Everyday Use Research Articles

Research gaps in the neurodevelopmental assessment of children with complex congenital heart defects: a scoping review

BackgroundChildren with congenital heart defects (CHD) are at risk for a range of developmental disabilities that challenge cognition, executive functioning, self-regulation, communication, social-emotional functioning, and motor skills. Ongoing developmental surveillance is therefore key to maximizing neurodevelopmental outcome opportunities. It is crucial that the measures used cover the spectrum of neurodevelopmental domains relevant to capturing possible predictors and malleable factors of child development.ObjectivesThis work aimed to synthesize the literature on neurodevelopmental measures and the corresponding developmental domains assessed in children aged 1−8 years with complex CHD.MethodsPubMed was searched for terms relating to psycho-social, cognitive and linguistic-communicative outcomes in children with CHD. 1,380 papers with a focus on complex CHD that reported neurodevelopmental assessments were identified; ultimately, data from 78 articles that used standardized neurodevelopmental assessment tools were extracted.ResultsThirty-nine (50%) of these excluded children with syndromes, and 9 (12%) excluded children with disorders of intellectual development. 10% of the studies were longitudinal. The neurodevelopmental domains addressed by the methods used were: 53% cognition, 16% psychosocial functioning, 18% language/communication/speech production, and 13% motor development-associated constructs.ConclusionsData on social communication, expressive and receptive language, speech motor, and motor function are underrepresented. There is a lack of research into everyday use of language and into measures assessing language and communication early in life. Overall, longitudinal studies are required that include communication measures and their interrelations with other developmental domains.

Wykorzystanie nowych technologii medialnych przez młodzież i seniorów. Raport z badań

The Internet and new media have become an integral part of everyday life for many people, regardless of age or social status. Young people and senior citizens are two important social groups affected by the development of media technologies, although often in very different ways. People belonging to different social categories may use new technologies in significantly different ways and have different problems related to their everyday use. Therefore, the aim of the analysis in the following sections is to identify the characteristics and ways in which young people and seniors use new media technologies. The analyses of the empirical material obtained in the face-to-face interviews aimed to answer the following research questions: (RQ1) What are the ways, characteristics and problems associated with the use of new media technologies by contemporary users? (RQ2) What are the peculiarities of the use of new media technologies by young people? (RQ3) What are the peculiarities of the use of new media technologies by older people? The results of the research indicate that the ways, characteristics and problems of using media technologies are rarely shared between older and younger people, as significant discrepancies are usually revealed. In particular, the observation of the specifics of the use of new media technologies by young people indicates that for them it is a tool that is indispensable for their daily personal, social and educational needs (permanent connection). Seniors, on the other hand, recognise the benefits of technology, but at the same time value life beyond the screen.

Combining Different Wearable Devices to Assess Gait Speed in Real-World Settings.

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices' performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices. Our study involved 20 healthy subjects performing a modified Six-Minute Walking Test (6MWT) under various conditions. The results revealed only little performance differences among devices, with the combination of smartwatches and smart shoes exhibiting superior estimation accuracy. Particularly, smartwatches captured additional health-related information and demonstrated enhanced accuracy when paired with other devices. Surprisingly, wearing all devices concurrently did not yield optimal results, suggesting a potential redundancy in feature extraction. Feature importance analysis highlighted key variables contributing to gait speed estimation, providing valuable insights for model refinement.

Pottery Vessels with graffiti Discovered in the Fort of Ala I Batavorum in Dacia

This paper presents graffiti discovered on a few plates discovered in a barrack from the fort of ala I Batavorum milliaria in Dacia. Typical for the Batavian troops, the onomastics is Latin and Greek. The instrumenta prove that the soldiers scribbled their names on every-day use vessels and offer us a glimpse of the very men that lived there together.

Food porn 2.0? Definitions, challenges, and potentials of an elusive concept

ABSTRACT Food porn emerged in the 1970s as an academic concept and has since become integrated into everyday social media use. The aim of this article is to analyse the concept of food porn through a critical discussion of the existing literature in cultural and media studies focusing on the definitions of food porn, its uses as an analytical and theoretical lens to explore food aesthetics, and its current relevance. The authors show that the definitions and interpretations vary a great deal and argue that three overarching themes dominate the literature: 1) formal aesthetics; 2) gender, body, and sexuality; 3) excess and transgression. Finally, it is argued that future uses of the concept should either focus on a) an empirically founded approach focusing on the actual use of the concept; or b) a theoretically founded approach with a formal typology focusing on hierarchies and power dynamics.

Ask how they did it: untangling the relationships between task-specific strategy use, everyday strategy use, and associative memory

ABSTRACT Objective Past research has shown that self-reported everyday strategy use and task-specific strategy use are related to associative memory performance in aging. Understudied is the relationship between these types of strategy use, whether they predict associative memory performance, and how this may differ across genders. Method A sample of older adults (N = 566, 53% female, ages 60–80) completed this online study. Study measures included 1. Multifactorial Memory Questionnaire (MMQ) Strategy Use subscale, a self-report measure of everyday strategy use, 2. Face-Name Task (FNT), a measure of associative memory, and 3. self-initiated number and types of strategies used on the FNT. Analyses examined the interrelationships among all study measures and their relative contributions to FNT performance while accounting for intraindividual factors. Results Participants who reported using more strategies on the FNT performed better than those who used fewer or no strategies; those who reported using at least three strategies and relating FNT to past experience performed best. Women outperformed men on the FNT but did not differ in task-specific strategy use. Participants who reported using no strategies on the FNT had lower MMQ Strategy Use scores. A multiple regression analysis indicated that female gender and using at least two task strategies were significant predictors of greater FNT performance. Conclusions The results indicate that task-specific strategy use relates more to associative memory performance than to everyday strategy use, but neither accounts for the female advantage in FNT performance. Findings encourage querying task-specific strategy use to contextualize age-related associative memory decline.

Community self‐protection, public authority and the safety of strangers in Bor and Ler, South Sudan

AbstractProtection is not simply something done or delivered to people by states, humanitarian organisations and armed peacekeepers. Instead, a growing literature has begun to examine the self‐protection strategies of people and communities in protracted violent crises. Its authors suggest that nuanced understandings of how people retain a measure of agency in the face of violence is an important first step for those seeking to reduce their levels of threat and vulnerability. We use interview data from communities in Bor and Ler, South Sudan, long affected by conflict, to show how attention to the relationship between public authority and the safety of strangers can reveal the skills, resources and conditions under which protection is successfully provided. This also helps to re‐root ‘protection’ in local vernaculars that more closely resemble its everyday use among South Sudanese and offers entry points for humanitarian interventions with more realistic prospects of positive outcomes for communities sceptical of humanitarians' broken promises to protect.

Research status of colloidal gold detection technology in medicine

Research status of colloidal gold detection technology in medicine

PSI-9 Relationship of body condition measures and boar reproductive performance

Abstract In the swine industry, boar nutritional requirements are not well characterized; thus, boars are typically fed to maintain a specific body condition score (BCS). Assessing body condition with subjective scoring can lead to over or underfeeding, which may have repercussions on sperm production and(or) quality. There are objective tools to assess body condition in live boars, like backfat (BF) thickness measured with real-time ultrasound, the Knauer caliper, and flank-to-flank (F2F) length. The relationship of sperm production and quality with BCS has not been reported in modern genetics and modern boar studs. The purpose of this study was to evaluate the relationship of body condition measures with boar reproductive performance. Data collected in March 2023 on commercial boars (n = 147) included a BCS ranging from 2.25 to 3.5, ultrasound backfat (13.7 ± 4.37 mm) performed by a trained technician, body weight (BW; 222 ± 30.2 kg) estimated using heart girth and body length from poll to tailhead, F2F length (106.03 ± 5.94 cm) and Knauer caliper score (17.5 ± 2.37). Additional variables considered were boar genetic line, age, and collection frequency. Sperm production data (total motility, 92.1 ± 7.22%; concentration, 36.7 ± 12.10 mil/mL; ejaculate volume, 231.1 ± 73.72 mL; normal cells, 83.4 ± 11.27%) were obtained from the six collections immediately prior to body condition evaluation. Data were evaluated with the glmmTMB package of R Statistical Software using a generalized linear mixed model. There were no significant relationships between motility or ejaculate volume and boar body condition. Backfat depth was related to percentage of normal cells (P = 0.029) and inversely related to sperm concentration (P = 0.035). There was a tendency for boars with greater F2F to have greater sperm concentration (P = 0.090). Generally, the percentage of normal cells decreased with increasing BCS, though due to the low number of observations in the lower categories, only BCS 3.25 and BCS 3.5 boars were found to have a significant relationship with the trait (P = 0.004 and P = 0.022, respectively). Caliper measure was not related with any sperm parameters. While accessible tools are necessary for consistent management of boars, BF thickness measured by ultrasound was the only objective tool in this study with a significant relationship to any sperm parameters assessed. Measuring BF with ultrasound may not be practical for everyday use. More research should be done to further assess body condition measurements, objective measuring tools, and boar sperm production.

Assessment of demand consumptions and potential viability of installation of biogas digester in melani village Eastern Cape, South Africa

AbstractAfrica relies heavily on traditional fossil fuel sources, especially coal. To solve the energy problem in rural areas, the country initiated the production and distribution of several renewable energy technologies. Biogas has been proven viable and has begun as a promising technology among several promising technologies. It has been one of the most successful models for producing clean, environmentally friendly, cost-effective energy sources and has multiple benefits. A financial analysis will be conducted, including an estimation of the total investment, the present value of the annual investment, the present value of the investment, and a simple payback period. To determine the demand, onset CTA-A hobo current transducers were installed in three families to measure everyday use in summer and winter. The Data acquisition system has shown that each home consumes an average of 140 kWh of electricity per month. Finally, the biogas digester's analytical life cycle cost analysis shows that the simple payback period would be approximately two years.

A Hybrid Image Augmentation Technique for User- and Environment-Independent Hand Gesture Recognition Based on Deep Learning

This research stems from the increasing use of hand gestures in various applications, such as sign language recognition to electronic device control. The focus is the importance of accuracy and robustness in recognizing hand gestures to avoid misinterpretation and instruction errors. However, many experiments on hand gesture recognition are conducted in limited laboratory environments, which do not fully reflect the everyday use of hand gestures. Therefore, the importance of an ideal background in hand gesture recognition, involving only the signer without any distracting background, is highlighted. In the real world, the use of hand gestures involves various unique environmental conditions, including differences in background colors, varying lighting conditions, and different hand gesture positions. However, the datasets available to train hand gesture recognition models often lack sufficient variability, thereby hindering the development of accurate and adaptable systems. This research aims to develop a robust hand gesture recognition model capable of operating effectively in diverse real-world environments. By leveraging deep learning-based image augmentation techniques, the study seeks to enhance the accuracy of hand gesture recognition by simulating various environmental conditions. Through data duplication and augmentation methods, including background, geometric, and lighting adjustments, the diversity of the primary dataset is expanded to improve the effectiveness of model training. It is important to note that the utilization of the green screen technique, combined with geometric and lighting augmentation, significantly contributes to the model’s ability to recognize hand gestures accurately. The research results show a significant improvement in accuracy, especially with implementing the proposed green screen technique, underscoring its effectiveness in adapting to various environmental contexts. Additionally, the study emphasizes the importance of adjusting augmentation techniques to the dataset’s characteristics for optimal performance. These findings provide valuable insights into the practical application of hand gesture recognition technology and pave the way for further research in tailoring techniques to datasets with varying complexities and environmental variations.

A study on the effect of the geometric properties and surface defects on silicon chip flexibility for wearable electronics

A study on the effect of the geometric properties and surface defects on silicon chip flexibility for wearable electronics

Creational and conversational AI affordances: How the new breed of chatbots are revolutionizing the knowledge industries

The new generative AI paradigm offers unprecedented opportunities for users to tap into. AI capabilities are increasingly helpful in creative and knowledge-intensive domains that have long been considered a territory of human expertise. The new breed of chatbots is based on large language models, and they have overcome many constraints that plague the everyday use of previous AI technologies. This article employs the theory of affordances to understand how ChatGPT facilitates (i.e., affords) and constraints (i.e., disaffords) the usefulness of a new breed of chatbots. We further divide two distinct yet interrelated dimensions of new AI affordances: creational and conversational. Using 29 interviews with professionals using ChatGPT in various creative and knowledge-intensive sectors, we identify three creational (content creation and enhancement, knowledge acquisition and creativity augmentation, and task automation) and three conversational (contextual sensitivity, interactive accessibility, and human–AI workflow synergy) affordances. Creational affordances refer to the system’s ability to produce novel outputs as well as automate routine work, whereas conversational affordances encompass the variety of interaction possibilities with an AI system. Interestingly, both affordances also involve disaffordances that limit the usefulness of the new types of AI systems. Furthermore, we introduce an integrated framework that shows how creational and conversational affordances reinforce each other via meta-affordances of accessibility, accumulation, and adaptability. We illustrate our findings with practical examples and offer guidelines for using these emerging capabilities in company settings.

Назад в будущее: визуализация развития, проблем и перспектив искусственного интеллекта, Data Science, квантовых вычислений

The paper is designed as a review and analysis of the current situation in the field of information technology (IT). The relevance of the article arises from the need to popularize IT among young people, which is reflected in the documents of the Ministry of Digital Development, Communications and Mass Communications of the Russian Federation, as well as from the high demand for experts in the field of digital technologies and the need to increase the digitalization of Russia. According to GeekBrains (the first programming school in Russia, which appeared in 2010, and the leader in the field of training for digital professions, which operates in 85 regions of the Russian Federation and 21 countries of the world), the number of IT job vacancies in this country will grow up to 2 million by 2027. All large organizations are looking for specialists in different IT branches, which are described in this and the following research paper. In this article, which is the first part of the study, the capabilities and problems of the following advanced technologies are considered: artificial intelligence, Data Science and quantum computing. The concepts of technologies are analyzed from the viewpoints of their everyday use and professional application. The topics are closely related and complement each other in one way or another. The article follows the logic and chronology of events in the global IT sphere. The conclusion contains a description of the author's thought experiment about bringing machine intelligence to life, it accumulates the mentioned technologies while taking into account the laws of physics. The calculations for this experiment are given as well. The materials from one of the GeekBrains's educational shows “The Way to IT” were used, including the GIF animation, which is reproduced only on the website of the “Scientific Visualization” journal.

An optimization-aided approach to parametrize scalable models of induction machines in speed variable drives

The accurate and time-saving prediction of essential machine variables (output power, torque, and efficiency) is crucial for manufacturers offering a wide power range of induction machines. Many motor variants are typically produced by axially scaling and rewinding the machine. Rescaling procedures of electromagnetic models of induction machines are in everyday use and well known. However, while a high accuracy can be achieved by rescaling in theory, more significant deviations between simulated and measured output parameters of the realized scaled device occur in praxis. These deviations can mainly be attributed to the faulty separation of effects in the distinct machine components, such as the rotor, stator, and bearings. This paper introduces an optimization-aided modeling approach based on the induction machine’s simple equivalent circuit representation. The method is validated by measurement data obtained from many induction machines with various axial lengths and winding configurations.

Vehicle Damage Analysis

Abstract: Vehicle damage, resulting from accidents, environmental factors, and everyday use, presents a ubiquitous challenge to vehicle owners and the broader automotive industry. An efficient and accurate vehicle damage assessment is essential for insurance claims, resale valuations, and overall vehicle safety. However, the traditional damage assessment methods often involve human subjectivity and can be time-consuming, leading to inefficiencies and customer dissatisfaction. This abstract explores the need for modernizing and automating the vehicle damage assessment process. Vehicle damage analysis plays a crucial role in accident reconstruction, insurance claims, safety assessment, and legal proceedings. This abstract provides an overview of the key aspects of vehicle damage analysis, including the methods and tools used, as well as its broader implications. Vehicle damage analysis involves the systematic examination and assessment of damage sustained by vehicles involved in accidents, incidents, or natural disasters. This process is essential for determining the cause and severity of the damage, estimating repair costs, and establishing liability in legal cases. This abstract highlights the multifaceted nature of the problem, encompassing the need for accurate and efficient damage detection, cost estimation, integration with insurance systems, and improved customer experiences. Addressing these challenges requires the application of advanced technologies such as computer vision, artificial intelligence, and machine learning, as well as a commitment to data security, privacy, and regulatory compliance.

"WOOP is my safe haven": A qualitative feasibility and acceptability study of the Wish Outcome Obstacle Plan (WOOP) intervention for spouses of people living with early-stage dementia.

As symptoms emerge and worsen in people living with dementia, their spouses can benefit from behavioral interventions to support their adjustment as a care partner. The Wish Outcome Obstacle Plan (WOOP) intervention improves the well-being of spouses of people living with dementia early in the disease course, but intervention mechanisms and opportunities for improvement are unclear. The present study gave voice to spouses who participated in a trial of WOOP, describing how WOOP was incorporated into their lives and how it could be improved for future implementation. For this qualitative study, we conducted longitudinal semi-structured interviews among 21 spouses of people living with dementia (three interviews over three months; 63 interviews total). Codebook thematic analysis was performed. Three meta-themes were derived: (1) assessing baseline strengths and limitations of WOOP, (2) learning from experience, and (3) fine-tuning and sustaining WOOP. Participants described how WOOP addressed their interpersonal and emotional stressors, their responses to behaviors of the person living with dementia, and their relationship quality. Considerations for future intervention delivery (e.g., solo vs. in group settings) and instructions (e.g., encouraging writing vs. thinking through the four steps of WOOP) were identified as areas of improvement. WOOP was described as a practical, feasible, and desirable intervention for spouses at the early stages of their partner's dementia. Participants made WOOP easier to incorporate in their everyday lives by adapting the design into a mental exercise that they used as needed. Suggestions from participants specified how to make the everyday use of WOOP more feasible, sustainable, and applicable in a variety of contexts. ClinicalTrials.gov HIC 2000021852.

Evaluation of Antibiotics by Disk Diffusion and Minimum Inhibitory Concentration Breakpoints in Urinary Tract Infections

Antibiotic resistance (ABR) has made it more challenging to treat uropathogenic organisms. It is impossible to compromise antimicrobial susceptibility testing (AST), which is essential and has a significant impact on infection treatment strategies. Although labor-intensive and technically challenging for everyday laboratory use, the agar dilution technique is appropriate for monitoring and assessing novel antimicrobials. Objective: To determine the minimum inhibitory concentration (MIC), Agar dilution technique and disk diffusion as susceptibility test methodologies. Methods: This study was carried out at Khyber Girls Medical College (KGMC) Peshawar. Keeping in view the Clinical and Laboratory Standards Institute (CLSI) guidelines AST was executed. BIOMÉRIEUX® API® kits and gram staining were utilized for identification of bacteria. The disk diffusion was performed using Thermo ScientificTM OxoidTM antibiotic discs of Co-trimoxazole, Levofloxacin, Nitrofurantoin and Fosfomycin. The MIC and zone of inhibitions for disk diffusion were noted according to the CLSI protocol. Results: 158 culture positive samples were isolated out of 680 total received. Esherechia Coli (E. coli) (74.1%) being the most isolated organism. In comparison of disk diffusion and agar dilution, categorical agreement for Levofloxacin, Cotrimoxazole, Nitrofurantoin and Fosfomycin were (82.28%, 72.15 %, 87.97% and 82.28%) respectively. Kappa coefficients of (0.64, 0.43, 0.57 and 0.37) (p < 0.0001) were calculated for Levofloxacin, Co-trimoxazole, Nitrofurantoin, and Fosfomycin respectively, revealing considerable level of agreement for these antibiotics. Conclusions: It was concluded that Agar dilution is more precise than disk diffusion but being more labor intensive and technical. Disk diffusion can still produce significantly accurate results with less resource consumption.

Measuring Surface Electromyography with Textile Electrodes in a Smart Leg Sleeve.

This paper presents the design, development, and validation of a novel e-textile leg sleeve for non-invasive Surface Electromyography (sEMG) monitoring. This wearable device incorporates e-textile sensors for sEMG signal acquisition from the lower limb muscles, specifically the anterior tibialis and lateral gastrocnemius. Validation was conducted by performing a comparative study with eleven healthy volunteers to evaluate the performance of the e-textile sleeve in acquiring sEMG signals compared to traditional Ag/AgCl electrodes. The results demonstrated strong agreement between the e-textile and conventional methods in measuring descriptive metrics of the signals, including area, power, mean, and root mean square. The paired data t-test did not reveal any statistically significant differences, and the Bland-Altman analysis indicated negligible bias between the measures recorded using the two methods. In addition, this study evaluated the wearability and comfort of the e-textile sleeve using the Comfort Rating Scale (CRS). Overall, the scores confirmed that the proposed device is highly wearable and comfortable, highlighting its suitability for everyday use in patient care.

Unlocking enhanced thermal conductivity in polymer blends through active learning

Polymers play an integral role in various applications, from everyday use to advanced technologies. In the era of machine learning (ML), polymer informatics has become a vital field for efficiently designing and developing polymeric materials. However, the focus of polymer informatics has predominantly centered on single-component polymers, leaving the vast chemical space of polymer blends relatively unexplored. This study employs a high-throughput molecular dynamics (MD) simulation combined with active learning (AL) to uncover polymer blends with enhanced thermal conductivity (TC) compared to the constituent single-component polymers. Initially, the TC of about 600 amorphous single-component polymers and 200 amorphous polymer blends with varying blending ratios are determined through MD simulations. The optimal representation method for polymer blends is identified, which involves a weighted sum approach that extends existing polymer representation from single-component polymers to polymer blends. An AL framework, combining MD simulation and ML, is employed to explore the TC of approximately 550,000 unlabeled polymer blends. The AL framework proves highly effective in accelerating the discovery of high-performance polymer blends for thermal transport. Additionally, we delve into the relationship between TC, radius of gyration (Rg), and hydrogen bonding, highlighting the roles of inter- and intra-chain interactions in thermal transport in amorphous polymer blends. A significant positive association between TC and Rg improvement and an indirect contribution from H-bond interaction to TC enhancement are revealed through a log-linear model and an odds ratio calculation, emphasizing the impact of increasing Rg and H-bond interactions on enhancing polymer blend TC.