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.

The development of communication systems for in-telligent transportation systems (ITS) relies on their performance in high-mobility scenarios. Such scenarios introduce rapid fluctuations in wireless channel properties. As a promising solution for vehicle-to-everything (V2X) communication, the orthogonal time frequency space (OTFS) approach has emerged. Nevertheless, the performance of OTFS systems is closely tied to time- and frequency diversity of the wireless propagation channel. However, there is a lack of understanding of the stationarity of the wireless channels, especially in the millimeter wave (mmWave) frequency bands. In this paper, we address this research gap by conducting a comprehensive stationarity analysis of measured sub-6 GHz and mmWave high-speed wireless channels. We evaluate the spatial stationarity of a scenario, where the transmitter is moving at high velocity. Furthermore, we investigate the influence of the transmit antenna orientation on the channel spatial stationarity. We could show that the spatial stationarity is proportional to the wavelength.

The increase in soil salinity has a negative effect on the growth and yield of plants. Mitigating the negative effects of soil salinity is therefore a difficult task and different methods are being used to overcome the negative effects of salt stress on crop plants. One of the often-used approaches is seed priming that can increase plants’ vigor and resilience. In this paper, we tested the effects of hydropriming, proline priming, and salicylic acid priming on the mitigation of the negative effects of salt stress on two bell pepper varieties (Capsicum annuum L.): Herkules and Kurtovska kapija. Sweet bell pepper seeds were primed following desiccation to achieve the original water content, and subsequently cultivated in salt-supplemented medium. The positive effects on vigor (in the form of increased germination and seedling establishment) as well as on level of tolerance for salt stress were recorded for both cultivars. The positive effects varied between the priming treatments and pepper cultivar used. The results of germination, seedling performance, photosynthetic pigments, and osmolytes were measured for seedlings grown from unprimed and primed seeds with under 0, 25, and 50 mM of NaCl. Both cultivars demonstrated greater germination when primed with proline and salicylic acid, while the Herkules cultivar demonstrated a higher tolerance to salt when proline was used as the priming agent. Priming with salicylic acid and proline in the seed improved germination and seedling performance, which could be related to the increase in proline content in the seedlings.

The objective of this study was to assess the impact that diets supplemented with grape seed cake rich in polyphenols had on lactating goats. The study investigated the quantity and quality of goat milk, the metabolic profile of blood, and the antioxidative status. The study involved 24 French Alpine dairy goats throughout their lactation period. The goats were, on average, 5 years old (±three months) and in the fourth lactation. The experiment lasted for 58 days. The control group (CON) had a diet without grape seed cake (GSC). The experimental groups were given a diet containing 5% and 10% GSC on a dry matter basis (GSC5 and GSC10, respectively). A slightly higher milk production, as well as protein and fat milk content, were found in GSC5 and GSC10, but the differences were not significant. Goat milk in the GSC10 group exhibited significantly higher activity of superoxide dismutase and glutathione reductase, as well as decreased concentrations of GUK and SCC. The feeding treatments did not affect significant differences in hematological and biochemical indicators, except for the BHB content, which can be associated with a higher energy value of feed containing GSC. There was an observed elevation in the activity of SOD within the blood of GSC5, and GSC10 was measured as well. The determined changes justify the supplementation of GSC rich in polyphenols to goat feed, especially in the amount of 10%, as it can reduce stress caused by lactation, which is known as a very stressful production period for animals.

Background To evaluate long-term outcomes and prognostic factors in patients with juvenile idiopathic arthritis (JIA), presenting as oligoarthritis, who received IAC as the first treatment for their disease. Methods We conducted retrospective study at the University Children’s Hospital Ljubljana, Slovenia, from January 2015 to May 2023 in children with JIA, clinically presenting as oligoarthritis receiving intra-articular corticosteroid injection (IAC) as the initial treatment. Patient and treatment data were collected, and the outcomes were categorized into three groups based on the later need for therapy: no therapy needed, only additional IAC needed and systemic therapy needed. The last group was further divided based on the requirement of bDMARD. Log-rank (Mantel-Cox) survival analyses compared different outcome groups. Results We included 109 patients with JIA, presenting as oligoarthritis (63% female), who were first treated with IAC. The mean age at IAC was 8.0 years, with a 4.3-year follow-up. Notably, 38.5% of patients did not require additional therapy post-IAC, whereas 15.5% required only additional IAC. Systemic therapy, mainly methotrexate (MTX), was necessary for 45.9% of patients, initiated in average 7.8 months post-IAC. Biologic therapy was initiated in 22% in average 2.2 years post-IAC. Number of injected joints correlated with the need for biologics. At the last follow-up, 88.9% had inactive disease. ANA positivity ( P  = 0.049, chi square 3.89) and HLA B27 antigen presence ( P  = 0.050, chi square 3.85) were associated with the need for systemic therapy. A subgroup of children older than 8 years, ANA and HLA B27 negative required significantly less systemic (25.8%) and biologic therapy (9.6%) compared to other patients ( p  = 0.050, chi square 3.77). Conclusion Almost 40% of children with oligoarticular JIA requiring IAC did not progress to chronic disease. Younger age, ANA positivity, and HLA B27 presence were predictive factors for systemic therapy, while the number of injected joints predicted the future need for biologic therapy.

A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a ‘guide towards substantiating freedom from infection’ that describes both all assumptions-limitations and available methods that can be applied in different settings.

In robot manipulation, Reinforcement Learning (RL) often suffers from low sample efficiency and uncertain convergence, especially in large observation and action spaces. Foundation Models (FMs) offer an alternative, demonstrating promise in zero-shot and few-shot settings. However, they can be unreliable due to limited physical and spatial understanding. We introduce ExploRLLM, a method that combines the strengths of both paradigms. In our approach, FMs improve RL convergence by generating policy code and efficient representations, while a residual RL agent compensates for the FMs' limited physical understanding. We show that Explorllm outperforms both policies derived from FMs and RL baselines in table-top manipulation tasks. Additionally, real-world experiments show that the policies exhibit promising zero-shot sim-to-real transfer. Supplementary material is available at https://explorllm.github.io.

Building embodied AI systems that can follow arbitrary language instructions in any 3D environment is a key challenge for creating general AI. Accomplishing this goal requires learning to ground language in perception and embodied actions, in order to accomplish complex tasks. The Scalable, Instructable, Multiworld Agent (SIMA) project tackles this by training agents to follow free-form instructions across a diverse range of virtual 3D environments, including curated research environments as well as open-ended, commercial video games. Our goal is to develop an instructable agent that can accomplish anything a human can do in any simulated 3D environment. Our approach focuses on language-driven generality while imposing minimal assumptions. Our agents interact with environments in real-time using a generic, human-like interface: the inputs are image observations and language instructions and the outputs are keyboard-and-mouse actions. This general approach is challenging, but it allows agents to ground language across many visually complex and semantically rich environments while also allowing us to readily run agents in new environments. In this paper we describe our motivation and goal, the initial progress we have made, and promising preliminary results on several diverse research environments and a variety of commercial video games.