize in the short run. Furthermore, both proposed protocols are verifiable, namely that the user can detect whether the server is honest. Finally, examples of the proposed protocols for implementing Deutsch’s algorithms are simulated through Qiskit framework to show their feasibility and correctness.