Search Results (14)

Seaweed has historically been essential for coastal communities worldwide. Following a period of decline in the last century, Ireland has seen a recent resurgence in the appreciation and use of seaweed. This research explores the evolution in seaweed foraging practices, with a specific focus on gastronomical uses in two Irish regions: the southwest and the west and midwest. It examines the diversity of seaweed and its present and past uses, comparing abandonment, continuation and revitalisation trajectories. Qualitative data were gathered through semi-structured interviews with 27 individuals who forage seaweed for commercial or personal use. We identified 22 seaweed species across the study areas, predominantly from the Fucaceae, Laminariaceae and Ulvaceae families. There was a fair divergence between the seaweed species used in the two study areas (16 seaweed species in the southwest region and 17 seaweed species in the west and midwest region), with 11 species mentioned in both areas. Different trajectories of resurgence were identified. In the west and midwest region, the revitalisation of local ecological and gastronomic knowledge related to seaweeds seems to be deeply entrenched in the territory’s historical legacy, showing a sort of continuation with the past and having followed a more commercially oriented path. Conversely, in the southwest region, the revival seems to be fostered by new knowledge holders with a contemporary interest in reconnecting with the marine landscape and promoting educational activities centred around seaweed. This research contributes to discussions on sustainable food systems and food heritage promotion, emphasising seaweed’s potential role in Irish coastal communities’ foodscapes. Full article

The main purpose of this manuscript is to present some new estimations of the Jensen gap in a discrete sense along with their applications. The proposed estimations for the Jensen gap are provided with the help of the notion of 6-convex functions. Some numerical experiments are performed to determine the significance and correctness of the intended estimates. Several outcomes of the main results are discussed for the Hölder inequality and the power and quasi-arithmetic means. Furthermore, some applications are presented in information theory, which provide some bounds for the divergences, Bhattacharyya coefficient, Shannon entropy, and Zipf–Mandelbrot entropy. Full article

Wildlife numbers are declining globally due to anthropogenic pressures. In Namibia, however, wildlife populations increased with policy instruments that allow private ownership and incentivize their sustainable use. Antithetically, this resulted in increased resource competition between humans and wildlife and triggered conflicts among various stakeholder groups. This paper summarizes the results of a qualitative exploration of conflicts in wildlife management in Namibia’s Kunene Region, adjacent to Etosha National Park. We conducted a workshop and expert interviews with stakeholders from relevant sectors. Our qualitative research sheds light on societal conflicts over wildlife that originate from diverging interests, livelihood strategies, moral values, knowledge holders, personal relations and views on institutional procedures. We frame our insights into conflicting human–wildlife interactions with theoretical concepts of social-ecological systems, ecosystem services and ecosystem disservices and open the floor for quantitative assessments. Overall, our results may present a suitable way of understanding biodiversity conflicts in a theoretical way. Full article

Front-of-package nutrition labelling (FOPNL) is known as an effective tool that can encourage healthier food choices and food reformulation. A very interesting type of FOPNL is grading schemes. Our objective was to compare two market-implemented grading schemes—European Nutri-Score (NS) and Australian Health Star Rating (HSR), using large Slovenian branded foods database. NS and HSR were used for profiling 17,226 pre-packed foods and drinks, available in Slovenian food supply dataset (2020). Alignment between models was evaluated with agreement (% of agreement and Cohen’s Kappa) and correlation (Spearman rho). The 12-month nationwide sales-data were used for sale-weighing, to address market-share differences. Study results indicated that both models have good discriminatory ability between products based on their nutritional composition. NS and HSR ranked 22% and 33% of Slovenian food supply as healthy, respectively. Agreement between NS and HSR was strong (70%, κ = 0.62) with a very strong correlation (rho = 0.87). Observed profiling models were most aligned within food categories Beverages and Bread and bakery products, while less aligned for Dairy and imitates and Edible oils and emulsions. Notable disagreements were particularly observed in subcategories of Cheese and processed cheeses (8%, κ = 0.01, rho = 0.38) and Cooking oils (27%, κ = 0.11, rho = 0.40). Further analysis showed that the main differences in Cooking oils were due to olive oil and walnut oil, which are favoured by NS and grapeseed, flaxseed and sunflower oil that are favoured by HSR. For Cheeses and cheese products, we observed that HSR graded products across the whole scale, with majority (63%) being classified as healthy (≥3.5 *), while NS mostly graded lower scores. Sale-weighting analyses showed that offer in the food supply does not always reflect the sales. Sale-weighting increased overall agreement between profiles from 70% to 81%, with notable differences between food categories. In conclusion, NS and HSR were shown as highly compliant FOPNLs with few divergences in some subcategories. Even these models do not always grade products equally high, very similar ranking trends were observed. However, the observed differences highlight the challenges of FOPNL ranking schemes, which are tailored to address somewhat different public health priorities in different countries. International harmonization can support further development of grading type nutrient profiling models for the use in FOPNL, and make those acceptable for more stake-holders, which will be crucial for their successful regulatory implementation. Full article

In this paper we give a new refinement of the Lah–Ribarič inequality and, using the same technique, we give a refinement of the Jensen inequality. Using these results, a refinement of the discrete Hölder inequality and a refinement of some inequalities for discrete weighted power means and discrete weighted quasi-arithmetic means are obtained. We also give applications in the information theory; namely, we give some interesting estimations for the discrete Csiszár divergence and for its important special cases. Full article

The laterally graded multilayer collimator is a vital part of a high-precision diffractometer. It is applied as condensing reflectors to convert divergent X-rays from laboratory X-ray sources into a parallel beam. The thickness of the multilayer film varies with the angle of incidence to guarantee every position on the mirror satisfies the Bragg reflection. In principle, the accuracy of the parameters of the sputtering conditions is essential for achieving a reliable result. In this paper, we proposed a precise method for the fabrication of the laterally graded multilayer based on a planetary motion magnetron sputtering system for film thickness control. This method uses the fast and slow particle model to obtain the particle transport process, and then combines it with the planetary motion magnetron sputtering system to establish the film thickness distribution model. Moreover, the parameters of the sputtering conditions in the model are derived from experimental inversion to improve accuracy. The revolution and rotation of the substrate holder during the final deposition process are achieved by the speed curve calculated according to the model. Measurement results from the X-ray reflection test (XRR) show that the thickness error of the laterally graded multilayer film, coated on a parabolic cylinder Si substrate, is less than 1%, demonstrating the effectiveness of the optimized method for obtaining accurate film thickness distribution. Full article

Hormones are important biological regulators, controlling development and physiological processes throughout life. We investigated pituitary hormones such as follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL) and total protein levels during the first 6 months of lactation. Breast milk samples were collected every fourth week of lactation from mothers who gave birth to preterm (n = 14) or term (n = 16) infants. Donor milk is suggested when own mother’s milk is not available; therefore, we collected breast milk samples before and after Holder pasteurization (HoP) from the Breast Milk Collection Center of Pécs, Hungary. Three infant formulas prepared in the Neonatal Intensive Care Unit of the University of Pécs were tested at three different time points. Our aim was to examine the hormone content of own mother’s milk and donor milk. There were no significant changes over time in the concentrations of any hormone. Preterm milk had higher PRL (28.2 ± 2.5 vs. 19.3 ± 2.3 ng/mL) and LH (36.3 ± 8.8 vs. 15.9 ± 4.1 mIU/L) concentrations than term milk during the first 6 months of lactation. Total protein and FSH concentrations did not differ between preterm and term breast milk. Holder pasteurization decreased the PRL concentration (30.4 ± 1.8 vs. 14.4 ± 0.6 ng/mL) and did not affect gonadotropin levels of donor milk. Infant formulas have higher total protein content than breast milk but do not contain detectable levels of pituitary hormones. Differences were detected in the content of pituitary hormones produced for preterm and term infants. Divergence between feeding options offers opportunities for improvement of nutritional guidelines for both hospital and home feeding practices. Full article

Photoacoustic (PA) imaging–a technique combining the ability of optical imaging to probe functional properties of the tissue and deep structural imaging ability of ultrasound–has gained significant popularity in the past two decades for its utility in several biomedical applications. More recently, light-emitting diodes (LED) are being explored as an alternative to bulky and expensive laser systems used in PA imaging for their portability and low-cost. Due to the large beam divergence of LEDs compared to traditional laser beams, it is imperative to quantify the angular dependence of LED-based illumination and optimize its performance for imaging superficial or deep-seated lesions. A custom-built modular 3-D printed hinge system and tissue-mimicking phantoms with various absorption and scattering properties were used in this study to quantify the angular dependence of LED-based illumination. We also experimentally calculated the source divergence of the pulsed-LED arrays to be 58° ± 8°. Our results from point sources (pencil lead phantom) in non-scattering medium obey the cotangential relationship between the angle of irradiation and maximum PA intensity obtained at various imaging depths, as expected. Strong dependence on the angle of illumination at superficial depths (−5°/mm at 10 mm) was observed that becomes weaker at intermediate depths (−2.5°/mm at 20 mm) and negligible at deeper locations (−1.1°/mm at 30 mm). The results from the tissue-mimicking phantom in scattering media indicate that angles between 30–75° could be used for imaging lesions at various depths (12 mm–28 mm) where lower LED illumination angles (closer to being parallel to the imaging plane) are preferable for deep tissue imaging and superficial lesion imaging is possible with higher LED illumination angles (closer to being perpendicular to the imaging plane). Our results can serve as a priori knowledge for the future LED-based PA system designs employed for both preclinical and clinical applications. Full article

According to poststructuralists, workers with higher level of education and possession of potential experience are supposed to have higher wages. Yet, there are plausible questions that arise as to what levels of education or work history are needed for the enhancement of wage discrimination. Additionally, the outcomes arising from rehashing years of schooling are worth considering. We used a several methods, employing the administrative Household Integrated Economic Survey (HIES) data from Pakistan without ignoring environmental effects. Our estimated results support the conventional assumptions of linearity of log-wage. First, we found substantial returns for postgraduate diploma holders in both public and private sectors, even after controlling the individual’s heterogeneity. Second, we did notice a significant divergence in return to low-level education (LLE) and job history. Third, rehashing years of education may create suspiciousness regarding the lack of competence. Our results suggest that continuous investment in human capital toward postgraduate diploma may result in higher premiums. Full article

This paper proposes a geometric estimator of dependency between a pair of multivariate random variables. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate samples. This estimator converges to a quantity that we call the geometric mutual information (GMI), which is equivalent to the Henze–Penrose divergence. between the joint distribution of the multivariate samples and the product of the marginals. The GMI has many of the same properties as standard MI but can be estimated from empirical data without density estimation; making it scalable to large datasets. The proposed empirical estimator of GMI is simple to implement, involving the construction of an minimal spanning tree (MST) spanning over both the original data and a randomly permuted version of this data. We establish asymptotic convergence of the estimator and convergence rates of the bias and variance for smooth multivariate density functions belonging to a Hölder class. We demonstrate the advantages of our proposed geometric dependency estimator in a series of experiments. Full article

Companion animals in the U.S. are increasingly regarded as members of the family with whom one may share a strong emotional bond. However, despite an evolving social construction that has elevated their status in the dominant culture, companion animals lack meaningful legal rights, and “family member” is a provisional status that can be dissolved at will based on the discretion of the sole rights-holder in the relationship: the human owner. Because they are still defined within the U.S. legal system as property, it is a common lament within the animal protection movement that the law has not kept pace with the emergent cultural perception of companion animals as family or best friends who may occupy a significant place in one’s constellation of interpersonal relationships. But how divergent are the laws that govern our treatment of companion animals from prevailing social norms? This article examines current trends in animal law and society to shed light on this question. I find that while a new family member cultural status is emerging for companion animals in the U.S., their legal status as property is a countervailing force, enabling contradictory practices and beliefs that construct animals as expendable. The fact that their cultural status is in flux in turn reinforces their status under the law. I conclude with proposed policy reforms that will facilitate the integration of companion animals into society as true rather than rhetorical family members. Full article

Modern indoor positioning system services are important technologies that play vital roles in modern life, providing many services such as recruiting emergency healthcare providers and for security purposes. Several large companies, such as Microsoft, Apple, Nokia, and Google, have researched location-based services. Wireless indoor localization is key for pervasive computing applications and network optimization. Different approaches have been developed for this technique using WiFi signals. WiFi fingerprinting-based indoor localization has been widely used due to its simplicity, and algorithms that fingerprint WiFi signals at separate locations can achieve accuracy within a few meters. However, a major drawback of WiFi fingerprinting is the variance in received signal strength (RSS), as it fluctuates with time and changing environment. As the signal changes, so does the fingerprint database, which can change the distribution of the RSS (multimodal distribution). Thus, in this paper, we propose that symmetrical Hölder divergence, which is a statistical model of entropy that encapsulates both the skew Bhattacharyya divergence and Cauchy–Schwarz divergence that are closed-form formulas that can be used to measure the statistical dissimilarities between the same exponential family for the signals that have multivariate distributions. The Hölder divergence is asymmetric, so we used both left-sided and right-sided data so the centroid can be symmetrized to obtain the minimizer of the proposed algorithm. The experimental results showed that the symmetrized Hölder divergence consistently outperformed the traditional k nearest neighbor and probability neural network. In addition, with the proposed algorithm, the position error accuracy was about 1 m in buildings. Full article

We describe a framework to build distances by measuring the tightness of inequalities and introduce the notion of proper statistical divergences and improper pseudo-divergences. We then consider the Hölder ordinary and reverse inequalities and present two novel classes of Hölder divergences and pseudo-divergences that both encapsulate the special case of the Cauchy–Schwarz divergence. We report closed-form formulas for those statistical dissimilarities when considering distributions belonging to the same exponential family provided that the natural parameter space is a cone (e.g., multivariate Gaussians) or affine (e.g., categorical distributions). Those new classes of Hölder distances are invariant to rescaling and thus do not require distributions to be normalized. Finally, we show how to compute statistical Hölder centroids with respect to those divergences and carry out center-based clustering toy experiments on a set of Gaussian distributions which demonstrate empirically that symmetrized Hölder divergences outperform the symmetric Cauchy–Schwarz divergence. Full article

Divergence is a discrepancy measure between two objects, such as functions, vectors, matrices, and so forth. In particular, divergences defined on probability distributions are widely employed in probabilistic forecasting. As the dissimilarity measure, the divergence should satisfy some conditions. In this paper, we consider two conditions: The first one is the scale-invariance property and the second is that the divergence is approximated by the sample mean of a loss function. The first requirement is an important feature for dissimilarity measures. The divergence will depend on which system of measurements we used to measure the objects. Scale-invariant divergence is transformed in a consistent way when the system of measurements is changed to the other one. The second requirement is formalized such that the divergence is expressed by using the so-called composite score. We study the relation between composite scores and scale-invariant divergences, and we propose a new class of divergences called H¨older divergence that satisfies two conditions above. We present some theoretical properties of H¨older divergence. We show that H¨older divergence unifies existing divergences from the viewpoint of scale-invariance. Full article