Search Results (3,844)

In this paper we investigate the chaos of a generalized perturbed Lotka–Volterra model based on considerations by other studies used in the literature. The model, containing N number of free parameters, could be of interest to specialists working in the fields of biological applications, chemistry, reaction kinetics, biostatistics, games theory, etc. With a specially developed software product, we generate the Melnikov equation $M(t)=0$ and examine all its zeros. This opens up an opportunity for the researcher to correctly understand and formulate the classical Melnikov criterion for the possible occurrence of chaos in the dynamical system. Several simulations are composed. We also demonstrate some specialized modules for investigating the dynamics of the proposed model. We further develop our model using the exponential form of the sine function. Thus, the perturbation can be interpreted as a term dependent on the characteristic function of a probability distribution. Although the original formulation leads to a distribution stated on a discrete domain, we can easily generalize the results for arbitrary distributions. Some particular examples are provided. Full article

A device under test, when applied to the test rig, often does not come with much information about its mechanical properties to the user. There are different applications in which specific properties of the device under test are of interest to the user. Therefore, a suitable model approach and a parameterisation method are required. If there is a torsional model of the plant, including the device under test and the load machines, it can, for example, be used in a model predictive control architecture. The focus of the publication is on the frequency range of driveability ($f<$ 30 Hz) and, in particular, on the phenomenon of the vehicle shuffle mode, which is important for driving comfort. The model approach has to map these characteristics. To make this possible, the publication presents a suitable, simplified modelling approach for electric powertrains in the hardware-in-the-loop environment and the possibility of indirect parameterisation for the moment of inertia and stiffness. The investigations demonstrate that the model possesses the essential eigenmodes and frequencies observed in the measurements on the test rig. Taking into account extensions, the model enables the incorporation of the properties of an open differential, including delta speeds. The natural frequency matches the measured one with deviations less than 1%. The results also show that the parameters are smaller than assumed. The authors will revise the developed method on this basis to achieve higher information value and a better confidence interval. This further work will discuss the influence of the confidence interval on the resulting parameters. Full article

Kolmogorov complexity asks whether a string can be outputted by a Turing Machine (TM) whose description is shorter. Analogously, a real number is considered computable if a Turing machine can generate its decimal expansion. The modern $ϵ$-approximation definition of computability, widely used in practical computation, ensures that computable reals are constructively closed under addition. However, Turing’s original 1936 digit-by-digit notion, which demands the direct output of the $n\text{-th}$ digit, presents a stark divergence. Though the set of Turing-computable reals is not constructively closed under addition, we prove that a Turing machine capable of computing $x+y$ non-constructively exists. The core constructive computational barrier arises from determining the ones digit of a sum like $0.33\overline{3}+0.66\overline{6}=0.99\overline{9}=1.00\overline{0}$. This particular example is ambiguous because both $0.99\overline{9}$ and $1.00\overline{0}$ are legitimate decimal representations of the same number. However, if any of the infinite number of 3s in the first term is changed to a 2 (e.g., $0.33\dots 32\dots +0.66\overline{6}$), the sum’s leading digit is definitely zero. Conversely, if it is changed to a 4 (e.g., $0.33\dots 34\dots +0.66\overline{6}$), the leading digit is definitely one. This implies an inherent undecidability in determining these digits. Recent papers and our work address this issue. Hamkins provides an informal argument, while Berthelette et al. present more complicated formal proof, and our contribution offers a simple reduction to the Halting Problem. We demonstrate that determining when carry propagation stops can be resolved with a single query to an oracle that tells if and when a given TM halts. Because a concrete answer to this query exists, so does a TM computing the digits of $x+y$, though the proof is non-constructive. As far as we know, the analogous question for multiplication remains open. This, we feel, is an interesting addition to the story. This reveals a subtle but significant difference between the modern $ϵ$-approximation definition and Turing’s original 1936 digit-by-digit notion of a computable number, as well as between constructive and non-constructive proof. This issue of computability and numerical precision ties into algorithmic information and Kolmogorov complexity. Full article

The open ocean cage aquaculture system is facing considerable challenges with disease outbreaks resulting from over-farming and the rise of resistance to antimicrobial treatment. However, the environmental consequences of antibiotic usage, including ecological contamination and the acceleration of antimicrobial resistance, underscore the urgent need for sustainable alternatives in aquaculture disease management. Lipopeptides, which are a compound that can be produced by marine bacteria such as Bacillus amyloliquefaciens or Bacillus subtilis, could represent a new solution. This review article comprehensively evaluates the feasibility of marine bacterial lipopeptides for sustainable disease management in open sea cage aquaculture. Lipopeptides, including surfactins, fengycins, iturins, and the clinically used daptomycin, have notable antiviral, antifungal, and antimicrobial properties, and can have positive effects on the immune system. Notably, lipopeptides have a remarkable antioxidant profile and excellent free radical scavenging ability, making them interesting candidates for improving disease resistance in fish relating to oxidative stress. The surfactins and iturins have amphiphilic structure and can destabilize pathogen cell membranes, inhibit biofilm formation and elicit host immune responses. This represents a paradigm shift in targeting multiple pathogens of aquaculture like Vibrio spp. and Aeromonas spp. Surfactins and iturins show broad-spectrum activity, while fengycins are selectively active against fungal threats. Daptomycin, which is primarily derived from Streptomyces, demonstrates the potential of the lipopeptide class to be developed therapeutically, which is something that tends to be overlooked. Unlike synthetic antibiotics, they are also biodegradable; therefore, there is much less environmental impact from lipopeptides. The complexity of the structure may have also some impact on the rate of development of resistance, if any. Their commercialization is possible; however, the main hurdles that need to be solved to improve aquaculture are the biologically scalable production, the economically viable purification, and the stability for practical application at sea. Integrating lipopeptides into disease management systems could also ensure the sustainability of open ocean cage aquaculture and reduce unnecessary antibiotic application. Full article

Background: Rotator cuff-related shoulder pain (RCRSP) is a prevalent musculoskeletal disorder treated by physiotherapists. Although international guidelines support active, exercise-based management, little is known about current physiotherapy practices in Cyprus. Aim: To investigate physiotherapy management practices for RCRSP in Cyprus, assess adherence to recommended clinical guidelines, and compare findings with practices in other countries. Methods: A cross-sectional online survey was conducted among Cypriot physiotherapists between June and July 2024. An English case vignette-based questionnaire, adapted from validated international surveys, examined demographics, clinical reasoning, treatment preferences, and guideline adherence. Descriptive statistics summarised responses; chi-square tests and logistic regression identified associations between demographics and clinical decisions. Content analysis was performed on open-ended responses. Results: A total of 143 physiotherapists completed the survey. Most adhered to guideline-recommended care, with 99.3% (n = 142/143) prescribing exercise and 100% (n = 143/143) providing patient education. Conservative management was preferred, with 64.3% (n = 91/143) not recommending imaging, 72.0% (n = 103/143) not recommending injections, and 73.4% (n = 104/143) not recommending surgical referrals. Significant associations were found between special interest in shoulder conditions and recommendations for surgery (χ² = 4.937, p = 0.026) and injections (χ² = 9.143, p = 0.002). Physiotherapists recommending surgery were nearly seven times more likely to suggest MRI (Exp(B) = 6.944, p < 0.001). Conclusions: Cypriot physiotherapists predominantly use exercise and education for the management of RCRSP, aligning closely with international recommendations. Conservative strategies were favoured, with limited use of imaging, injections, and surgical referrals. However, variation in clinical decision-making, particularly regarding referrals and imaging, indicates partial adherence to best practice and highlights opportunities for enhanced guideline implementation and targeted clinical training. Full article

Microalgae are photosynthetic microorganisms capable of fixing CO₂ to produce O₂ and a wide variety of metabolites of interest. Attempts have been made to describe their growth dynamics using mathematical models; however, these models fail to fully represent the dynamics of this bioprocess. Therefore, achieving maximum biomass production in the shortest possible time represents a control challenge due to the nonlinear and time-varying dynamics. Some classic control strategies implemented for this bioprocess are totally or partially dependent on a mathematical model, resulting in controllers with low performance, implementation complexity, and limited robustness. This is where the Virtual Reference Feedback Tuning (VRFT) approach becomes relevant, as it is a model-free control strategy. VRFT is based on the iterative generation of a virtual reference with the aim of minimizing steady-state error, without requiring an explicit model of the bioprocess. Its implementation involves the collection of experimental data in open loop, the minimization of a cost function in closed loop, and the linearization of the system around a stable equilibrium point. This work presents the design and implementation of a VRFT-based control strategy applied to the closed cultivation of the microalga Scenedesmus obliquus UTEX 393 in three flat photobioreactors at laboratory scale. The variables controlled using this strategy were temperature, photosynthetically active light intensity, and level. The experimental results showed that the pre-established references were met. A steady-state temperature of 25 ± 0.625 °C, a PAR (Photosynthetically Active Radiation) light intensity of 100 ± 5 µmol·m⁻²·s⁻¹, and level control that ensured a constant volume of the culture medium were achieved. This suggests that VRFT is a viable control alternative for this type of bioprocess under nominal conditions. Full article

The thematic processing of pseudocolor composite images, especially those created from remote sensing data, is of considerable interest. The set of spectral classes comprising such images is typically described by a nominal scale, meaning the absence of any predetermined relationships between the classes. However, in many cases, images of this type may contain elements of a regular spatial order, one variant of which is a gradient structure. Gradient structures are characterized by a certain regular spatial ordering of spectral classes. Recognizing gradient patterns in the structure of pseudocolor composite images opens up new possibilities for deeper thematic images processing. This article describes an algorithm for analyzing the spatial structure of a pseudocolor composite image to identify gradient patterns. In this process, the initial nominal scale of spectral classes is transformed into a rank scale of the gradient legend. The algorithm is based on the analysis of Moore neighborhoods for each image pixel. This creates an array of the prevalence of all types of local binary patterns (the pixel’s nearest neighbors). All possible variants of the spectral class rank scale composition are then considered. The rank scale variant that describes the largest proportion of image pixels within its gradient order is used as a final result. The user can independently define the criteria for the significance of the gradient order in the analyzed image, focusing either on the overall statistics of the proportion of pixels consistent with the spatial structure of the selected gradient or on the statistics of a selected key image region. The proposed algorithm is illustrated using analysis of test examples. Full article

The purpose of this systematic review was to synthesize the literature to better understand how the field researched principal preparation in relation to race and racism. Using a critical race theory methodological lens (CRM), we analyzed 36 studies of current candidates or recent graduates with an emphasis on the research design and methods. The research chosen for inclusion was (1) empirical, (2) focused on principal preparation programs in the U.S., (3) focused on preparing candidates around issues related to race and racism, and (4) published between 2012 and 2024. Literature was drawn from three major databases that include journals in the field of educational leadership, ERIC, ProQuest, and Education Full Text, in the summer of 2025. It is important to note that our literature search focusing on peer-reviewed articles poses a limitation in terms of the comprehensiveness of the sampled literature, thus excluding potentially important information sources. To analyze the studies, we created a scoring rubric to assess the degree to which each article addressed each CRM tenet. To assess risk of bias, each article was scored by two authors, and the third author also scored the article if the first two disagreed. Our findings show that focus on race and racism was present in most studies reviewed, and almost half centered on the experiences of candidates of color. However, most of the studies reviewed conformed to traditional research paradigms and methods, as illustrated by choices related to frameworks, methods, and data sources. We offer recommendations for researchers of principal preparation who are interested in more critical work related to race and racism, and we argue for increased opportunities for scholars to meet, discuss, and collaborate across institutions around how they are studying leadership preparation for racial equity. The review is registered through Open Science Framework. Full article

Transnational higher education programs in engineering face persistent challenges in sustaining student motivation, engagement, and learning outcomes. Cultural norms, linguistic barriers, and traditional pedagogies often reinforce teacher-centred instruction, limiting active participation. This mixed-methods action research investigates how problem-based learning (PBL) supported by interactive handouts affects students’ motivation, engagement, and perceived learning outcomes in civil engineering programs, delivered in a Sino–UK university context. Drawing upon socio-cultural constructivism, Self-Determination Theory (SDT), and the multidimensional framework of student engagement, the study repositions motivation and engagement as central drivers of learning. Quantitative data from student surveys (N = 49) and qualitative responses from open-ended questions were analysed to identify patterns of perceived improvement and underlying mechanisms. Findings reveal that the scaffolded PBL and interactive tasks enhanced students’ intrinsic motivation, collaborative engagement, and self-reported understanding of key concepts. Students described the activities as “more interesting,” “interactive,” and “helpful for exam preparation.” In total, 92% agreed that the handouts improved their understanding of core concepts, while 78% of students reported being more motivated to participate in class, and 92% of students expressed that the handouts enhanced the learning environment. While self-reported perceptions limit causal claims, the findings contribute to a growing body of evidence advocating for learner-centred, motivationally informed pedagogies in transnational engineering education. Full article

Ultra-Wideband (UWB) technology enables centimeter-level indoor positioning, but it remains highly sensitive to channel dynamics, multipath and Non-Line-of-Sight (NLoS) propagation. Recent studies increasingly apply Machine Learning (ML) methods to address these issues by modeling nonlinear channel behavior and mitigating ranging bias. This paper presents a comprehensive review and provides a critical synthesis of 169 research works published between 2020 and 2024, offering an integrated overview of how ML techniques are incorporated into UWB-based Indoor Positioning Systems (IPSs). The studies are grouped according to their functional objective, learning algorithm, network architecture, evaluation metrics, dataset, and experimental setting. The results indicate that most approaches apply ML to channel classification and ranging error mitigation, with Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and hybrid CNN–Long Short-Term Memory (LSTM) architectures being among the most common choices due to their ability to capture spatial and temporal patterns in the Channel Impulse Response (CIR). Despite the reported accuracy improvements, scalability and cross-environment generalization remain open challenges, largely due to the scarcity of public datasets and the lack of standardized evaluation protocols. Emerging research trends highlight growing interest in transfer learning, domain adaptation, and federated learning, along with lightweight and explainable models suitable for embedded and multi-sensor systems. Overall, this review summarizes the progress made in ML-driven UWB localization, identifies current gaps, and outlines promising directions toward more robust and generalizable indoor positioning frameworks. Full article

Many tropical islands and coastal communities suffer from high energy costs, unreliable electrical supplies, poverty, and underemployment, which are all exacerbated by climate change. Multi-use Ocean Thermal Energy Conversion (OTEC) systems could align with the goals and values of these underserved and remote communities. Developing multi-use OTEC systems could help meet the United Nations’ Sustainable Development Goals #7 (Affordable and Clean Energy) and #13 (Climate Action). Multiple uses of OTEC water and power are explored in this study, including seawater air conditioning, desalination, support for aquaculture in tropical regions, and other uses. A use case for an onshore OTEC plant at the location of the existing OTEC plant in Kona, Hawaii, is examined to determine if sufficient thermal resources exist for OTEC power generation year-round, and to determine the potential for each value-added use. Potential environmental effects are evaluated using a new open-source numerical model for determining the risk from the discharge of large volumes of cold deep seawater in the ocean. Companies currently using the cold deep seawater pumped ashore at the Kona location were surveyed to determine their dependence on and interest in expanded OTEC and cold-water availability at the site. The analysis indicates that multi-use OTEC is feasible, with seawater air conditioning (SWAC), aquaculture, and desalination being the most compatible immediate additions, while future potential exists for adding extraction of critical minerals from seawater and e-fuel generation. Full article

Background: Periprosthetic joint infections (PJI) represent a serious complication following joint arthroplasty and require, in addition to surgical intervention, a targeted antibiotic therapy. The aim of this study was to compare microbiological recommendations for the antibiotic treatment of fictitious PJI patients generated by an artificial intelligence (AI) system with those of an interdisciplinary team (IT) consisting of microbiologists and orthopedic surgeons. The differences between the recommendations suggested by AI and the IT were analyzed with regard to the suggested agents and duration of antibiotic therapy. Methods: Based on meta-analyses, a cohort of 100 fictitious patients with acute early- and acute late-onset PJI was created, reflecting the typical demographic data, comorbidities and pathogen profiles of such a population. This information was input into the AI system ChatGPT (OpenAI, GPT-5 “Thinking mode” accessed via ChatGPT Plus, San Francisco, CA, USA) to generate corresponding recommendations. The objective was to use these profiles to obtain recommendations for definitive antibiotic therapy, including daily dosage, intravenous and oral treatment durations. Simultaneously, the same fictitious patient data were reviewed by the IT to produce their own recommendations. Results: The results revealed both concordances and discrepancies in the selection of antibiotics. Notably, in cases involving multidrug-resistant organisms and more complex clinical scenarios, the AI-generated recommendations were incongruent with those of the IT, with estimated percentage agreement ranging from 0–33%. In straightforward clinical scenarios with monomicrobial infections, AI reached an estimated percentage agreement of up to 57% (95%-CI [0.47–0.67]). Furthermore, AI consistently recommended 12 weeks of therapy duration vs. six weeks usually recommended by the IT. Conclusions: The study provides important insights into the potential and limitations of AI-assisted decision-making models in orthopedic infection treatments. Consultation of AI is universally accessible at all times of day, which may offer a significant advantage in the future for the treatment of PJI. This kind of application will be of particular interest for institutions without in-house microbiology services. However, from our perspective, the current level of incongruence between the AI-generated recommendations and those of an experienced interdisciplinary team remains too high for this approach to be clinically implemented at this time. Furthermore, AI lacks transparency regarding the sources it uses to inform about its decision-making and therapeutic recommendations, currently carries no legal weight and clinical implementation is severely hindered by restrictive privacy laws regarding health care data. Full article

The relationship between insect diversity and crop production has been of continuous scientific interest. Understanding insect community dynamics using various sampling and monitoring methods at different crop phenology stages is crucial for enhancing pest management and ecosystem service functioning. The present study assessed the influence of four trap types (Blue, Yellow, White, and Malaise) applied at four tomato developmental stages (start of planting, flowering, flowering fruit development and harvest) on insect diversity in northeastern Tunisian open-field conditions. A total of 1771 insect individuals belonging to seven orders and 31 families were trapped, with the order Hymenoptera being the most common in the sampled plots, which was represented by 25 families. Trap type exerted a strong effect on both abundance and alpha diversity parameters. Yellow pan traps showed the highest diversity, with family richness (S) ranging from 1 to 16, Shannon diversity (H) reaching 2.54, Simpson (Is) diversity ranging from 0.72 to 0.90 and Pielou’s evenness (J) ranging from 0.83 to 0.98. Blue and white traps displayed intermediate diversity (Blue: S = 6 and H = 1.7; White: S = 7 and H = 1.6), while Malaise traps captured the least diverse assemblages (S = 4, H = 1.2 and Is = 0.65). These differences were highly significant (p < 0.05). Phenological stage significantly structured Hymenoptera diversity. Richness peaked at the start of planting (S = 1–16 and H up to 2.54) and declined sharply at harvest (S = 1–6). Pollinator families (Apidae, Halictidae, Megachilidae) were the most abundant during flowering, whereas parasitoid families (Braconidae, Eulophidae) dominated during the fruit development stage. Beta diversity analyses (NMDS, stress = 0.25) and PERMANOVA showed that trap type and phenological stage jointly explained 15.5% of the variation in community composition (R² = 0.155, p = 0.014). Although a strong taxonomic overlap among traps was observed, Indicator Value analysis revealed significant trap-specific associations, including the family Andrenidae with Blue traps and the family Scoliidae with White and Yellow traps. Overall, the results of the present study demonstrate that both trap type and crop phenology significantly influence insect population diversity. A multi-trap sampling strategy combining colored pan traps and Malaise traps could be recommended to accurately characterize insect communities and associated ecosystem services in Mediterranean open-field tomato systems. Full article

Background: Early childhood caries is defined as a carious disease affecting primary teeth in children under 6 years of age. It may lead to pain, infections, and difficulties with eating. Despite its burden, evidence on simple, non-invasive preventive approaches which can be implemented both in dental clinics and outreach services is fragmented. The aim of this review was to identify and map such methods for the secondary and tertiary prevention of ECC and to define priorities for future research. Material and Methods: The scoping review followed the PCC framework (Population–Concept–Context). Two databases were searched: PubMed and Scopus. A systematic search was conducted in PubMed and Scopus between 1 August and 30 September 2025. Eligible studies included children under 6 years of age with existing carious lesions, evaluated non-invasive methods for secondary and tertiary ECC prevention (such as sodium fluoride (NaF), silver diamine fluoride (SDF), nano-silver fluoride (NSF), and motivational techniques), requiring simple armamentarium, and reported data on the effectiveness in the context of ECC. Only publications from the past 5 years, available in English, and in open access, were considered. The results of the analysis were summarized narratively, outlining intervention types based on their characteristics, impact, and usage context. Results: Fifteen studies were included. Most were randomized controlled trials (eight studies), focusing primarily on silver diamine fluoride (SDF), often compared with other non-invasive methods, followed by systematic reviews (two studies), reviews (two studies), cross-sectional studies (two articles), and one qualitative study. Only one publication examined the use of motivational interviewing within the context of ECC. While the evidence on non-invasive approaches is growing, significant gaps remain. Small sample sizes, short follow-up periods, and heterogenous interventions and outcomes limit comparability. To strengthen the evidence base, future studies should recruit larger cohorts, adhere to standardized procedures, and use consistent reporting. Conclusions: The majority of studies focused on SDF, reflecting the increasing interest in its use. Research on motivational interviewing in ECC is particularly scarce. Further research under standardized conditions is needed to enable reliable comparisons across treatment protocols. Full article

Bio-based fertilisers (BBFs), produced from various types of biological waste using different processing methods, have demonstrated encouraging levels of agronomic efficiency and environmental benefits, consistent with the principles of sustainable development (SD). Nevertheless, bringing these newly developed products to market remains difficult due to limited farmer awareness, perceived risks, and regulatory uncertainties. In this paper, we examine the attitudes, opinions, and awareness of farmers regarding the use of various BBFs in their fertilisation practices. We applied a survey research method, using the Paper and Pen Personal Interview (PAPI), and answers were collected by agricultural advisors. A questionnaire, consisting of open, closed, and Likert scale questions, focusing on general information about farmers, current practices regarding fertiliser use, and the determinants of fertiliser choice, was used. Descriptive statistics, cross-tabulations, chi-square tests, Cramer’s V coefficients, 95% confidence intervals, and McNemar’s test were used to analyse the data. This study was conducted in all 16 voivodeships in Poland, collecting a total of 800 responses. Factors influencing the negative or positive attitude of farmers toward this practice were identified. Currently, mineral fertilisers remain the dominant choice among Polish farmers due to their accessibility, cost-effectiveness, and agronomic performance. There is observed growing, albeit cautious, interest in alternative fertilisation strategies and the correct understanding of sustainable agriculture practices. About half of farmers expressed willingness to partially replace mineral fertilisers with organic options, but only a minority showed interest in adopting BBFs. The findings indicate that concerns about contaminants, heterogeneous quality, limited availability, and regulatory uncertainty continue to constrain interest in BBFs. Although respondents recognised potential environmental benefits, economic and agronomic considerations remained the primary drivers of decision-making. As the survey was conducted in late 2021, the results reflect pre-2022 market conditions and should be interpreted as a baseline rather than a direct indication of current attitudes. Overall, this study provides insights into behavioural and structural factors influencing fertiliser use in Poland and highlights areas where further policy, advisory, and market developments may help support more sustainable nutrient management. Full article