Past Usage Research Articles

Performance-enhancing drugs attitudes among young amateur Croatian athletes

Abstract Background Recent studies revealed that amateur athletes, especially young ones, have an increasing tendency of performance-enhancing drugs (PEDs) usage. The aim of this study was to explore PEDs attitudes among young, amateur Croatian athletes. Methods This cross-sectional questionnaire study was done in convenient sample of young amateur Croatian athletes during the August 2019 to January 2020 at the occupational and sports medicine office in Eastern Croatia. Performance Enhancement Attitudes Scale (PEAS) was used for evaluation of athletes' attitudes towards doping. Results There were 306 athletes median age 18.0 (interquartile range (IR) 15.0 - 21.0) years; 62.7% females and 37.3% males. According to the age there were 52.9% of adolescents (aged 13 to 18 years) and 47.1% of young adults (aged 19 to 24 years). Regarding the type of sport there were 19.6% of subjects who played individual sports and 80.4% of them who played team sports. Considering the length of sport engagement 49.7% of subjects were engaged in their sport for 1 to 5 years and 50.3% of them were engaged in their sport for 6 or more years. The prevalence of current PEDs usage was 1.3%, while past PEDs usage prevalence was 3.3%. Current PEDs usage was more frequent among young adults (P = 0.048) and athletes playing individual sports (P = 0.001). Athletes who were engaged in sports for 1 to 5 years had more permissive attitudes toward PEDs (P < 0.001) as measured by the PEAS. The study did not establish any correlation between current or past PEDs usage and attitudes toward PEDs. Conclusions PEDs usage is present among young Croatian amateur athletes. There is a need for interventions directed toward the prevention of PEDs usage in an observed subgroup of athletes. Key messages In order to be more effective doping prevention strategies should take into account athletes’ attitudes towards doping. Public awareness and knowledge about doping in sports should be increased in order to achieve more efficient anti-doping programs.

Genetic Hybrid Optimization of a Real Bike Sharing System

In recent years there has been a growing interest in resource sharing systems as one of the possible ways to support sustainability. The use of resource pools, where people can drop a resource to be used by others in a local context, is highly dependent on the distribution of those resources on a map or graph. The optimization of these systems is an NP-Hard problem given its combinatorial nature and the inherent computational load required to simulate the use of a system. Furthermore, it is difficult to determine system overhead or unused resources without building the real system and test it in real conditions. Nevertheless, algorithms based on a candidate solution allow measuring hypothetical situations without the inconvenience of a physical implementation. In particular, this work focuses on obtaining the past usage of bike loan network infrastructures to optimize the station’s capacity distribution. Bike sharing systems are a good model for resource sharing systems since they contain common characteristics, such as capacity, distance, and temporary restrictions, which are present in most geographically distributed resources systems. To achieve this target, we propose a new approach based on evolutionary algorithms whose evaluation function will consider the cost of non-used bike places as well as the additional kilometers users would have to travel in the new distribution. To estimate its value, we will consider the geographical proximity and the trend in the areas to infer the behavior of users. This approach, which improves user satisfaction considering the past usage of the former infrastructure, as far as we know, has not been applied to this type of problem and can be generalized to other resource sharing problems with usage data.

Deep Spatiotemporal Correlation Network Model for Load Prediction in Service Function Chaining

For flexible and elastic management of network function virtualization (NFV)-enabled service function chaining (SFC), the resource demands of virtual network functions (VNFs) need to be predicted appropriately. Even though several prediction schemes have been introduced in the literature, they do not work well in multiple SFC environments. To overcome this limitation, we propose a novel prediction model called the deep spatiotemporal correlation network (DSCN). DSCN learns temporal correlation in the VNF load from the past resource usage patterns. At the same time, DSCN defines upstream/downstream VNF instances across multiple SFCs and learns spatial resource usage patterns by extracting features of them. Evaluation results demonstrate that DSCN can improve the prediction accuracy by up to 13.2% and 10.9% compared to the existing models.

The global burden of vaccine-preventable infectious diseases in children less than 5 years of age: Implications for COVID-19 vaccination. How can we do better?

Background: Infectious diseases are a leading cause of morbidity and mortality worldwide. As of 2018, the total world population of children < 5 years of age was roughly estimated at 679 million. Of these children, an estimated 5.3 million died of all causes in 2018, with an estimated 700,000 who died of vaccine-preventable infectious diseases; 99% of the children who died had lived in low- and middle-income countries. The infectious diseases that remain major causes of mortality for which vaccines have been shown to provide proven preventive success include, in order of prevalence, are those caused by Streptococcus pneumoniae, Rotavirus, Bordetella pertussis, measles virus, Haemophilus influenzae type b and influenza virus. Objective: The purpose of the present report was to address the global burden of these six vaccine-preventable infectious diseases in children < 5 years of age, together with implications for the prevention of coronavirus disease 2019 (COVID-19) infection in children. Methods: The current immunization strategies for the prevention of the six vaccine-preventable infectious diseases in children are reviewed as a framework for new strategies of vaccine prevention of COVID-19 in children. Results: The burden of addressing vaccine prevention of future infectious disease in children can be effectively pursued through knowledge gained from past experiences with vaccine usage in these six vaccine-preventable childhood infectious diseases. Conclusion: Issues with regard to the burden of disease mortality, disease transmission, and available vaccines as well as vaccine successes and shortcomings for specific pathogens can serve as important landmarks for effective use of future vaccines. Although much success has been made globally in preventing these childhood deaths, much remains to be done.

Law Enforcement Pathways to Mental Health: Secondary Traumatic Stress, Social Support, and Social Pressure.

The mental health of law enforcement officers (LEO) is critical to the safety and well-being of the officers and the public they serve. However, LEO face significant on-the-job stressors that undermine mental health, and there is a lot to be learned about when and how LEO seek and enter mental health services. The present study sought to explore variables related to mental health seeking behavior, the role of social engagement and social pressure in the decision to seek mental health services, and the most common pathways into mental health utilized by LEO. A small sample of 86 LEO were recruited from the social media page of a law enforcement nonprofit support organization to take several self-report measures on past mental health service usage and intentions to seek future services, the Inventory of Attitudes Toward Seeking Mental Health Services, the Professional Quality of Life Survey, and a measure of social engagement on mental health topics. Results indicate that while a number of factors are associated with intentions to seek future services, the primary factor in past mental health seeking behavior was secondary traumatic stress. Those who sought mental health services reported higher social engagement and social pressure to seek help. LEO entered mental health services for a variety of reasons and through a variety of provider options, such that no one provider source was preferred. Though the present study was limited by a small sample size, reliance on self-report measures, and occurred during a time of civil unrest that sparked the “defund the police” movement, the results serve as a starting point for understanding the pathways into mental health services for LEO and the roles of secondary trauma and prior mental health service experience.

Frustration-Based Promotions: Field Experiments in Ride-Sharing

The service industry has become increasingly competitive. One of the main drivers for increasing profits and market share is service quality. When consumers encounter a bad experience, or a frustration, they may be tempted to stop using the service. In collaboration with the ride-sharing platform Via, our goal is to understand the benefits of proactively compensating customers who have experienced a frustration. Motivated by historical data, we consider two types of frustrations: long waiting times and long travel times. We design and run three field experiments to investigate how different types of compensation affect the engagement of riders who experienced a frustration. We find that sending proactive compensation to frustrated riders (i) is profitable and boosts their engagement behavior, (ii) works well for long waiting times but not for long travel times, (iii) seems more effective than sending the same offer to nonfrustrated riders, and (iv) has an impact moderated by past usage frequency. We also observe that the best strategy is to send credit for future usage (as opposed to waiving the charge or sending an apologetic message). This paper was accepted by Vishal Gaur, operations management.

Repairing a Cracked Mirror: The Heterogeneous Effect of Personalized Digital Nudges Driven by Misperception

Our study aims to deepen the understanding of personalized digital nudges by evaluating their effects on energy‐saving behavior. We conducted a field experiment with a leading smart metering company in South Korea to investigate whether customers save more energy when a personalized goal and feedback are provided, and how the impacts of nudges vary according to the types of misperception. Specifically, we focused on the behavior of customers who underestimate or overestimate their past electricity usage compared to their actual consumption. We merged daily energy consumption with a pre‐experiment survey for the customers. We found that goal‐setting and feedback mechanisms have a markedly different impact on each type of misperception. Underestimating customers reduced energy consumption only under the “goal‐setting with feedback" treatment. Conversely, overestimating customers reduced energy consumption even under the “goal‐setting without feedback" condition. The underlying mechanism is suggested as updating biased beliefs toward goal achievement. Overall, the results demonstrate that personalized nudges lead to heterogeneous behavioral responses and that service providers and policymakers can use these signals to enrich their planning of behavioral nudges.

Factors Affecting the Long Term Patency of Arteriovenous Access for Hemodialysis

Objective: The objective of the study was to analyze and evaluate the possible factors in the long-term patency of arteriovenous (AV) access for hemodialysis (HD). Materials and Methods: This was a cross-sectional study recruiting patients from January 2019 to December 2019. All patients who have a working HD vascular access, either AV fistula (AVF) or AV graft which has been working for at least 2 years were included and collected demographic data along with other parameters such as timing of creation, interventions, dialysis sessions, and antiplatelet therapy among others. Results: We included 81 patients with AV access patent more than 2 years; 22.5% were aged &gt;65 years, 39.6% were diabetic, 68.5% were hypertensive, and 26.1% had vascular disease. Analysis revealed that the patient factors such as current tobacco usage and side of creation and technical factors such as maturation time, number of dialysis sessions, and single-center dialysis have a significant effect on the patency of the AV access, while the factors such as past tobacco usage, diabetes, hypertension, use of jugular catheter before access creation, and cannulation technique could not establish any statistical effect on the patency of AV access. Conclusion: There is a complex interaction of factors that may affect the patency of an individual AV access. These need to be carefully considered when selecting surgical site or technique, adjuvant treatments, and follow-up protocols for AVFs.

A pilot study of patient satisfaction with a self-completed tablet-based digital questionnaire for collecting the patient\u2019s medical history in an emergency department

BackgroundThe increasing popularity and availability of tablet computers raises questions regarding clinical scenarios. This pilot study examined the patient’s satisfaction when using a tablet-based digital questionnaire as a tool for obtaining medical history in an emergency department and to what extent gender, age, technical competence and mother tongue influence the user satisfaction. Patients were asked to complete three consecutive questionnaires: The first questionnaire collected basic epidemiological data to measure past digital usage behaviour, the second questionnaire collected the patient’s medical history, and the third questionnaire assessed the overall perceived user satisfaction when using the tablet-based survey application for medical anamnesis.ResultsOf 111 consenting patients, 86 completed all three questionnaires. In summary, the user evaluation was positive with 97.7% (n = 84) of the patients stating that they had no major difficulties using the digital questionnaire. Only 8.1% (n = 7) of patients reported a preference to fill out a paper-and-pen version on the next visit instead, while 98.8% (n = 85) stated that they would feel confident filling out a digital questionnaire on the next visit. The variables gender, age, mother tongue and/or technical competence did not exert a statistically significant influence towards the defined scales usability, content and overall impression.ConclusionIn conclusion, self-administered tablet-based questionnaires are widely accepted tools for collecting medical information in the emergency room across all ages and genders, regardless of technical competence.

Acoustic Environment of Urban Historical Places: A Case Study in Kastamonu, Turkey

The general aim of this paper is to demonstrate the significance of the acoustic environment in urban historical places, which represent intangible cultural heritage, and to emphasize the need for the spaces to have their own unique acoustic environment depending on their characteristics. Both sound pressure level measurements and sound classifications were conducted in three urban historical places to emphasize their effect on the character of the area. Based on the data obtained, noise maps were created. The results of the study indicated that there was no change in sound sources due to the similarity of past and present usage types of the three selected historical areas, and that sound sources as an element of cultural heritage in the area were preserved and survived to the present day as a consequence. The type of use, intensity of use, structural-plant density, and climatic change were found to be effective in determining the acoustic environment character. The continuity of sound sources, which are among the elements that constitute the identity in historical places in particular and can be considered as cultural heritage elements, and the harmony of these sound sources for the intended use of the space are the factors that should be taken into account in spatial planning and design.

Provenance-and machine learning-based recommendation of parameter values in scientific workflows.

Scientific Workflows (SWfs) have revolutionized how scientists in various domains of science conduct their experiments. The management of SWfs is performed by complex tools that provide support for workflow composition, monitoring, execution, capturing, and storage of the data generated during execution. In some cases, they also provide components to ease the visualization and analysis of the generated data. During the workflow’s composition phase, programs must be selected to perform the activities defined in the workflow specification. These programs often require additional parameters that serve to adjust the program’s behavior according to the experiment’s goals. Consequently, workflows commonly have many parameters to be manually configured, encompassing even more than one hundred in many cases. Wrongly parameters’ values choosing can lead to crash workflows executions or provide undesired results. As the execution of data- and compute-intensive workflows is commonly performed in a high-performance computing environment e.g., (a cluster, a supercomputer, or a public cloud), an unsuccessful execution configures a waste of time and resources. In this article, we present FReeP—Feature Recommender from Preferences, a parameter value recommendation method that is designed to suggest values for workflow parameters, taking into account past user preferences. FReeP is based on Machine Learning techniques, particularly in Preference Learning. FReeP is composed of three algorithms, where two of them aim at recommending the value for one parameter at a time, and the third makes recommendations for n parameters at once. The experimental results obtained with provenance data from two broadly used workflows showed FReeP usefulness in the recommendation of values for one parameter. Furthermore, the results indicate the potential of FReeP to recommend values for n parameters in scientific workflows.

Association between preconception cannabis use and risk of postpartum depression: Findings from an Australian longitudinal cohort

Background and aimEvidence suggests a positive association between cannabis use and depression however whether preconception cannabis use is associated with postpartum depression (PPD) remains unknown. This study examined the association using a longitudinal design. MethodsParticipants were from the Australian Longitudinal Study on Women’s Health (cohort born in 1989−95), a sample broadly representative of similarly aged Australian women. The association of past year cannabis use at 3–15 months prior to pregnancy with PPD at ages 19–24 to 22–27 was examined in 516 women with 570 singleton live births. The associations of chronicity, recency, and initiation of cannabis use before pregnancy with PPD at ages 21–26 to 24–29 were investigated in 538 women with 590 singleton live births. PPD was ascertained from self-report of doctor diagnosis for each birth. Relative risk (RR) and 95 % confidence interval (CI) were used to calculate the associations of interest. ResultsCompared with no cannabis use, any past-year cannabis use at 3–15 months before pregnancy may be associated with an increased risk of PPD (1.50, 0.99−2.28). Compared with no cannabis use in the first three annual surveys before pregnancy, chronic use (a past year user in ≥ 2 surveys) was associated with an 80 % higher risk of incident PPD for births in the following 1–4 years (1.80, 1.22−2.68). Compared to never users at ages 20–25, former users who had no use within the past year had no increased risk; past year users had 73 % higher risk (1.73, 1.07−2.81); and past year users who initiated cannabis use at or after age 18 had twice the risk of incident PPD for births in the following 1–4 years (2.02, 1.17−3.49). ConclusionThis study provides evidence that preconception cannabis use is associated with increased risk of PPD. More studies are warranted to confirm this finding before cannabis cessation policies can be reinforced on reducing the risk of PPD.

How learning effects influence knowledge contribution in online Q&A community? A social cognitive perspective

Informative contributions are critical for the healthy development of online Q&A communities, which have gained increasing popularity in solving personalized open-ended problems. However, little is known about whether past contribution behaviors and corresponding community feedbacks received affect the characteristics of subsequent contributions. Drawing upon the social cognitive theory, we examine the learning effects on users' knowledge contribution behaviors. Specifically, we focus on two types of learning effects: enactive learning from one's past contribution experience and vicarious learning from observation of others' performances in a question thread. Using a dataset collected from one of the largest online Q&A communities in China, we find that the length feature of past user contributions that garner highly positive feedback, no matter through enactive or vicarious learning, would influence the informativeness of subsequent contributions in the community. These learning effects are more effective for users with higher social status. The enactive learning effect is stronger for contributors with higher social status. For the vicarious learning on higher-status contributors, the influence of high-vote long answers is stronger, but the high-vote short answers show a weaker effect. Our research provides a deeper understanding of knowledge contribution behaviors in online knowledge communities and guides for establishing a healthy knowledge contribution environment.

Drug Planning At Andi Makkasau Hospital In Parepare City

Background: Medicine is a very important element for efforts to improve health, prevention, diagnosis, treatment, and recovery which must be endeavored to always be available when needed. One of the important resources is the supply of medicines, especially in hospitals. The provision of drugs should be in accordance with the amount of treatment needed. If the supply of drugs is not smooth, it will hamper health services. Purpose: to obtain information on drug planning at the Andi Makassau Hospital, Parepare City. Method: the research uses a phenomenological descriptive approach. Data collection was carried out using an interview method conducted at the Andi Makkasau Hospital, Parepare City in August 2019. Results: Information on drug planning at Andi Makkasau Hospital was obtained from interviews with the head of the pharmacy installation, the person in charge of planning and planning staff. Conclusion: Drug planning at the Hospital Pharmacy installation uses the epidemiological method and the consumption method, those involved in the planning method are the pharmacy warehouse, the planning team, the supply division and the head of the installation. Guidelines for drug planning based on DOEN, Hospital Formulary, hospital therapy standards, available budget, remaining inventory, and past period usage

Contract-based Inter-user Usage Coordination in Free-floating Car Sharing

We propose a novel distributed user-car matching method based on a contract between users to mitigate the imbalance problem between vehicle distribution and demand in free-floating car sharing. Previous regulation methods involved an incentive system based on the predictions of origin-destination (OD) demand obtained from past usage history. However, the difficulty these methods have in obtaining accurate data limits their applicability. To overcome this drawback, we introduce contract-based coordination among drop-off and pick-up users in which an auction is conducted for drop-off users' intended drop-off locations. We theoretically analyze the proposed method regarding the upper bound of its efficiency. We also compare it with a baseline method and non-regulation scenario on a free-floating car-sharing simulator. The experimental results show that the proposed method achieves a higher social surplus than the existing method.

An artificial intelligence that increases simulated brain–computer interface performance

Objective. Brain–computer interfaces (BCIs) translate neural activity into control signals for assistive devices in order to help people with motor disabilities communicate effectively. In this work, we introduce a new BCI architecture that improves control of a BCI computer cursor to type on a virtual keyboard. Approach. Our BCI architecture incorporates an external artificial intelligence (AI) that beneficially augments the movement trajectories of the BCI. This AI-BCI leverages past user actions, at both long (100 s of seconds ago) and short (100 s of milliseconds ago) timescales, to modify the BCI’s trajectories. Main results. We tested our AI-BCI in a closed-loop BCI simulator with nine human subjects performing a typing task. We demonstrate that our AI-BCI achieves: (1) categorically higher information communication rates, (2) quicker ballistic movements between targets, (3) improved precision control to ‘dial in’ on targets, and (4) more efficient movement trajectories. We further show that our AI-BCI increases performance across a wide control quality spectrum from poor to proficient control. Significance. This AI-BCI architecture, by increasing BCI performance across all key metrics evaluated, may increase the clinical viability of BCI systems.

Purchasing professionals and the flat-rate bias: Effects of price premiums, past usage, and relational ties on price plan choice

Purchasing professionals arguably choose a price plan that leads to the lowest costs—all else being equal—for their companies when buying services. However, evidence suggests that they prefer flat rates, even where these are more expensive than pay-per-use options. A series of four experiments showed that experienced purchasing professionals tend to exhibit a flat-rate bias in their price plan choices across different business services. The experiments also investigated moderators that intensify or attenuate this bias, which decreased when the flat-rate option was the more expensive alternative but increased with past usage, with upper bound extremes. We also found directional support that the flat-rate bias increases when the buyer-seller relationship is stronger. The experiments also revealed how insurance, convenience, taximeter, overestimation, distrust, and administration effects are related to preferences for flat rates. Beyond their contribution to the pricing literature, these results provide actionable insights for marketing managers and purchasing professionals.

Challenges and opportunities for wearable IoT forensics: TomTom Spark 3 as a case study

Wearable IoT devices like fitness trackers and smartwatches continue to create opportunities and challenges for forensic investigators in the acquisition and analysis of evidential artefacts in scenarios where such devices are a witness to a crime. However, current commercial and traditional forensic tools available to forensic investigators fall short of conducting device extraction and analysis of forensic artefacts from many IoT devices due to their heterogeneous nature. In this paper, we conduct a comprehensive forensic analysis and show artefacts of forensic value from the physical TomTom Spark 3 GPS fitness smartwatch, its companion app installed on an Android smartphone, and Bluetooth event logs located in the app’s metadata. Our forensic methodology and analysis involved the combination and use of a non-forensic tool, a commercial forensic tool, and a non-forensic manufacturer-independent analysis platform tool specifically designed for endurance athletes to identify, extract, analyse, and reconstruct user activity data in an investigative scenario. We show forensic metadata associated with the device information, past user activities, and audio files from the physical smartwatch. We recovered data associated with past user activities stored in proprietary activity files and databases maintained by the app on an Android smartphone. From the event logs, we show when user activity was synced with the app and uploaded to the device cloud storage. The results from our work provide vital references for forensic investigators to aid criminal investigations, highlight limitations of current forensic tools, and for developers of forensic tools an incentive into developing forensic software applications and tools that can decode all relevant data generated by wearable IoT devices.

Historicizing the ideology of ‘the market’

The concept of the market is a linchpin notion in the analysis of contemporary capitalism. This article seeks to question how the term has tended to oscillate between two problematic types of use: either underspecifying the history and politics tied to the concept or, conversely, overloading the notion with a proliferation of too many meanings and applications. As a way to chart an alternative approach which can objectify and critique some of these patterns, this paper re-excavates the notion of ‘the market’ through a historicization of its ideological production and consumption. In particular, the argument brings political economy scholarship into a conversation with theoretical advances in the analysis of ideology, notably Michael Freeden’s so-called ‘morphological approach’. The article illuminates not only past usage patterns but also how the potency of the expression has been refreshed within recent decades associated with neoliberalism. In this way, through a dissection of this master category, the article also aims to contribute to identifying more precisely what is new in the neoliberal ideological ecosystem.

Applications of Satellite Radar Imagery for Hazard Monitoring: Insights from Australia

Earth observation (EO) satellites facilitate hazard monitoring and mapping over large-scale and remote areas. Despite Synthetic Aperture Radar (SAR) satellites being well-documented as a hazard monitoring tool, the uptake of these data is geographically variable, with the Australian continent being one example where the use of SAR data is limited. Consequently, less is known about how these data apply in the Australian context, how they could aid national hazard monitoring and assessment, and what new insights could be gleaned for the benefit of the international disaster risk reduction community. The European Space Agency Sentinel-1 satellite mission now provides the first spatially and temporally complete global SAR dataset and the first opportunity to use these data to systematically assess hazards in new locations. Using the example of Australia, where floods and uncontrolled bushfires, earthquakes, resource extraction (groundwater, mining, hydrocarbons) and geomorphological changes each pose potential risks to communities, we review past usage of EO for hazard monitoring and present a suite of new case studies that demonstrate the potential added benefits of SAR. The outcomes provide a baseline understanding of the potential role of SAR in national hazard monitoring and assessment in an Australian context. Future opportunities to improve national hazard identification will arise from: new SAR sensing capabilities, which for Australia includes a first-ever civilian EO capability, NovaSAR-1; the integration of Sentinel-1 SAR with other EO datasets; and the provision of standardised SAR products via Analysis Ready Data and Open Data Cubes to support operational applications.