Next-generation mobile networks, such as 5G/6G, have envisioned the possibility of direct communication between user devices, known as Device-to-Device (D2D) communication. Given that in D2D networks, traffic is transmitted ad-hoc from device to device, the range and quality of service are directly dependent on the number of nodes forming the D2D network. Therefore, we need to incentivize users to participate in the network operation through appropriate compensation for the provided resources and work done. A D2D network formed this way is inherently decentralized, making blockchain the primary choice as a technology. In this paper, we propose a new blockchain-based protocol for active tracing of IP traffic via in-band network telemetry. The experiment demonstrates that the proposed protocol can record all nodes participating in traffic forwarding in the D2D network through active traffic monitoring. Blockchain-based microtransactions can use participation records provided by our protocol to incentivize users to expand and strengthen the D2D network.

The applications presented in this conference paper focus on the development of a mobile and web application serving as a planner with a focus on tracking persons with Down syndrome. These innovative technological solutions contribute to the development of independence and functionality for persons with Down syndrome while emphasizing the importance of inclusivity in society. In addition to focusing on organizing activities, the mobile and web applications provide support and facilitate daily tasks. The web application allows parents/guardians/teachers to add new activities to the planner and track the progress of these activities. On the other hand, the mobile application enables persons with Down syndrome to record their activities within the application, considering their specific challenges, and customizing the user interface to their needs.

Software development is implemented in several key phases, one of which is software testing. Software testing consists of selecting techniques for the purpose of finding software defects and bugs in the process of writing code. There are several ways and approaches that lead us to that purpose, with the goal of selecting the most adequate method in terms of cost, complexity, and efficiency. In this paper, we will take a deeper dive into mutation testing techniques. Mutation testing techniques are fault-based and focus more on test structures than the input data, which is considered the testing start point. The basic concept of mutation testing consists of a few steps, which will be covered in this paper, and metrics that measure how effective the tests really are. With a few code examples, we will show why code coverage, which is mostly taken as a measure while testing, is sometimes not the most reliable source and does not give a full picture when talking about the quality of written tests.

Embedded real-time clock systems have a large number of applications in practice. The main issue is the accuracy of time they show, which is why performing time synchronization is very important for their usability and reliability. This paper proposes an embedded real-time analogue clock that uses an AdaFruit NeoPixel LED ring for visualizing current time. Three different colors are used for showing hour, minute and second values, whereas different levels of brightness are used for describing accurate values of time to the level of milliseconds. An Ethernet LAN module is used for performing time synchronization via a remote NTP server. Dynamic synchronization interval change is used for removing the effect of the microcontroller clock error on the accuracy of the shown time. After being put to use, the system was able to perform multiple functions successfully, including the conveying of information to the user when the clock is out of sync.

This research delves into the crucial role of solar energy, particularly photovoltaic (PV) conversion, in the global shift towards renewable sources. Focusing on the stochastic nature of PV power plants, the study emphasizes fault ride-through operations and their repercussions on electrical power systems. A detailed modeling approach is employed using Electromagnetic Transient Program (EMTP) software to simulate a large-scale PV power plant connected to a high-voltage transmission network. The analysis encompasses various fault scenarios, shedding light on the resilience of PV systems and their broader impacts during faults. This investigation enhances the understanding of PV dynamics in fault conditions, providing valuable insights for sustainable energy systems.

This article aims to show the potential contribution of high-yielding rice varieties to achieve sustainable intensification in paddy farming, by focusing on a developing country. A comparative life cycle assessment of traditional vs. high-yielding varieties is carried out by comparing the area-based and yield-based results. Primary data are collected through a farm survey (49 farms in the Mazandaran province, Iran; spring 2018). The results highlight that high-yielding varieties can reduce the yield-scaled impacts. However, area-scaled impacts are subject to increase for most impact categories. Statistically significant trade-offs involve global warming potential (+13% per ha and −28% per t in high-yielding varieties) and fossil resource depletion (+15% per ha and −26% per t in high-yielding varieties). Pesticide management is the most alarming practice. High-yielding varieties increase pesticide consumption and related toxicity impacts both per t and per ha. This study is a new contribution to the literature by improving and broadening the mainstream productivity perspective of current life cycle assessment research about crop varieties. The lessons learnt from this study suggest that the trade-offs between yield-scaled and area-scaled impacts should be carefully considered by decision-makers and policymakers, especially in developing countries that, like Iran, are affected by the overexploitation of natural resources. Targeted policy and the development of farmer education and advisory services are needed to create the enabling conditions for farm management changes, including conscious use of production inputs while avoiding heuristics.

This paper describes a new smartphone-based colorimetric method for the determination of N-acetyl-L-cysteine and glutathione using a reaction with the Cu(II)–neocuproine complex. The reaction resulted in the formation of a yellow Cu(I)–neocuproine complex. Reaction solutions, prepared according to the selected optimal conditions, are placed in front of a light blue background, and a smartphone camera is used for digital image acquisition. The intensity of the blue RGB canal was selected for analytical response and determined using the free Color Grab mobile app. Also, absorbance at a wavelength of 450 nm was measured for all reaction solutions using a UV–Vis spectrophotometer. The proposed procedures allow the determination of both thiols in the linear dynamic range from 3.0 × 10–6 to 2.0 × 10–4 mol L−1 for a spectrophotometer as a detector, or from 6.0 × 10–6 to 2.0 × 10–4 mol L−1 for a smartphone as a detector. The obtained results indicate that the proposed method is accurate, simple, cost-effective, and applicable to the determination of thiols in pharmaceuticals.

Waste water in the galvanic process contains high concentrations of heavy metals that pose a direct danger to humans and the environment. Conventional methods for their removal are quite expensive and generate a large amount of waste. The development of new and improvement of existing methods for the removal of heavy metals from galvanic wastewater are the subject of many studies. Compared to other purification methods, the adsorption is becoming an increasingly popular method of wastewater purification, especially if the adsorbent is cheap, easily available and does not require any other treatment before use. Therefore, the aim of the work was to investigate the possibility of using natural bentonite for the removal of heavy metal ions from multi-component water systems of the galvanic industry. For this purpose, the physico-chemical characterization of natural bentonite was performed, and then the influence of pH value, time and temperature on the adsorption efficiency was examined. The results of adsorption showed that natural bentonite can be used as an adsorbent for the removal of heavy metal ions from waste galvanic waters, and that at pH 5 it achieves the maximum removal efficiency for Cu(II):Cr(III):Ni(II) ions in the percentage ratio 100 : 99.990 : 99.998. The results showed that the highest removal efficiency for Cu (II) ions was achieved in the first 10 minutes, and 20 minutes for Cr (III) and Ni (II) ions. The maximum efficiency of Cu (II) removal was achieved at all temperatures, while for Cr (III) 99.99% and Ni (II) 100% maximum efficiency was achieved at 35°C, which indicates that the adsorption process is endothermic. The experimental results of the adsorption of Cu (II) metal ions are in good agreement with the Langmuir and Freundlich theoretical models, while for Cr (III) and Ni (II) ions they are in better agreement with the Langmuir adsorption model.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age‐specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age‐specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome‐wide association study data, and the within‐pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Given the uncertainty surrounding how existing explainability methods for autonomous vehicles (AVs) meet the diverse needs of stakeholders, a thorough investigation is imperative to determine the contexts requiring explanations and suitable interaction strategies. A comprehensive review becomes crucial to assess the alignment of current approaches with varied interests and expectations within the AV ecosystem. This study presents a review to discuss the complexities associated with explanation generation and presentation to facilitate the development of more effective and inclusive explainable AV systems. Our investigation led to categorising existing literature into three primary topics: explanatory tasks, explanatory information and explanatory information communication. Drawing upon our insights, we have proposed a comprehensive roadmap for future research centred on (i) knowing the interlocutor, (ii) generating timely explanations, (ii) communicating human-friendly explanations and (iv) continuous learning. Our roadmap is underpinned by principles of responsible research and innovation, emphasising the significance of diverse explanation requirements. To effectively tackle the challenges associated with implementing explainable AV systems, we have delineated various research directions, including the development of privacy-preserving data integration, ethical frameworks, real-time analytics, human-centric interaction design and enhanced cross-disciplinary collaborations. By exploring these research directions, the study aims to guide the development and deployment of explainable AVs, informed by a holistic understanding of user needs, technological advancements, regulatory compliance and ethical considerations, thereby ensuring safer and more trustworthy autonomous driving experiences.

Background and introduction Statisticians rank oral and lip cancer sixth in global mortality at 10.2%. Mouth opening and swallowing are challenging. Hence, most oral cancer patients only report later stages. They worry about surviving cancer and receiving therapy. Oral cancer severely affects QOL. QOL is affected by risk factors, disease site, and treatment. Using oral cancer patient questionnaires, we use light gradient Boost Tree classifiers to predict life quality. Methods DIAS records were used for 111 oral cancer patients. The European Organisation for Research and Treatment of Cancer’s QLQ-C30 and QLQ-HN43 were used to document the findings. Anyone could enroll, regardless of gender or age. The IHEC/SDC/PhD/OPATH-1954/19/TH-001 Institutional Ethical Clearance Committee approved this work. After informed consent, patients received the EORTC QLQ-C30 and QLQ-HN43 questionnaires. Surveys were in Tamil and English. Overall, QOL ratings covered several domains. We obtained patient demographics, case history, and therapy information from our DIAS (Dental Information Archival Software). Enrolled patients were monitored for at least a year. After one year, the EORTC questionnaire was retaken, and scores were recorded. This prospective analytical exploratory study at Saveetha Dental College, Chennai, India, examined QOL at diagnosis and at least 12 months after primary therapy in patients with histopathologically diagnosed oral malignancies. We measured oral cancer patients’ quality of life using data preprocessing, feature selection, and model construction. A confusion matrix was created using light gradient boosting to measure accuracy. Results Light gradient boosting predicted cancer patients’ quality of life with 96% accuracy and 0.20 log loss. Conclusion Oral surgeons and oncologists can improve planning and therapy with this prediction model.

In this paper we derive some new identities involving the Fibonacci and Lucas polynomials and the Chebyshev polynomials of the first and the second kind. Our starting point is a finite trigonometric sum which equals the resolvent kernel on the discrete circle with $m$ vertices and which can be evaluated in two different ways. An expression for this sum in terms of the Chebyshev polynomials was deduced in \cite{JKS} and the expression in terms of the Fibonacci and Lucas polynomials is deduced in this paper. As a consequence, we establish some further identities involving trigonometric sums and Fibonacci, Lucas, Pell and Pell-Lucas polynomials and numbers, thus providing a"physical"interpretation for those identities. Moreover, the finite trigonometric sum of the type considered in this paper can be related to the effective resistance between any two vertices of the $N$-cycle graph with four nearest neighbors $C_{N}(1,2)$. This yields further identities involving Fibonacci numbers.

Background: Understanding the relationship between teachers’ physical activity (PA) and quality of life (QoL), which is impacted by work-related stress, could help develop guidelines for improvement. The purpose of this study was to investigate the impact of physical activity on high school teachers’ quality of life and the differences in QoL and PA between male and female teachers. Methods: The sample consisted of 499 respondents (193 men and 306 women), all working in the educational system. The International Physical Activity Questionnaire (short form) was used for PA assessment, and the WHOQoL questionnaire to measure QoL. Results: Physical health and Psychological health domains were areas where male teachers scored better (p < 0.01, both), while female teachers had higher scores in Social relationships domain (p < 0.05). Regression analysis showed that PA affects Physical health: Sig. = 0.056; Psychological health: Sig. = 0.000; Social relationships: Sig. = 0.001; Environment: Sig. = 0.021 in men, and Physical health (Sig. = 0.009) and Psychological health (Sig. = 0.039) in women. Conclusions: The findings of this study allow us to conclude that, whereas female teachers’ PA primarily impacts their physical and psychological domain, male teachers’ PA has an impact on their overall QoL.

Messaging apps, such as Telegram and WhatsApp, are routinely used to communicate, chat and make decisions. Group Recommender Systems (GRSs) have been introduced as self standing tools to support group interactions and decision-making. We present here a TelegramBot, named CHARM, that supports groups to make a decision on an arbitrary topic by leveraging GRSs techniques. CHARM helps elicit the group members’ preferences, ranks the items that the members have suggested to be considered, provides a summary of the current status of the discussion, and finally recommends a fair choice. A focus group study has revealed that the designed functionality includes features that users expect to find in a bot aimed at supporting group decision-making.