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Herein, a new, direct paper-based fluorimetric method is described for the quantitative determination of glutathione (GSH) molecules in nutritional supplements. Briefly, the proposed analytical method is based on the fluorescence emission resulting from the direct and selective chemical reaction of GSH molecules with the derivatization reagent that is o-phthalaldehyde (OPA) in acidic conditions at room temperature. The intensity of the emitted fluorescence on the surface of the analytical paper devices after irradiation with a lamp at 365 nm is proportional to the concentration of GSH and is measured using a smartphone as the detector. This methodology, which is suitable for measurements in laboratories with limited resources, does not require specialized instrumentation or trained personnel. The protocol governing the proposed method is simple and easily applicable. Essentially, the chemical analyst should adjust the value of pH on the surface of the paper by adding a minimal amount of buffer solution; then, after adding a few microliters of the derivatization reagent, wait for the surface of the paper to dry and, finally, add the analyte. Subsequently, the irradiation of the sensor and the measurement of the emitted fluorescence can be recorded with a mobile phone. In the present study, several parameters affecting the chemical reaction and the emitted fluorescence were optimized, the effect of interfering compounds that may be present in dietary supplements was examined, and the stability of these paper sensors under different storage conditions was evaluated. Additionally, the chemical stability of these paper devices in various maintenance conditions was studied, with satisfactory results. The detection limit calculated as 3.3 S/N was 20.5 μmol L−1, while the precision of the method was satisfactory, ranging from 3.1% (intra-day) to 7.3% (inter-day). Finally, the method was successfully applied to three different samples of dietary supplements. [ABSTRACT FROM AUTHOR]

Hypochlorous acid (HClO), the core bactericidal substance of the human immune system, plays a vital role in many physiological and pathological processes in the human body. In this work, we designed and synthesized a novel deep-red fluorescent probe TCF-ClO for the determination of hypochlorous acid through theoretical analysis. The results showed that probe TCF-ClO exhibited excellent characteristics of long-wavelength emission (635 nm), fast response (< 1 min), and low detection limit (24 nM). In addition, it had been successfully used for imaging of HClO in living HeLa cells. More importantly, the TCF-ClO composited paper-based sensing material was successfully constructed. The RGB/gray value was obtained from a mobile phone and computer, which could achieve the quantitative detection of HClO, with a linear detection range of 0–50 μM and a detection limit of 1.09 μM (RGB mode)/3.38 μM (gray mode). The function of the paper-based sensor extended from qualitative to quantitative detection of HClO, and it is expected to become a portable device widely used in the environmental area. [ABSTRACT FROM AUTHOR]

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence. [ABSTRACT FROM AUTHOR]

Biosensors have emerged as a valuable tool with high specificity and sensitivity for fast and reliable detection of hazardous substances in drinking water. Numerous substances have been addressed using synthetic biology approaches. However, many proposed biosensors are based on living, genetically modified organisms and are therefore limited in shelf life, usability and biosafety. We addressed these issues by the construction of an extensible, cell-free biosensor. Storage is possible through freeze drying on paper. Following the addition of an aqueous sample, a highly efficient cell-free protein synthesis (CFPS) reaction is initiated. Specific allosteric transcription factors modulate the expression of ‘superfolder’ green fluorescent protein (sfGFP) depending on the presence of the substance of interest. The resulting fluorescence intensities are analyzed with a conventional smartphone accompanied by simple and cheap light filters. An ordinary differential equitation (ODE) model of the biosensors was developed, which enabled prediction and optimization of performance. With an optimized cell-free biosensor based on the Shigella flexneri MerR transcriptional activator, detection of 6 μg/L Hg(II) ions in water was achieved. Furthermore, a completely new biosensor for the detection of gamma-hydroxybutyrate (GHB), a substance used as date-rape drug, was established by employing the naturally occurring transcriptional repressor BlcR from Agrobacterium tumefaciens. [ABSTRACT FROM AUTHOR]

The need to complete multiple tasks concurrently is a common occurrence both daily life and in occupational activities, which can often include simultaneous cognitive and physical demands. As one example, there is increasing availability of head-worn display technologies that can be employed when a user is mobile (e.g., while walking). This new method of information presentation may, however, introduce risks of adverse outcomes such as a decrement to gait performance. The goal of this study was thus to quantify the effects of a head-worn display (i.e., smart glasses) on motor variability during gait and to compare these effects with those of other common information displays (i.e., smartphone and paper-based system). Twenty participants completed four walking conditions, as a single task and in three dual-task conditions (three information displays). In the dual-task conditions, the information display was used to present several cognitive tasks. Three different measures were used to quantify variability in gait parameters for each walking condition (using the cycle-to-cycle standard deviation, sample entropy, and the “goal-equivalent manifold” approach). Our results indicated that participants used less adaptable gait strategies in dual-task walking using the paper-based system and smartphone conditions compared with single-task walking. Gait performance, however, was less affected during dual-task walking with the smart glasses. We conclude that the risk of an adverse gait event (e.g., a fall) in head-down walking conditions (i.e., the paper-based system and smartphone conditions) were higher than in single-task walking, and that head-worn displays might help reduce the risk of such events during dual-task gait conditions. [ABSTRACT FROM AUTHOR]

Introduction: Data collection using paper-based questionnaires can be time consuming and return errors affect data accuracy, completeness, and information quality in health surveys. We compared smartphone and paper-based data collection systems in the Burden of Obstructive Lung Disease (BOLD) study in rural Sudan. Methods: This exploratory pilot study was designed to run in parallel with the cross-sectional household survey. The Open Data Kit was used to programme questionnaires in Arabic into smartphones. We included 100 study participants (83% women; median age = 41.5 ± 16.4 years) from the BOLD study from 3 rural villages in East-Gezira and Kamleen localities of Gezira state, Sudan. Questionnaire data were collected using smartphone and paper-based technologies simultaneously. We used Kappa statistics and inter-rater class coefficient to test agreement between the two methods. Results: Symptoms reported included cough (24%), phlegm (15%), wheezing (17%), and shortness of breath (18%). One in five were or had been cigarette smokers. The two data collection methods varied between perfect to slight agreement across the 204 variables evaluated (Kappa varied between 1.00 and 0.02 and inter-rater coefficient between 1.00 and -0.12). Errors were most commonly seen with paper questionnaires (83% of errors seen) vs smartphones (17% of errors seen) administered questionnaires with questions with complex skip-patterns being a major source of errors in paper questionnaires. Automated checks and validations in smartphone-administered questionnaires avoided skip-pattern related errors. Incomplete and inconsistent records were more likely seen on paper questionnaires. Conclusion: Compared to paper-based data collection, smartphone technology worked well for data collection in the study, which was conducted in a challenging rural environment in Sudan. This approach provided timely, quality data with fewer errors and inconsistencies compared to paper-based data collection. We recommend this method for future BOLD studies and other population-based studies in similar settings. [ABSTRACT FROM AUTHOR]

Objective As society becomes more interconnected with technology, it is important to examine how traditional "paper and pencil" administered neuropsychological tests can be utilized in digital electronic forms (e.g. computers, touch screen tablets, and smartphones). Literature has shown somewhat mixed outcomes for the validity of computerized tests. Gathering data electronically has been found to reduce human error in both test administration and in data collection itself. Digitizing carries benefits in the research field where electronic administration may make it possible to gather data on a larger scale numerically and geographically. However, in some conversions to digital versions of a task, changes may be made to the stimuli and procedure that might seemingly be benign, but could activate different cognitive responses, potentially compromising construct validity. This study examined the comparability of paper and electronic forms of the Stroop task, which is used widely and has been previously validated in paper form. Method Electronic Stroop tests were examined for concurrent validity with a paper version. Two touch-screen based apps were examined: BrainBaseline for the iPad and EncephalApp for smartphone. Young and older adults (n = 58) completed paper and an electronic version of the Stroop. Results Correlation analyses revealed a significant, but modest relationship between paper Stroop and the BrainBaseline version (r =.54; p =.001), while the EncephalApp correlation was non-significant (r =.44; p =.18). Conclusions These results need to be verified in a larger sample, but the implication is that some paper and electronic versions of cognitive tests are not necessarily interchangeable, and caution should be used. [ABSTRACT FROM AUTHOR]

The aim of the paper is to define activities performed by car (vehicle) drivers while waiting at traffic lights in city areas and how frequent they are. Some of these activities could be a factor leading to possible traffic accident. The research is based on the sample of 17,088 surveyed vehicles. Data were collected on 67 streets in 5 cities in the Czech Republic (Praha, Brno, Pardubice, Olomouc, Frýdek-Místek) from IV/2022 to VI/2023. The way of survey is manual data collection. There are defined and assessed 7 groups of activities - following traffic situation; cellular phone; (vehicle) control elements; talking to other people in a vehicle; paper documents; drinking+eating+smoking; and dressing-up. The modified SWOT analysis is applied in process of definition of these groups of activities. All these activity groups and their impacts on vehicle driving are discussed in the paper. The data collected are assessed in transport technology as well as statistics points of view. Means of descriptive statistics and χ² Goodness-of-Fit test are applied. Data are compared by city as well as by direction of drive (towards/outwards or around the city centre). The relation to the distance from the city centre is assessed in the case of Prague. Differences by drivers leaving residential areas and shopping centres are discussed, as well as the impact of tram transport. The main result is that ca. 65% of drivers still follow traffic while waiting at traffic lights. Talking to others in vehicle is recorded by 14% of drivers. Vehicle control elements are manipulated by 4%. The remaining 17% of drivers perform other (and may be riskier) activities - cellular phone 8%; drinking+eating+smoking 6%; dressing-up 2%; and paper documents 1%. From a transport technology point of view, this structure should be considered as representative. Relationships to some of the facts mentioned were recorded, but they are seen to be not so significant. The increased frequency of 'drinking+eating+smoking' and 'dressing-up' activities by leaving shopping centres can be pointed out as an example. The paper is extended by comparison between stated (in on-line survey) and revealed (on-site) preferences, with the result that people are open to allow also activities which can be problem in the point of safety (e.g. cellular phone). The paper is concluded with suggestions. First is statement, that the ergonomics of vehicles that reduce the demands on attention by performing such activities is helpful. The second suggestion is to mark specific parking places for short stops in city areas. Both suggestions are based on the fact, that ca. 21% of drivers perform activities reducing attention, and it is illusory that these activities should be totally replaced by their prohibition. It is necessary to give them the opportunity to manage these activities more safely than by waiting at traffic lights. The paper presents results of activities of students at internships between the Palacký University Olomouc and the University of Pardubice. [ABSTRACT FROM AUTHOR]

The continuing increase of the popularity of mobile phones generates a large volume of waste mobile phones. The efficient collection of this waste has become a focus and frontier of both academic research and related business. This paper reviews the waste mobile phone collection in Dalian, China. The findings show that several challenges currently impede the implementation of collection, including unsmooth collection channels, poor convenience, and low environmental awareness of residents. A new joint collection mode is put forward to increase the waste mobile phone collection rate. In the mode, the responsibilities of each stakeholder (including the collecting enterprise, the third-party logistics company, the government, and the resident) are clarified. Moreover, a conjoint analysis method is applied to identify residents' willingness for collection. The obtained results show that compensation mode, collection price, and convenience degree are the three factors that influence the prevailing preferences of residents. Collection services with high market share must satisfy the concourse of three conditions. The collection price exceeds 30% of the mobile phone's original price, the compensation mode is cash and information service is provided. These results can provide a reference for the service design of collection mode and the formulation of relevant corporate strategies. • Waste mobile phones are an environmental problem if not handled appropriately. • Collection is the critical bottleneck of waste mobile phones managements. • A new joint collection mode aiming at increasing collection rate was put forward. • Conjoint analysis was applied to investigate residents' willingness for collection. [ABSTRACT FROM AUTHOR]

Abstract: Paper and traditional books have been serving as useful tools in supporting knowledge-intensive tasks and school learning. Although learning strategies such as selective verbatim note-taking or question-asking may foster intentional recall or resolve comprehension difficulties in paper-based learning practice, improvement in learning may depend on the opportunity and quality of which students apply note-taking, review notes, or enhance comprehension through questioning. This study aims to complement a paper textbook with a mobile phone and to treat the combination as a whole to facilitate verbatim note-taking, resolving comprehension questions, and receiving reading recommendations. The textbook paragraphs were augmented with line numbers to facilitate coordination between the mobile phone and the paper textbook. An eight-week comparative study was conducted to explore the use of two reading vehicles. The results and findings show that using a mobile phone to augment paper-based learning is technically feasible and seems to promote the application of verbatim note-taking and posting comprehension questions for discussion. However, the results of two course tests indicate that consequent learning improvement seemed inconsistent among the students. A six-week case study was also conducted to explore the implications of the augmented support to students’ learning practice. The findings show that mobile phones as learning supportive tools to augment paper-based learning could support students’ planning and management of learning strategies or activities. The portability of mobile phones and paper textbooks and the ubiquitous connection of paper-based learning with an online learning community may provide the flexibility in planning ahead for suitable learning strategies or activities and may enhance students’ assessment for management of students’ learning goals. [Copyright &y& Elsevier]

User identity recognition is the key shield to protect users' privacy data from disclosure and embezzlement. The user identity of mobile devices such as mobile phones mainly includes fingerprint recognition, nine-grid password, face recognition, digital password, etc. Due to the requirements of computing resources and convenience of mobile devices, these verification methods have their own shortcomings. In this paper, a user identity recognition technology based on finger trajectory is proposed. Based on the analysis of the users' finger trajectory data, the feature of the user's finger movement trajectory is extracted to realize the identification of the user. Also, in this paper, we design and implement an android app, through which we collect the real finger trajectory data of 34 people and use K-means clustering combined with Bayesian classification to recognize and distinguish the user identity. The experimental results show that the finger trajectory has a good performance on identifying the users, which can be constructed as a new low-cost scheme for mobile device user identity recognition. [ABSTRACT FROM AUTHOR]

Mobile phone backplanes are an important part of mobile phones, and are often affected by a wide range of factors during the manufacturing process, resulting in defects of various scales and similar backgrounds. Therefore, accurately identifying these defects is crucial for improving mobile phone quality. To address this challenge, this paper proposes a multi-scale and dynamic attention fusion UNet (MDAF-UNet) model. The model innovatively combines normal convolution with dilated convolution. This allows the model to capture subtle features of defects and to perceive a larger range of feature variations. Moreover, an improved attention mechanism is introduced in this paper. It fuses channel attention and spatial attention, and dynamically adjusts the feature fusion strategy with learnable weights. This allows the model to increase the attention of important features and improve the effectiveness of feature representation. Experimental results on a publicly available dataset show that the MDAF-UNet model achieves 66.9% Mean Intersection over Union (MIoU), outperforming other state-of-the-art models. This result provides an effective solution to the mobile phone backplane defect segmentation problem. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the prevalence of airflow obstruction and associated risk factors among study participants. Data were collected and compared using a paper questionnaire and mobile phone technology. The pilot study was carried out among adult residents of two communities in Nigeria and Benin Republic. A paper questionnaire and a mobile phone containing the same information were used to interview the respondents with spirometry testing between the two interviews. Data collected were analysed using SPSS version 16. Kappa statistics was used to test the agreement between the data collected using the paper questionnaire and the mobile phone. One hundred respondents comprising of 56 males and 44 females, with a mean age of 45.4±16.8 years participated in the study. Fifteen selected variables showed varying levels of agreement ranging from slight to perfect agreement between data collected using the two methods. The respiratory symptoms identified were cough (18%), phlegm (18%), wheeze (8%), and shortness of breath (30%). Wood was the major type of fuel used for cooking by the respondents (59.0%). Only 42 spirograms passed quality control and only 2 (4.8%) showed features of airflow obstruction. The study revealed that there was an agreement between data collected using mobile phones and the traditional paper questionnaire. The prevalence of risk factors for airflow obstruction was high among the respondents. We recommend that the use of mobile phones in data collection should be promoted and employed in large-scale surveys in all developing countries of the world. [ABSTRACT FROM AUTHOR]

The article discusses the telecommunication industry has evolved to provide services for new types of Internet of Things (IoT) devices in addition to basic mobile phone or internet services. Topics include the extended reality devices, sensors, and ground and aerial robots, to name a few. With the deployment of these new services, it is difficult for the wireless network to support ubiquitous connections with diverse quality-of-service (QoS) requirements.

The explosive growing number of data from mobile devices, social media, Internet of Things and other applications has highlighted the emergence of big data. This paper aims to determine the worldwide research trends on the field of big data and its most relevant research areas. A bibliometric approach was performed to analyse a total of 6572 papers including 28 highly cited papers and only papers that were published in the Web of Science Core Collection database from 1980 to 19 March 2015 were selected. The results were refined by all relevant Web of Science categories to computer science, and then the bibliometric information for all the papers was obtained. Microsoft Excel version 2013 was used for analyzing the general concentration, dispersion and movement of the pool of data from the papers. The t test and ANOVA were used to prove the hypothesis statistically and characterize the relationship among the variables. A comprehensive analysis of the publication trends is provided by document type and language, year of publication, contribution of countries, analysis of journals, analysis of research areas, analysis of web of science categories, analysis of authors, analysis of author keyword and keyword plus. In addition, the novelty of this study is that it provides a formula from multi-regression analysis for citation analysis based on the number of authors, number of pages and number of references. [ABSTRACT FROM AUTHOR]

The article reports on the development of a color version of electronic paper (e-paper) by E Ink. According Sriram K. Peruvemba, E Ink's vice president of marketing, e-paper could be used in a number of applications such as electronic books, electronic magazines, tablet personal computers (PC), cellular telephones and other handheld devices. The technology makes use of millions of tiny microcapsules and in the monochromatic version, each microcapsule contains positively charged white and negatively charged black particles suspended in clear fluid.

The quality of an image is most important at every stage of its processing. Images captured with recent smart devices such as digital cameras or smart mobile phones can be affected by various types of noise, which degrades image quality. The evaluation and elimination of noise or distortion in a picture is viewed as significant as, the evaluation of the image's quality. This study presents a survey of available techniques and algorithms for denoising images and determining image quality. This paper studies the types of noise or distortions, techniques, parameters used by the algorithm, various metrics used to assess the quality and the performance of the algorithm. Some of the important filters, databases in the area of image quality assessment and denoising are discussed in this paper. [ABSTRACT FROM AUTHOR]

With the rapid growth of urbanization and the proliferation of mobile phone usage, smart city initiatives have gained momentum in leveraging data-driven insights to enhance urban planning and resource allocation. This paper proposes a novel approach for predicting people's concentration and movements within a smart city environment using mobile phone data provided by telecommunication operators. By harnessing the vast amount of anonymized and aggregated mobile phone data, we present a predictive framework that offers valuable insights into urban dynamics. The methodology involves collecting and processing location-based data obtained from telecommunication operators. Using machine learning techniques, including clustering and spatiotemporal analysis, we developed models to identify patterns in people's movements and concentration across various city regions. Our proposed approach considers factors such as time of day, day of the week, and special events to capture the intricate dynamics of urban activities. The predictive models presented in this paper demonstrate the ability to predict areas of high concentration of people, such as commercial districts during peak hours, as well as the people flow during the time. These insights have significant implications for urban planning, traffic management, and resource allocation. Our approach respects user privacy by working with aggregated and anonymized data, ensuring compliance with privacy regulations and ethical considerations. The proposed models were evaluated using real-world mobile phone data collected from a smart city environment in Lisbon, Portugal. The experimental results demonstrate the accuracy and effectiveness of our approach in predicting people's movements and concentration. This paper contributes to the growing field of smart city research by providing a data-driven solution for enhancing urban planning and resource allocation strategies. As cities continue to evolve, leveraging mobile phone data from telecommunication operators can lead to more efficient and sustainable urban environments. [ABSTRACT FROM AUTHOR]

Android has been the most widely used operating system for mobile phones over the past few years. Malicious attacks against android are a major privacy and security concern. Malware detection techniques for android applications are therefore significant. A class of methods using Function Call Graphs (FCGs) for android malware detection has shown great potential. The relationships between functions are limited to simple binary relationships (i.e., graphs) in these methods. However, one function often calls several other functions to produce specific effects in android applications, which cannot be captured with FCGs. In this paper, we propose to formalize android malware detection as a hypergraph-level classification task. A hypergraph is a topology capable of portraying complex relationships between multiple vertices, which can better characterize the functional behavior of android applications. We model android applications using hypergraphs and extract the embedded features of android applications using hypergraph neural networks to represent the functional behavior of android applications. Hypergraph neural networks can encode high-order data correlation in a hypergraph structure for data representation learning. In experiments, we validate the gaining effect of hypergraphs on detection performance across two open-source android application datasets. Especially, HGNNP obtains the best classification performance of 91.10% on the Malnet-Tiny dataset and 97.1% on the Drebin dataset, which outperforms all baseline methods. [ABSTRACT FROM AUTHOR]

This study attempts to compare the density of human expiratory droplet deposition on commonly exposed/used surfaces of an indoor residential setting by simulating the droplet exhalation using mist sprays filled with a colored medium. The simulation is not an exact replica of a human exhale but is designed to reveal the variations between surfaces. The droplets dispersed in expiratory air in an indoor environment can carry microorganisms, both bacteria and viruses, causing respiratory infections. The process involved a human actor performing predefined daily tasks and was followed around by a second actor, who mimicked breath exhalation using mist sprays. The activities included reading a magazine, watching TV, using a mobile phone, a laptop, making tea, receiving visitors, and talking to a friend. Paper surfaces were used to collect the spray pigment. The results were scanned and analyzed by a computer. The output was in the form of percentage and pixel count of colored pigment on each paper. The results showed that the most significant percentage of pigment was received on the surfaces that simulated activities performed closest to the face. The top recipient of pigment by far was the mobile phone, followed by the remote controller, laptop, keyboard, and mouse. The surfaces farthest from the face, such as the floor, received little to no detectable pigment. [ABSTRACT FROM AUTHOR]

Inspired by pandemic-transformed instruction, this paper examines the digital accessibility of five tech tools used in information literacy sessions, specifically for students who use assistive technologies such as screen readers. The tools are Kahoot!, Mentimeter, Padlet, Jamboard, and Poll Everywhere. First, we provide an overview of the Americans with Disabilities Act (ADA) and digital accessibility definitions, descriptions of screen reading assistive technology, and the current use of tech tools in information literacy instruction for student engagement. Second, we examine accessibility testing assessments of the five tech tools selected for this paper. Our data show that the tools had severe, significant, and minor levels of digital accessibility problems, and while there were some shared issues, most problems were unique to the individual tools. We explore the implications of tech tools' unique environments as well as the importance of best practices and shared vocabularies. We also argue that digital accessibility benefits all users. Finally, we provide recommendations for teaching librarians to collaborate with campus offices to assess and advance the use of accessible tech tools in information literacy instruction, thereby enhancing an equitable learning environment for all students. [ABSTRACT FROM AUTHOR]

On-site determination of trace copper ions in natural waters is of great significance to environmental monitoring, and how to develop accurate and specific point-of-care test methods is one critical issue. In the study, a paper-based analytical device (PAD) being modified with a new truncated DNAzyme (CLICK-T, which was derived from a reported DNAzyme-CLICK-17) was developed for Cu ions detection. The detection mechanism was based on Cu(II)-catalyzed azide-alkyne cycloaddition (Cu(II)AAC) reaction. It can directly conduct on-site analysis of Cu(II) ions based on fluorescent signals detected using a mobile phone. In the assay, the CLICK-T was firstly modified on the PADs. Then, water samples containing Cu ions mixed with 3-azido-7-hydroxycoumarin and 3-butyn-1-ol were instantly dripped on PADs and incubated for 20 min. Finally, the PADs were excited at 365 nm and emitted fluorescence which could be analyzed on site using smart phones. The Cu(II) concentration could be quantified through RGB analysis with the aid of iPhone APP software. The limit of detection is 0.1 µM by the naked eye due to the fact that CLICK-T exhibited a good catalytic effect on Cu(II)AAC. The Cu(II) concentration could also be directly detected without using reductant, such as ascorbic acid, which is prone to be oxidized in air. This simplifies the PDA detection process improves its efficiency. The PAD is convenient for the on-site analysis of Cu ions in natural waters. [ABSTRACT FROM AUTHOR]

Millions of formal and informal land rights are still undocumented worldwide and there is a need for scalable techniques to facilitate that documentation. In this context, sketch mapping based on printed high-resolution satellite or aerial imagery is being promoted as a fit-for-purpose land administration method and can be seen as a promising way to collect cadastral and land use information with the community in a rapid and cost-effective manner. The main disadvantage of paper-based mapping is the need for digitization to facilitate the integration with existing land administration information systems and the sustainable use of the data. Currently, this digitization is mostly done manually, which is time-consuming and error-prone. This article presents the SmartLandMaps approach to land rights mapping and digitization to address this gap. The recording involves the use of sketches during participatory mapping activities to delineate parcel boundaries, and the use of mobile phones to collect attribute information about spatial units and land rights holders. The digitization involves the use of photogrammetric techniques to derive a digital representation from the annotated paper maps, and the use of computer vision techniques to automate the extraction of parcel boundaries and stickers from raster maps. The approach was deployed in four scenarios across Africa, revealing its simplicity, versatility, efficiency, and cost-effectiveness. It can be regarded as a scalable alternative to traditional paper-based participatory land rights mapping. [ABSTRACT FROM AUTHOR]

Nowadays, with the significant growth of the mobile market, security issues on the Android Operation System have also become an urgent matter. Trusted execution environment (TEE) technologies are considered an option for satisfying the inviolable property by taking advantage of hardware security. However, for Android, TEE technologies still contain restrictions and limitations. The first issue is that non-original equipment manufacturer developers have limited access to the functionality of hardware-based TEE. Another issue of hardware-based TEE is the cross-platform problem. Since every mobile device supports different TEE vendors, it becomes an obstacle for developers to migrate their trusted applications to other Android devices. A software-based TEE solution is a potential approach that allows developers to customize, package and deliver the product efficiently. Motivated by that idea, this paper introduces a VTEE model, a software-based TEE solution, on Android devices. This research contributes to the analysis of the feasibility of using a virtualized TEE on Android devices by considering two metrics: computing performance and security. The experiment shows that the VTEE model can host other software-based TEE services and deliver various cryptography TEE functions on theAndroid environment. The security evaluation shows that adding the VTEE model to the existing Android does not addmore security issues to the traditional design. Overall, this paper shows applicable solutions to adjust the balance between computing performance and security. [ABSTRACT FROM AUTHOR]

The article reports that researchers at Queen's University in Kingston, Ontario have developed a flexible E Ink display film, a paper computer for smart phones that may replace glass screens.

Background: The use of digital technology in healthcare has been found to be useful for data collection, provision of health information and communications. Despite increasing use of medical mobile phone applications (apps), by both clinicians and patients, there appears to be a paucity of peer-reviewed publications evaluating their use, particularly in pregnancy. This scoping review explored the use of mobile phone apps for clinical decision support in pregnancy. Specific objectives were to: 1. determine the current landscape of mobile phone app use for clinical decision support in pregnancy; 2. identify perceived benefits and potential hazards of use and 3. identify facilitators and barriers to implementation of these apps into clinical practice.Methods: Papers eligible for inclusion were primary research or reports on the development and evaluation of apps for use by clinicians for decision support in pregnancy, published in peer-reviewed journals. Research databases included Medline, Embase, PsychoInfo, the Cochrane Database of Systematic Reviews and the online digital health journals JMIR mHealth and uHealth. Charting and thematic analysis was undertaken using NVivo qualitative data management software and the Framework approach.Results: After screening for eligibility, 13 papers were identified, mainly reporting early stage development of the mobile app, and feasibility or acceptability studies designed to inform further development. Thematic analysis revealed four main themes across the included papers: 1. acceptability and satisfaction; 2. ease of use and portability; 3. multi-functionality and 4. the importance of user involvement in development and evaluation.Conclusions: This review highlights the benefits of mobile apps for clinical decision support in pregnancy and potential barriers to implementation, but reveals a lack of rigorous reporting of evaluation of their use and data security. This situation may change, however, following the issue of FDA and MHRA guidelines and implementation of UK government and other international strategies. Overall, the findings suggest that ease of use, portability and multi-functionality make mobile apps for clinical decision support in pregnancy useful and acceptable tools for clinicians. [ABSTRACT FROM AUTHOR]

Designed for an introductory nonmajors biology course, this case study presents students with a series of short news stories describing a scientific study of cell-phone use and its health effects. Students read the news stories and then the scientific paper they are based on, comparing the information presented by the news media to the information contained in the original research article. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things is the core field of smart city. And intelligent detection is an important application field of industrial Internet of Things. Demand of the industrial is particularly urgent. In particular, the defect detection of mobile phone shells (MPS) has always been a common problem for famous mobile phone companies. A compression-free defect detection method (CFDDM) for MPS based on machine vision is proposed in this paper. Firstly, affine transformation is utilized to solve the angle deviation of MPS in different images. Then, edge detection, binarization, and open operation are combined to highlight the edge region based on the results of angle adjustment. It is convenient for region of interest (ROI) extraction and clipping. Finally, the method of gray histogram contrasting is utilized for defect detection according to the results of ROI clipping. And the detection results are obtained. In this paper, MPS data set is utilized for many tests. The results show that the proposed method can effectively detect whether there are defects in MPS data set without image compression. The recognition accuracy is 100%. The recognition time of a single image is about 4.56 s, which is better than other defect detection methods. [ABSTRACT FROM AUTHOR]

Studies have demonstrated that parents often exhibit a still face while silently reading their cell phones when responding to texts. Such disruptions to parent-child interactions have been observed during parental media use such as texting and these disruptions have been termed technoference. In the present study, we explored changes to mother-child interactions that occur before, during and after interruptions due to texting using an adapted naturalistic still face paradigm. Specifically, we examined the effect of an interruption due to either maternal smartphone use or use of an analog medium on maternal interaction quality with their 20- to 22-month-old children. Mother-child interactions during free play were interrupted for 2 min by asking the mothers to fill out a questionnaire either (a) by typing on the smartphone (smartphone group) or (b) on paper with a pen (paper-pencil group). Interactional quality was compared between free-play and interruption phases and to a no-interruption control group. Mixed ANOVA across phase and condition indicated that maternal responsiveness and pedagogical behavior decreased during the interruption phase for both the interruption groups (smartphone and paper-and-pencil) but not for the no-interruption group. Children also increased their positive bids for attention during the paper-and-pencil and the smartphone conditions relative to the no-interruption control. These findings are consistent with a large body of research on the still-face paradigm and with a recent study demonstrating that smartphone interruptions decreased parenting quality. The present study, however, connects these lines of research showing the many everyday disruptions to parent-child interactions are likely to decrease parenting quality and that toddlers are likely to detect and attempt to repair such interruptions. [ABSTRACT FROM AUTHOR]

Pedestrians, bicyclists, and scooterists are Vulnerable Road Users (VRUs) in traffic accidents. The number of fatalities and injuries in traffic accidents involving vulnerable road users has been steadily increasing in the last two decades in the U.S., even though road vehicles now have perception sensors like cameras to detect risk and issue collision warnings or apply emergency braking. Perception sensors like cameras are highly affected by lighting and weather conditions. Cameras, radar, and lidar cannot detect vulnerable road users in partially occluded and occluded situations. This paper proposes the use of Vehicle-to-VRU communication to inform nearby vehicles of VRUs on trajectories with a potential collision risk. An Android smartphone app with low-energy Bluetooth (BLE) advertising is developed and used for this communication. The same app is also used to collect motion data of VRUs for training. VRU motion data are smoothed using a Kalman filter, and an LSTM neural network is used for future motion prediction. This information is used in an algorithm comparing Time-To-collision-Zone (TTZ) for the vehicle and VRU, and issues driver warnings with different severity levels. The warning severity level is based on the analysis of real data from a smart intersection for close vehicle and VRU interactions. The resulting driver warning system is demonstrated using proof-of-concept experiments. The method can easily be extended to a VRU collision-mitigation system. [ABSTRACT FROM AUTHOR]

This article presents the Motor Transport Institute's research to set out road safety indicators of behaviors and opinions on one of the increasingly important road traffic problems. Two types of studies on the unsafe use of mobile phones and others on board devices (distraction) by road users in Poland between 2014 and 2023 are presented. Safety Performance Indicators (SPI) on handheld mobile phone use from roadside observations and declared opinions on talking, reading messages, checking social media/news, and listening to headphones while driving, cycling, and walking are presented. Overall, 306,240 passenger car drivers observed on all road types all week long in Poland showed a dropping trend (1.8%) between before the study in 2014 SPI 4.1% distracted drivers to SPI 2.3% after the study in 2022. More drivers used mobile phones on single carriageways both in built-up and outside built-up areas. On motorways outside built-up areas, where vehicles are speeding, drivers of passenger cars rarely talk on their handheld mobiles. Results from the first European Union (EU) Baseline project to collect road indicators produced a Key Performance Indicator of 3.8% distracted passenger car (all types of roads, all weekdays and weekend) from 44,011 observed in Poland in 2021. Results from the EU project E-Survey on Road Users' Attitude, third edition (ESRA3), showed declared opinions of mobile use while driving, cycling, and walking down the street in Poland in 2023 compared to 2018 (ESRA2). A positive trend is seen among car drivers who declared lower use of handheld mobile phones than in 2018 (a drop of 11.2%). The survey showed Polish cyclist used more often headphones to listen to music, checked news and messages than cyclists in Europe in 2023. More by 10.1% pedestrians in Europe than in Poland declared checking social media/news, reading messages/emailing while walking down the street in 2023. This lower rate in Poland can be explained by pedestrian's legal prohibition of mobile phone use while crossing the street since 2021. There is strong support for policy measures forbidding all drivers of motorized vehicles to use handheld mobile phone use while driving in all of Europe. Enforcement measures are twice as strong in Europe than in Poland. As the number of accidents and fatalities on distraction is unknown, calculating SPI during roadside observations and questionnaire surveys gives in-depth knowledge of the problem. The authors of the paper represent the Motor Transport Institute's (MTI's) research institution, which systematically analyzes trends in road safety in Poland during its own, national, and international projects. [ABSTRACT FROM AUTHOR]

The data sets provided by Information and Communication Technologies have been extensively used to study the human mobility in the framework of complex systems. The possibility of detecting the behavior of individuals performing the urban mobility may offer the possibility of understanding how to realize a transition to a sustainable mobility in future smart cities. The Statistical Physics approach considers the statistical distributions of human mobility to discover universal features. Under this point of view the power laws distributions has been extensively studied to propose model of human mobility. In this paper we show that using a GPS data set containing the displacements of mobile devices in an area around the city Rimini (Italy), it is possible to reconstruct a sample of mobility paths and to study the statistical properties of urban mobility. Applying a fuzzy c-means clustering algorithm, we succeed to detect different mobility types that highlight the multilayer structure of the road network. The disaggregation into homogeneous mobility classes explains the power law distributions for the path lengths and the travel times as an overlapping of exponential distributions, that are consistent with a maximum entropy Principle. Under this point of view it is not possible to infer other dynamical properties on the individual mobility, except for the average values of the different classes. We also study the role of the mobility types, when one restricts the analysis to the an origin-destination framework, by analyzing the daily evolution of the mobility flows. [ABSTRACT FROM AUTHOR]

Since the invention of the microphone by Barina in 1876, there have been numerous applications of audio processing, such as phonographs, broadcasting stations, and public address systems, which merely capture and amplify sound and play it back. Nowadays, audio processing involves analysis and noise-filtering techniques. There are various methods for noise filtering, each employing unique algorithms, but they all require two or more microphones for signal processing and analysis. For instance, on mobile phones, two microphones located in different positions are utilized for active noise cancellation (one for primary audio capture and the other for capturing ambient noise). However, a drawback is that when the sound source is distant, it may lead to poor audio capture. To capture sound from distant sources, alternative methods, like blind signal separation and beamforming, are necessary. This paper proposes employing a beamforming algorithm with two microphones to enhance speech and implementing this algorithm on an embedded system. However, prior to beamforming, it is imperative to accurately detect the direction of the sound source to process and analyze the audio from that direction. [ABSTRACT FROM AUTHOR]

With the popularity of smartphones, a large number of "phubbers" have emerged who are engrossed in their phones regardless of the situation. In response to the potential dangers that phubbers face while traveling, this paper proposes a multimodal danger perception network model and early warning system for phubbers, designed for mobile devices. This proposed model consists of surrounding environment feature extraction, user behavior feature extraction, and multimodal feature fusion and recognition modules. The environmental feature module utilizes MobileNet as the backbone network to extract environmental description features from the rear-view image of the mobile phone. The behavior feature module uses acceleration time series as observation data, maps the acceleration observation data to a two-dimensional image space through GADFs (Gramian Angular Difference Fields), and extracts behavior description features through MobileNet, while utilizing statistical feature vectors to enhance the representation capability of behavioral features. Finally, in the recognition module, the environmental and behavioral characteristics are fused to output the type of hazardous state. Experiments indicate that the accuracy of the proposed model surpasses existing methods, and it possesses the advantages of compact model size (28.36 Mb) and fast execution speed (0.08 s), making it more suitable for deployment on mobile devices. Moreover, the developed image-acceleration multimodal phubber hazard recognition network combines the behavior of mobile phone users with surrounding environmental information, effectively identifying potential hazards for phubbers. [ABSTRACT FROM AUTHOR]

The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such pedestrian-friendly walking environments. Identifying locations and routes with high pedestrian concentration is critical for improving pedestrian-friendly walking environments. This paper presents a quantitative method to map pedestrian walking behavior by utilizing real-time data from mobile phone sensors, focusing on the University of Moratuwa, Sri Lanka, as a case study. This holistic method integrates new urban data, such as location-based service (LBS) positioning data, and data clustering with unsupervised machine learning techniques. This study focused on the following three criteria for quantifying walking behavior: walking speed, walking time, and walking direction inside the experimental research context. A novel signal processing method has been used to evaluate speed signals, resulting in the identification of 622 speed clusters using K-means clustering techniques during specific morning and evening hours. This project uses mobile GPS signals and machine learning algorithms to track and classify pedestrian walking activity in crucial sites and routes, potentially improving urban walking through mapping. [ABSTRACT FROM AUTHOR]

The joint optimisation of product design configuration (PDC) for new and remanufactured products involves specification upgrading for parts recovered from used product returns. Reversely, the specification upgrading decision for used parts/modules is also affected by the original specifications selected for parts/modules during the new product design process. Hence, the joint optimisation of PDC for both new and remanufactured products entails a hierarchical decision framework, of which scarcely any study involves the specification upgrading concerns. To fill this gap, this paper proposes a bilevel optimisation model that involves two-level decision-making. The upper level handles the configuration of new product variants to maximise the shared surplus of new product offerings. Meanwhile, the lower-level deals with the configuration and specification upgrading of remanufactured product variants to maximise the shared surplus of remanufactured product offerings. A non-linear integer bilevel programming is further presented to model the hierarchical optimisation problem, to solve which a nested bilevel genetic algorithm is also proposed. Furthermore, a case study involving configuration design for new and remanufactured mobile phone variants is conducted to validate the proposed model. Four scenarios are investigated to examine the effects of model parameters on the optimal solutions with the simulation result given at last. [ABSTRACT FROM AUTHOR]

Background: South Africa is pursuing a malaria elimination initiative, with the goal of zero local transmission by the year 2018. The South African National Department of Health has developed a 24 Hour Electronic Reporting System that is expected to decrease the time required for malaria cases to be reported from the health facility level, to the district, provincial and national levels. This will facilitate case investigation within 48 hours and response within 72 hours upon/of diagnosis, the objective of our study was to compare timeliness of data input between the paper-based and the 24-hour reporting system and to assess the acceptability of end users to use the new 24-hour reporting system. Methods & Materials: This is a prospective descriptive study, using a questionnare with open and close ended questions which was developed using Epi Info 7. We compared 148 cases of the current reporting paper-based system and the 24-hour reporting system (Unstructured supplementary service data-USSD platform). We analysed the responses using STATA version 13. Results: The preliminary findings from the study show that the mean time difference in days from date of diagnosis to the case being captured was one day for the 24-hour reporting system and seven days for the current papaer-based system. the mean time difference in days for case investigation to occur using the papaer based system is 5.4 days. all 120 health care facility workers interviewed found the system to be simple to use and were willing to use the system to report malaria cases. Conclusion: The 24-hour reporting system has decreased the time required for maaria cases to be notified from the healthcare facility to the district, provincial and national levels. the next step will be to assess whether this system will improve investigation timeliness (48 hours from diagnosis) and response (72 hours) for those sub-districts that have an annual parasite rate of <0.1/1000 population at risk. [ABSTRACT FROM AUTHOR]

Ground contact time (GCT) is one of the most relevant factors when assessing running performance in sports practice. In recent years, inertial measurement units (IMUs) have been widely used to automatically evaluate GCT, since they can be used in field conditions and are friendly and easy to wear devices. In this paper we describe the results of a systematic search, using the Web of Science, to assess what reliable options are available to GCT estimation using inertial sensors. Our analysis reveals that estimation of GCT from the upper body (upper back and upper arm) has rarely been addressed. Proper estimation of GCT from these locations could permit an extension of the analysis of running performance to the public, where users, especially vocational runners, usually wear pockets that are ideal to hold sensing devices fitted with inertial sensors (or even using their own cell phones for that purpose). Therefore, in the second part of the paper, an experimental study is described. Six subjects, both amateur and semi-elite runners, were recruited for the experiments, and ran on a treadmill at different paces to estimate GCT from inertial sensors placed at the foot (for validation purposes), the upper arm, and upper back. Initial and final foot contact events were identified in these signals to estimate the GCT per step, and compared to times estimated from an optical MOCAP (Optitrack), used as the ground truth. We found an average error in GCT estimation of 0.01 s in absolute value using the foot and the upper back IMU, and of 0.05 s using the upper arm IMU. Limits of agreement (LoA, 1.96 times the standard deviation) were [−0.01 s, 0.04 s], [−0.04 s, 0.02 s], and [0.0 s, 0.1 s] using the sensors on the foot, the upper back, and the upper arm, respectively. [ABSTRACT FROM AUTHOR]

When a band is performing at a public occasion, certain sound effects are expected to be added to enliven the atmosphere. To achieve this effect, microphones and instruments are all connected to an audio mixer, then the expected audio output will be played through the speakers. However, sound engineers always spend plenty of time tuning the mixer until the satisfied results are obtained. This paper presents a smart digital mixer system that integrates touch control, speech control, and commonly used functions on an Android mobile platform to improve the mobility of audio mixer while tuning. The proposed system adopts a digital signal processor (DSP) as the core of the hardware architecture. The application provides a UI interface on an Android mobile phone in order to achieve the functions of speech recognition and touch control. The control commands will be transmitted to DSP via Bluetooth 5.0, self-defined Bluetooth packet format (SBPF), and data transfer controller (DTC). The main contribution of this work is to propose multiple functions of a mixer system with a convenient and interactive user interface. The experimental results show the average accuracy of all respondents reached 92.3%. Moreover, the proposed system has the advantage of having a low-cost hardware circuit design, and provides high flexibility of setting for the audio mixer system according to the user's preference. [ABSTRACT FROM AUTHOR]

Mobile phone consumers have been motivated by the rapid growth of technology and encouraged to update their devices regularly to keep up with new innovations, architectures, and capabilities. Consequently, mobile/cell phone waste has risen significantly in the last decade. Due to their small size, it is convenient for users to keep outdated or unused mobile phones at home or the office, rather than recycling them appropriately. A reverse supply chain (RSC) is one possible method of mitigating the questionable e-waste activity present in the ecosystem. RSC has been significant for the mobile phone industry, user states, analysts, and scholars. This paper reviews the available literature in the RSC management (RSCM) domain, along with its processes and strategies. The paper reviews 223 published scholarly papers in the domain of mobile phone waste recycling and investigates 22 papers related to factors influencing consumers’ intention with regard to electronic recycling, focusing on mobile devices, which contribute significantly to electronic waste management practices. [ABSTRACT FROM AUTHOR]

Since there is steady increase in cell phone addiction, the act of reaching for a phone between tasks, or even mid-task, is becoming more commonplace, without a true understanding about the potential cognitive costs of taking a break in this way as opposed to taking a break through another medium. This experimental study included 414 participants who completed a cognitively demanding task (solving anagrams) either on paper or on a computer screen. Participants in three of four randomly assigned conditions engaged in a break task (selecting items for a hypothetical shopping list) either on a cell phone, a larger computer screen, or on a paper in the middle of the task. The fourth condition had participants engaging in both halves of the cognitive task with no break. The results show that using cell phone for a break did not allow brain to recharge as effectively as the other types of breaks, both in terms of being able to perform quickly and efficiently in the second half of the task (how long it took to complete), and in terms of performance (how many anagrams were successfully solved in the second half). As people are increasingly addicted to their cell phones, it is important to know the unintended costs associated with reaching for this device every spare minute. Although people may assume that it is not different from any other kind of interaction or break, this study shows that the phone might be more cognitively taxing than expected. [ABSTRACT FROM AUTHOR]