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We study the behaviour, when p→+∞p\to +\infty , of the first p-Laplacian eigenvalues with Robin boundary conditions and the limit of the associated eigenfunctions. We prove that the limit of the eigenfunctions is a viscosity solution to an eigenvalue problem for the so-called ∞\infty -Laplacian. Moreover, in the second part of the article, we focus our attention on the p-Poisson equation when the datum ff belongs to L∞(Ω){L}^{\infty }\left(\Omega ) and we study the behaviour of solutions when p→∞p\to \infty .

We prove some results about existence of connecting and closed geodesics in a manifold endowed with a Kropina metric. These have applications to both null geodesics of spacetimes endowed with a null Killing vector field and Zermelo’s navigation problem with critical wind.

Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this scoping review, we provide a comprehensive overview of related research on proposed VLA methods, as well as identifying any gaps in the literature that could assist in describing new and helpful directions to the field. This review searched all relevant articles in five accessible databases -- Scopus, Web of Science, ERIC, ACM, and IEEE Xplore -- using 40 keywords. These studies were mapped, categorized, and summarized based on their objectives, the collected data, the intervention approaches employed, and the results obtained. The results determined what affordances the VLA tools allowed, what kind of visualizations were used to inform teachers and students, and, more importantly, positive evidence of educational interventions. We conclude that there are moderate-to-clear learning improvements within the limit of the studies' interventions to support the use of VLA tools. More systematic research is needed to determine whether any learning gains are translated into long-term improvements.

ImportanceThe ability to detect extracellular environmental conditions is a fundamental property of all life forms. Because microbial two-component sensor systems convert information about extracellular conditions into biochemical information that controls their behaviors, we evaluated how two-component sensor systems evolved within the deep Earth across multiple sites where abiotic and biotic properties vary. We show that these sensor systems remain abundant in microbial consortia at all subterranean sampling sites and observe correlations between sensor system abundances and abiotic (dissolved organic carbon variation) and biotic (consortia diversity) properties. These results suggest that multiple environmental properties may drive sensor protein evolution and highlight the need for further studies of metagenomic and geochemical data in parallel to understand the drivers of microbial sensor evolution.

Abstract The statistical properties of the detection events constituting the interference fringes at the output of an interferometer are well-known. Nevertheless, there is still no unified view of what is happening to a quantum system inside an interferometer. Strong measurements of path operators destroy the interference effect. In weak measurements, an observable is weakly coupled to a pointer system and the resulting weak values quantify the observable by minimally disturbing the system. Previous which-way experiments with weak measurements could extract either the real or imaginary part of a single weak value with each ensemble. Here, we present the simultaneous full complex quantification of two path weak values with a single ensemble in a Mach–Zehnder neutron interferometer. Magnetic fields, oscillating with different frequencies, change the energy state in each interferometer path. The time-dependent phase between the energy states distinctly marks each path. The resulting beating intensity modulation at the interferometer output gives both path weak values. For the present experiment, the weak values’ absolute value and phase directly describe the observed amplitude and phase of the intensity modulation.

Quantum dot (QD) solids are promising optoelectronic materials; further advancing their device functionality requires understanding their energy transport mechanisms. The commonly invoked near-field Förster resonance energy transfer (FRET) theory often underestimates the exciton hopping rate in QD solids, yet no consensus exists on the underlying cause. In response, we use time-resolved ultrafast stimulated emission depletion (STED) microscopy, an ultrafast transformation of STED to spatiotemporally resolve exciton diffusion in tellurium-doped cadmium selenide-core/cadmium sulfide-shell QD superlattices. We measure the concomitant time-resolved exciton energy decay due to excitons sampling a heterogeneous energetic landscape within the superlattice. The heterogeneity is quantified by single-particle emission spectroscopy. This powerful multimodal set of observables provides sufficient constraints on a kinetic Monte Carlo simulation of exciton transport to elucidate a composite transport mechanism that includes both near-field FRET and previously neglected far-field emission/reabsorption contributions. Uncovering this mechanism offers a much-needed unified framework in which to characterize transport in QD solids and additional principles for device design.

Abstract Background Assessment of undergraduate students using assessment instruments in the clinical setting is known to be complex. The aim of this study was therefore to examine whether two different assessment instruments, containing learning objectives (LO`s) with similar content, results in similar assessments by the clinical supervisors and to explore clinical supervisors’ experiences of assessment regarding the two different assessment instruments. Method A mixed-methods approach was used. Four simulated care encounter scenarios were evaluated by 50 supervisors using two different assessment instruments. 28 follow-up interviews were conducted. Descriptive statistics and logistic binary regression were used for quantitative data analysis, along with qualitative thematic analysis of interview data. Result While significant differences were observed within the assessment instruments, the differences were consistent between the two instruments, indicating that the quality of the assessment instruments were considered equivalent. Supervisors noted that the relationship between the students and supervisors could introduce subjectivity in the assessments and that working in groups of supervisors could be advantageous. In terms of formative assessments, the Likert scale was considered a useful tool for evaluating learning objectives. However, supervisors had different views on grading scales and the need for clear definitions. The supervisors concluded that a complicated assessment instrument led to limited very-day usage and did not facilitate formative feedback. Furthermore, supervisors discussed how their experiences influenced the use of the assessment instruments, which resulted in different descriptions of the experience. These differences led to a discussion of the need of supervisor teams to enhance the validity of assessments. Conclusion The findings showed that there were no significant differences in pass/fail gradings using the two different assessment instruments. The quantitative data suggests that supervisors struggled with subjectivity, phrasing, and definitions of the LO´s and the scales used in both instruments. This resulted in arbitrary assessments that were time-consuming and resulted in limited usage in the day-to-day assessment. To mitigate the subjectivity, supervisors suggested working in teams and conducting multiple assessments over time to increase assessment validity.

Sarcopenia is a prevalent condition with significant clinical implications, and it is expected to escalate globally, demanding for effective diagnostic strategies, possibly at an early stage of the disease. Imaging techniques play a pivotal role in comprehensively evaluating sarcopenia, offering insights into both muscle quantity and quality. Among all the imaging techniques currently used for the diagnosis and follow up of sarcopenia, it is possible to distinguish two classes: Rx based techniques, using ionizing radiations, and non-invasive techniques, which are based on the use of safe and low risk diagnostic procedures. Dual-energy x-ray Absorptiometry and Computed Tomography, while widely utilized, entail radiation exposure concerns. Ultrasound imaging offers portability, real-time imaging, and absence of ionizing radiation, making it a promising tool Magnetic Resonance Imaging, particularly T1-weighted and Dixon sequences, provides cross- sectional and high-resolution images and fat-water separation capabilities, facilitating precise sarcopenia quantification. Bioelectrical Impedance Analysis (BIA), a non-invasive technique, estimates body composition, including muscle mass, albeit influenced by hydration status. Standardized protocols, such as those proposed by the Sarcopenia through Ultrasound (SARCUS) Working Group, are imperative for ensuring consistency across assessments. Future research should focus on refining these techniques and harnessing the potential of radiomics and artificial intelligence to enhance diagnostic accuracy and prognostic capabilities in sarcopenia.

This study focuses on anti-trauma mats designed for buffaloes’ comfort, using as raw materials rubber powder from end-of-life tyres (ELTs) and an isocyanate-based polyurethane resin binder. The first part of the study focused on mat formulation. Whilst it was possible to select a unique combination of raw materials and design features, it was necessary to investigate the relationship between three critical parameters affecting mat consistency and therefore buffalo comfort: binder quantity, mat thickness, and desired final mat density (bulk). In order to quantitatively assess the variation in hardness, various combinations were investigated within well-defined ranges based on the relevant literature. The results obtained from nine selected combinations indicate that increases in the three critical parameters do not induce a real phase transition in the final product consistency, although the hardness suggests an increasing trend. The mats consistently exhibited a moderately soft/hard consistency, offering environmental benefits in terms of increased rubber usage and potentially reduced chemical binder, depending on the desired thickness. The selected mixture showed excellent resistance to heavy chemical loads, suggesting reliability for frequent cleaning operations. The second part of the study involved field trials of the mats with calves. This involved monitoring their weight gain and appetite levels over a 90-day period. The results showed excellent growth performance compared to uncoated grids (i.e., weight gain was approximately 20% higher at the end of the observation period); this was similar to that achieved with the use of straw bedding. However, compared to straw bedding, the mats (i) exhibit long-term durability, with no signs of wear from washing or trampling over the months of the trial, (ii) allow for quick and efficient cleaning, and (iii) enable companies to save on labour, material (straw), and waste disposal costs, while maintaining (or even improving) the same welfare levels associated with the use of straw.

Background: Lemierre syndrome is a rare, potentially fatal complication of oropharyngeal infections characterized by septic thrombophlebitis of the internal jugular vein. It primarily affects healthy adolescents and young adults. Its incidence declined after the antibiotic era, but it may have resurged in recent decades, likely due to judicious antibiotic use and increasing bacterial resistance. Prompt diagnosis and treatment are imperative to prevent significant morbidity and mortality. Methods: Lemierre syndrome has been called “the forgotten disease,” with a reported incidence of around 3.6 cases per million. The mean age at presentation is around 20 years old, though it can occur at any age. Lemierre Syndrome follows an oropharyngeal infection, most commonly pharyngitis, leading to septic thrombophlebitis of the internal jugular vein. F. necrophorum is the classic pathogen, though other organisms are being increasingly isolated. Metastatic infections, especially pulmonary, are common complications. Contrast-enhanced CT of the neck confirming internal jugular vein thrombosis is the gold standard for diagnosis. Long-course broad-spectrum IV antibiotics covering anaerobes are the mainstays of the disease’s treatment. Anticoagulation may also be considered. Mortality rates are high without treatment, but most patients recover fully with appropriate therapy. Conclusions: Lemierre syndrome should be suspected in patients with prolonged pharyngitis followed by unilateral neck swelling and fevers. Early diagnosis and prompt antibiotic therapy are key, given the potential for disastrous outcomes if untreated. An increased awareness of Lemierre syndrome facilitates its timely management.

Most research on sonoluminescence and sonochemistry has been conducted at acoustic frequencies above ∼20 kHz. Consequently, mathematical models for the dynamics of acoustically-driven bubbles have hardly been examined in the audible frequency spectrum. Here, we develop a new hybrid modelling approach that combines the rigour of the advection–diffusion model whilst retaining the simplicity of a reduced-order boundary layer model to predict phase-change, mass and heat transfer in an inertially collapsing bubble excited by audible sound. Differences in these approaches are explored through a thorough validation against experimental data obtained from ultra-high speed videos of bubble dynamics at 17.8 kHz. Our results indicate that, while the boundary layer model agrees well with the advection–diffusion model at high driving frequencies, there are significant deviations at lower frequencies, where the boundary layer model overpredicts parameters such as bubble size and quantity of trapped vapour while underpredicting others such as temperature and pressure. These deviations at lower frequencies is caused by an inaccurate estimation of the boundary layer thickness originating from the time-scale competition between diffusion and fast bubble wall motion. Our work questions the suitability of existing reduced-order models developed for ultrasonic frequencies when applied to the audible range, reinforcing that further research in the audible range is needed.

With profound effects on patient care, the role of artificial intelligence (AI) in radiomics has become a disruptive force in contemporary medicine. Radiomics, the quantitative feature extraction and analysis from medical images, offers useful imaging biomarkers that can reveal important information about the nature of diseases, how well patients respond to treatment and patient outcomes. The use of AI techniques in radiomics, such as machine learning and deep learning, has made it possible to create sophisticated computer-aided diagnostic systems, predictive models, and decision support tools. The many uses of AI in radiomics are examined in this review, encompassing its involvement of quantitative feature extraction from medical images, the machine learning, deep learning and computer-aided diagnostic (CAD) systems approaches in radiomics, and the effect of radiomics and AI on improving workflow automation and efficiency, optimize clinical trials and patient stratification. This review also covers the predictive modeling improvement by machine learning in radiomics, the multimodal integration and enhanced deep learning architectures, and the regulatory and clinical adoption considerations for radiomics-based CAD. Particular emphasis is given to the enormous potential for enhancing diagnosis precision, treatment personalization, and overall patient outcomes.

Issues of diversity and inclusion increasingly influence the purchasing process and brand loyalty of new generations of customers. Additionally, scholars and policymakers are calling for a more inclusive society and advocating for the integration of people with disabilities. However, there is a lack of research investigating these issues from a marketing perspective. Using a strategy of inquiry regarding in-depth multiple case studies from different players of the toy industry, this paper highlights how to set marketing strategies that develop and communicate new offerings by promoting both Marketing and Social Value and fostering the social inclusion of children with a disability. The proposed model contributes to the emerging literature of Inclusive Marketing and will help marketers implement a socially inclusive approach. [ABSTRACT FROM AUTHOR]