Set Of Values Research Articles

Differences in health utilities between cancer patients and the general population: the case of Quebec using the SF-6Dv2.

A considerable debate persists in the literature about whose preferences should be considered in the calculation of quality-adjusted life-years. Some suggest considering only the preferences of the general population, while others advocate for the consideration of those of patients or a combination of both. This study aims to inform and measure the differences in health preferences between cancer patients and the general population in Quebec. A total of 60,976 observations representing the preferences of the general population for various health states were collected and used to develop a new value set using the SF-6Dv2. This value set was generated by combining 34,299 observations with time trade-off (TTO) and 26,677 observations with discrete choice experiment (DCE). Utility scores derived from this value set were compared to those of patients’ preferences from a new value set in breast and colorectal patients for the SF-6Dv2. For both patients and the general population, the ‘Pain’ dimension was the highest contributor to the utility score. However, noticeable differences were observed in the estimates. Estimates of levels 2 and 3 were generally lower for cancer patients, while they were more likely to have greater estimates in severe levels. Significant differences in utility scores were also noticed with the general population showing higher mean utility scores for the same health states. These differences increased as the health states worsened. This study sheds light on the existing differences in preferences between cancer patients and the general population of Quebec for a better consideration in healthcare decision-making.

A Prerequisite for need of Harmonized Nutrient Reference Values & its Standardized Terminology for Better access of Nutritional Supplements Globally

Abstract: To reduce the risk of insufficient nutrient intake, nutrient reference values for humans are set at the average nutrient need level without a safety margin. The vast majority of nations and areas in the globe set nutritional intake guidelines for their citizens. Currently, no harmonized nutrient reference value has been published, as well as the development of standards cannot be achieved through the use of formalized frameworks or terminology. The study's objective was to create recommendations for appropriate and secure micronutrient intake ranges that could be used to inform dietary advice. As relevant to the study, we examined micronutrient data from food intake surveys from representative nations. The comparison of national standards illustrates that the level of reference values for nutrient for individual countries is dependent on variables such as methodology, data sources, physical activity exemptions, standard body weights, and age range. In the current study, iron, calcium, magnesium, vitamin A, B12, D and folate were identified as the most commonly under-consumed micronutrients. In this article, the level of six countries' standards are compared to the current reference values for nutrients. Further, numerous words for different dietary standards components are discussed, and a final set of harmonized reference nutrient intake for the dietary advice is provided.

Cross-Regional Crop Classification Based on Sentinel-2

Accurate crop classification is of vital importance for agricultural water management. Most researchers have achieved crop classification by model optimization in the same temporal and regional domain by adjusting the value of input features. This study aims to improve the accuracy of crop classification across temporal and spatial domains. Sentinel-2 satellite imagery is employed for crop classification training and prediction in selected farming areas of Heilongjiang Province by calculating vegetation indices and constructing sequential input feature datasets. The HUNTS filtering method was used to mitigate the influence of cloud cover, which increased the stability and completeness of the input feature data across different years. To address the issue of shifts in the input feature values during cross-scale classification, this study proposes the hypothesis testing distribution method (HTDM). This method balances the distribution of input feature values in the test set even without knowing the crop distribution, thereby enhancing the accuracy of the classification test set. The results indicate that the HTDM significantly improves prediction accuracy in cases of substantial image quality variance. In 2022, the recognition accuracy for crop types at all farms processed by the HTDM was above 87%, showcasing the strong robustness of the HTDM.

Spaycations: A Qualitative Study of Veterinarians’ Motivations And Perceived Impacts of Remote Volunteer Spay Neuter

Increasingly, veterinarians skilled in High Quality High Volume Spay Neuter (HQHVSN) are invited to volunteer their surgical services in distant low-resource communities on trips that have become casually known as “spaycations.” While these trips are numerous, there is little research on veterinarians’ motivations for participating and their perceptions of the impacts these clinics have on communities they visit. The current study was open to veterinarians who work in or are trained in HQHVSN whether or not they had been on a spaycation trip. For the purpose of this study, a spaycation is defined as an unpaid or minimally paid trip from a high resource area to a low or moderate resource country or area to provide spay neuter services that is organized by someone other than the individual surgeon. Forty-one veterinarians responded to an electronic questionnaire containing open-ended questions relating to their thoughts and experiences regarding spaycations and their impacts on the volunteer veterinarians as well as on the animals, clients, communities, veterinary practitioners, and animal populations in the areas visited. A reflexive thematic analysis was conducted in which the veterinarians’ responses were coded inductively for semantic themes using a critical realist approach. Respondents had participated in a variety of spaycations around the world over the past 20 years. Most responding veterinarians were motivated by a desire to make a difference and give back to communities in need as well as the desire to travel and to experience other cultures. Many enjoyed bonding with and learning from other vets and team members on the spaycation, and said that while the trips were exhausting they were also paradoxically energizing, and that they renewed their professional passion. Many veterinarians were concerned by the financial and time commitments associated with participating in spaycations, and these costs had prevented some veterinarians from participating. Further reasons for not participating in spaycations included concerns about stress and burnout and about the continual expectation for veterinarians to volunteer their time. Some veterinarians presented concerns about spaycations producing damaging interactions with the local communities including cultural misunderstandings, distrust, the creation of dependence, colonialism, and White Savior syndrome. Local involvement in the spay neuter event varied, with some events entirely planned and staffed locally and involving training and mentorship of local veterinary professionals and students, while other spaycations included little local involvement. Veterinarians varied in their estimation of the animal population impact of the spaycation and agreed that recurrent or ongoing interventions are necessary for appreciable and sustainable population impacts, but that health impacts on individual animals and their families were important and visible even after a single trip. Thematic analysis identified three main themes, HQHVSN is a special skill set, Colonialism and Cost and Value. Spaycations are a unique way for HQHVSN veterinarians to use their distinctive skills in communities of need. The compelling nature of these trips necessitates conscientious and culturally-sensitive leadership and planning to provide safe, sustainable, community-centered programs with a focus on long-term solutions.

An integrated method for gravity gradient inversion and gravity gradient depth imaging

Summary Gravity gradient data can show the structural features of geological bodies in the shallow lithosphere with higher sensitivity and resolution than conventional gravity data. Gravity gradient inversion can be applied to obtain the lithospheric density structures of geological bodies. However, as with gravity data, gravity gradient data have no inherent depth resolution. The methods of gravity gradient depth imaging and gravity gradient inversion are integrated in this study. The depth imaging method is effective for calculations without prior information and iterative computations. As the parameters in the depth weighting function should be chosen from a set of values used in inversion tests of synthetic data, which brings some uncertainties, the depth imaging results of gravity gradient are introduced into the depth weighting function. Several synthetic models are tested to demonstrate the advantages and features of the effective integrated method. Finally, the integrated method is applied to the interpretation of the GOCE satellite gravity gradient tensors over the northeastern margin of the Qinghai-Tibet Plateau. The results reveal that in the crust of the study area, the distribution of density anomalies is more in line with the mechanism of the crustal flow model, in the upper mantle of the study area, the density anomalies are mainly influenced by the high heat flow environment.

Value Sets of Business-owning Families: An Indigenous African Perspective

ABSTRACT While the literature highlights the important role played by family values in family businesses, knowledge on the nature of these values is limited or close to non-existent from certain perspectives, notably an indigenous African family business perspective. Therefore, utilizing seven indigenous Black South African family businesses as case studies, our study seeks to identify the family value sets in the business-owning families using a qualitative design. The findings show that these families uphold and teach the next-generation (NextGen) four family value sets, namely moral and ethical, economic, spiritual and religious, and cultural values. The NextGen is expected to use these value sets as they navigate their lives in and outside the family. Our study contributes to theory by identifying, developing and providing detailed insights into the nature of family values from an indigenous Black South African business-owning family perspective, and our value classification framework potentially provides other researchers with a theoretical foundation to conduct further research. Business-owning families should uphold value sets that accommodate the needs of individual family members, entire business-owning families, and their respective cultures. We also believe that non-indigenous businesses need to understand the family value sets upheld by indigenous Black African businesses to engage with them appropriately and improve business relationships.

Foundations of reasoning with uncertainty via real-valued logics

Interest in logics with some notion of real-valued truths has existed since at least Boole and has been increasing in AI due to the emergence of neuro-symbolic approaches, though often their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of such systems. We introduce a rich class of multidimensional sentences, with a sound and complete axiomatization that can be parameterized to cover many real-valued logics, including all the common fuzzy logics, and extend these to weighted versions, and to the case where the truth values are probabilities. Our multidimensional sentences form a very rich class. Each of our multidimensional sentences describes a set of possible truth values for a collection of formulas of the real-valued logic, including which combinations of truth values are possible. Our completeness result is strong, in the sense that it allows us to derive exactly what information can be inferred about the combinations of truth values of a collection of formulas given information about the combinations of truth values of a finite number of other collections of formulas. We give a decision procedure based on linear programming for deciding, for certain real-valued logics and under certain natural assumptions, whether a set of our sentences logically implies another of our sentences. The generality of this work, compared to many previous works on special cases, may provide insights for both existing and new real-valued logics whose inference properties have never been characterized. This work may also provide insights into the reasoning capabilities of deep learning models.

Assessment of abiotic reduction rates of organic compounds by interpretable structural factors and experimental conditions in anoxic water environments

For organic contaminants in lake sediments, aquifers, and anaerobic bioreactors, their reduction is one of the primary transformation paths in these anoxic water environments. A simple model is introduced to predict pseudo-first order rate constants (kobs) for the abiotic reduction of organic compounds featuring diverse reducible functional groups. It utilizes the largest experimental dataset of –log kobs, encompassing 59 organic compounds (278 data points). Unlike available complex quantitative structure–activity relationship (QSAR) methods, the novel approach requires both experimental conditions and structural parameters. In comparison to one of the available general QSAR methods, the new model demonstrates favorable performance. The average absolute deviation (AAD), absolute maximum deviation (ADmax), average absolute relative deviation (AARD%), and R-squared (R2) values of the estimated outputs for 54/5 training/test data sets of the new model are 0.641/1.761, 1.761/1.417, 20.52/83.87, and 0.797/0.949, respectively. On the other hand, the available general comparative QSAR method shows the AAD: 1.311/2.301, ADmax: 3.795/3.732, AARD%: 641.0/821.2, and R2: 0.003/0.447. For the test set, AAD, AARD%, ADmax, and R2 values for the new/comparative models are 0.649/2.403, 62.20/190.5, 1.215/3.732 and 0.974/0.789, respectively. In summary, the new model offers a straightforward approach for the manual calculation of –log kobs, demonstrating excellent goodness-of-fit, reliability, precision, and accuracy.

A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study

ObjectivesTo develop and validate radiomics model based on computed tomography (CT) for preoperative prediction of CN0 status in patients with papillary thyroid carcinoma (PTC).MethodsA total of 548 pathologically confirmed LNs (243 non-metastatic and 305 metastatic) two distinct hospitals were retrospectively assessed. A total of 396 radiomics features were extracted from arterial-phase CT images, where the strongest features containing the most predictive potential were further selected using the least absolute shrinkage and selection operator (LASSO) regression method. Delong test was used to compare the AUC values of training set, test sets and cN0 group.ResultsThe Rad-score showed good discriminating performance with Area Under the ROC Curve (AUC) of 0.917(95% CI, 0.884 to 0.950), 0.892 (95% CI, 0.833 to 0.950) and 0.921 (95% CI, 868 to 0.973) in the training, internal validation cohort and external validation cohort, respectively. The test group of CN0 with a AUC of 0.892 (95% CI, 0.805 to 0.979). The accuracy was 85.4% (sensitivity = 81.3%; specificity = 88.9%) in the training cohort, 82.9% (sensitivity = 79.0%; specificity = 88.7%) in the internal validation cohort, 85.4% (sensitivity = 89.7%; specificity = 83.8%) in the external validation cohort, 86.7% (sensitivity = 83.8%; specificity = 91.3%) in the CN0 test group.The calibration curve demonstrated a significant Rad-score (P-value in H-L test > 0.05). The decision curve analysis indicated that the rad-score was clinically useful.ConclusionsRadiomics has shown great diagnostic potential to preoperatively predict the status of cN0 in PTC.

Analysis and design of wireless power transfer system with anti-misalignment constant voltage output characteristics

Analysis and design of wireless power transfer system with anti-misalignment constant voltage output characteristics

A comprehensive investigation of uncertainties in cavitating waterjet experiments

This paper systematically examines the sources of uncertainty in cavitating waterjet test setups and provides illustrative case studies to conduct thorough uncertainty analyses for erosion tests using cavitating waterjet method. Within this study, utilizing examples of uncertainty analysis presented by the International Towing Tank Conference (ITTC) for various testing techniques, a novel uncertainty analysis implementation suitable for cavitating waterjet tests has been conducted. Firstly, cavitation erosion experiments were carried out on samples aluminum (Al 6063) material under cavitation number conditions (σ = 0.02 to σ = 0.033 range) as part of the validation study. Subsequently, within the scope of uncertainty analysis calculations, five erosion tests were conducted for each of the two different cavitation numbers (σ = 0.03 and σ = 0.05). The study aims to examine the bias and precision uncertainty components separately for the test results of erosion rate and establish a reliable and repeatable procedure for predicting the uncertainty level of cavitating waterjet tests. For the first time in the literature, the uncertainty components of cavitating waterjet tests were investigated in detail and the uncertainty level in cavitating waterjet tests, including bias and precision errors, was predicted in accordance with specific ITTC guidelines and procedures. Based on the results, the primary bias error source was identified as the pressure inside the cavitation chamber, with the nozzle pressure being the second most significant bias error source. Consequently, it is recommended to perform the bias error prediction based on the ratio of these two, known as the cavitation number. Precision error, crucial for uncertainty, was estimated using five sets of erosion rate values, emphasizing its importance in cavitating waterjet tests. It is anticipated that the suggested methodology will serve as a benchmark for predicting uncertainty levels in cavitating waterjet tests.

Good husbandry of the cow vet

As a new graduate, we often think that honing our technical skills is the number one priority. While being a technically-skilled veterinarian is incredibly important for serving our clients and animals, we also need to develop the skills to take care of ourselves. We can assess our mental and physical states as cattle veterinarians through the lens of the 5 Freedoms and 5 Domains of Animal Welfare. We will discuss how goal setting is a habit of highly successful people and how we often overlook the value of intention setting. As cattle veterinarians, we can combat imposter syndrome through setting boundaries, recog­nizing burnout and investing in relationships. Cattle veterinar­ians, like our bovine patients, are herd animals too.

METHODOLOGICAL CHALLENGES OF RESEARCH ON PROBLEMS OF SOCIALIZATION OF PERSONALITY IN THE CONTEXT OF THE RUSSIAN-UKRAINIAN WAR

Relevance. Despite being traditional and important for psychological and sociological sciences, the problem of socialization remains vulnerable to criticism due to the apologetic nature of its theoretical and methodological foundations. Within the limits of traditional approaches, the success or failure of the process and results of socialization are considered, in fact, in the interests of the officially recognized state ideology with a corresponding set of ideals and values. This may be acceptable for countries with established democratic regimes, but it generates many insidious questions in the conditions of confrontation between societies with different civilizational reference points. This is the situation we have today in the context of the russian-Ukrainian war. Methodology is based on the discursive approach, which does not deprive the researcher of the right to evaluate socialization from his or her ideological position, but excludes the extrapolation of these evaluations to the psychological (procedural) content of socialization. According to this approach, the discourses in which socialization takes place, rather than its psychological content itself, can be evaluated from a moral or ideological perspective. This allows for a more realistic evaluation of the socialization experience of different societies, different countries and peoples, for comparison, etc. People’s participation in the reproduction and development of discourse can be traced by the results of monitoring all-Ukrainian representative surveys conducted by the Institute of Social and Political Psychology of the National Academy of Sciences of Ukraine since the early 1990s. Results. During this time, the territorial-state discourse has gradually formed as a leading one in Ukrainian society. Its value imperative is the attitude of state independence. About 80% of citizens believe that although there are many obstacles in the way of our statehood, Ukraine should still be independent.

Responding to economic abuse: An institutional logics analysis of feminist activism

AbstractEconomic abuse (EA)—intimate partners' efforts to control women's economic resources—still suffers from ambiguous legal recognition. Even in countries with legal recognition, state allocation of resources for support remains meager. We suggest that Israeli state welfare organizations (SWOs) employees have developed their professional response to EA along two distinct value sets—a dominant institutional logic in their respective organizations and a more covert feminist institutional logic encountered in collaborations with feminist Non Governmental Organizations. Using a framework of multiple institutional logics, in interviews with 48 SWO employees, we map the multiple institutional logics that cultivate responses to EA survivors and show that elements of feminist understanding and practices on EA permeate SWOs' practices. The existence of a feminist institutional logic creates a path for exploring whether the feminist impact is significant in enabling committed responses to EA even while no institutional change is achieved.

Parametric Dynamic Simulation and Bayesian Design Optimization of a Front-Loading Washing Machine

Abstract Objective This paper presents the dynamic modeling and design optimization of a fully parametrized front-loading washing machine. Methods A thorough mathematical analysis is performed to capture the effect of nine design variables (including rotation speed, spring stiffness, weight balancer mass density, damping coefficient, spring and damper angles) on vibrational characteristics of the washing machine. The parametric simulation reveals a complex relationship between the vibrational dynamics and design variables, entailing a computationally efficient optimization approach. A Bayesian Optimization (BO) framework is developed, in which a Gaussian process model and Genetic Algorithm (GA) are utilized along with carefully selected acquisition functions to enable adaptive sampling and search for optimal design values. The objective function is to minimize the maximum amplitude of the tub displacement inside the washing machine body. Two case studies are performed to consider a different number of design variables and choices of various infill methods. Results Results show that the fully parametrized front-loading washing machine model is applicable for parametric simulation and design optimization. The proposed BO is able to successfully find a set of design variable values corresponding to the lowest maximum displacement for vibration reduction. A comparison analysis is also carried out to exhibit the difference in optimization convergence and computational cost caused by the choice of acquisition functions. Conclusion It is shown that the fully parametrized washing machine model yields a lower maximum displacement than the model with fewer design variables. Of the two acquisition functions studied for optimization, the Expected Improvement function converges more rapidly than the Lower Bound criterion.

Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire

Abstract Purpose This study aimed to develop a Japanese value set for the EORTC QLU-C10D, a multi-attribute utility measure derived from the cancer-specific health-related quality-of-life (HRQL) questionnaire, the EORTC QLQ-C30. The QLU-C10D contains ten HRQL dimensions: physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, and bowel problems. Methods Quota sampling of a Japanese online panel was used to achieve representativeness of the Japanese general population by sex and age (≥ 18 years). The valuation method was an online discrete choice experiment. Each participant considered 16 choice pairs, randomly assigned from 960 choice pairs. Each pair included two QLU-C10D health states and life expectancy. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Preference weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy. Results A total of 2809 eligible panel members consented, 2662/2809 (95%) completed at least one choice pair, and 2435/2662 (91%) completed all choice pairs. Within dimensions, preference weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Intermediate utility weights were associated with social functioning and nausea; the remaining symptoms and emotional functioning were associated with smaller utility decrements. The value of the worst health state was − 0.221, lower than that seen in most other existing QLU-C10D country-specific value sets. Conclusions The Japan-specific QLU-C10D value set is suitable for evaluating the cost and utility of oncology treatments for Japanese health technology assessment and decision-making.

Improved clinical data imputation via classical and quantum determinantal point processes

Imputing data is a critical issue for machine learning practitioners, including in the life sciences domain, where missing clinical data is a typical situation and the reliability of the imputation is of great importance. Currently, there is no canonical approach for imputation of clinical data and widely used algorithms introduce variance in the downstream classification. Here we propose novel imputation methods based on determinantal point processes (DPP) that enhance popular techniques such as the multivariate imputation by chained equations and MissForest. Their advantages are twofold: improving the quality of the imputed data demonstrated by increased accuracy of the downstream classification and providing deterministic and reliable imputations that remove the variance from the classification results. We experimentally demonstrate the advantages of our methods by performing extensive imputations on synthetic and real clinical data. We also perform quantum hardware experiments by applying the quantum circuits for DPP sampling since such quantum algorithms provide a computational advantage with respect to classical ones. We demonstrate competitive results with up to 10 qubits for small-scale imputation tasks on a state-of-the-art IBM quantum processor. Our classical and quantum methods improve the effectiveness and robustness of clinical data prediction modeling by providing better and more reliable data imputations. These improvements can add significant value in settings demanding high precision, such as in pharmaceutical drug trials where our approach can provide higher confidence in the predictions made.

Improved clinical data imputation via classical and quantum determinantal point processes

Imputing data is a critical issue for machine learning practitioners, including in the life sciences domain, where missing clinical data is a typical situation and the reliability of the imputation is of great importance. Currently, there is no canonical approach for imputation of clinical data and widely used algorithms introduce variance in the downstream classification. Here we propose novel imputation methods based on determinantal point processes (DPP) that enhance popular techniques such as the multivariate imputation by chained equations and MissForest. Their advantages are twofold: improving the quality of the imputed data demonstrated by increased accuracy of the downstream classification and providing deterministic and reliable imputations that remove the variance from the classification results. We experimentally demonstrate the advantages of our methods by performing extensive imputations on synthetic and real clinical data. We also perform quantum hardware experiments by applying the quantum circuits for DPP sampling since such quantum algorithms provide a computational advantage with respect to classical ones. We demonstrate competitive results with up to 10 qubits for small-scale imputation tasks on a state-of-the-art IBM quantum processor. Our classical and quantum methods improve the effectiveness and robustness of clinical data prediction modeling by providing better and more reliable data imputations. These improvements can add significant value in settings demanding high precision, such as in pharmaceutical drug trials where our approach can provide higher confidence in the predictions made.

Men’s Violence against Women as Portrayed in the Swedish Media: The Construction of Victimhood and the Role of the Perpetrator

Men’s violence against women is an international problem and while global and national initiatives have been created to better the criminalization process, the influence of news reporting on violence against women has not been successfully addressed in such policy. The aim of this study is to contribute to understanding how media frames violence against women in the Swedish context, which is both highly protective of crime reporting and where violence against women is a central policy and public discussion issue. A mixed methods approach was used in the analysis of 295 digital news articles that were published by four media outlets (Aftonbladet, Expressen, Svenska Dagbladet and Dagens Nyheter) within the period January 1st, 2019–December 31st, 2021. The study found that digital news articles first frame the issue of violence against women as episodic, but later transform into a thematic frame when follow-up articles were written on a given case. The study found a construction of victimhood by Swedish news media that allowed for two victim personas to be identified: the ideal victim and the ideal minority victim. In connection with the portrayal of the victim, the study also identified two different portrayals of the perpetrator: the ideal foreign perpetrator and the Swedish perpetrator. Both the description of the victim and perpetrator allowed for insights to be made regarding the role of racialization in news reporting and how this effects the framing of social issues. Finally, the study presented a set of news values that were most frequently found in articles that reveal several news factors of violence against women that contribute to the topic being seen as newsworthy.

Transient overvoltage suppression of LCC‐HVDC sending‐end system based on DC current control optimisation

AbstractThe receiving‐end system AC fault of the line‐commutated‐converter‐based high voltage direct current (LCC‐HVDC) will lead to commutation failure of the inverter side. During the fault and its recovery, AC transient low voltage and transient overvoltage (TOV) will occur in the sending‐end system. The TOV has the risk of triggering the disorderly off‐grid of the nearby renewable power generations. Besides, in a serious situation, it will threaten the power system to maintain a secure and steady operation. Therefore, the authors analyse the mechanism involved in the AC transient voltage during the AC fault and the recovery period first. It reveals that the key factor causing the TOV of the sending‐end system is the setting of the DC current reference value. Then, a DC current reference value limit method based on the AC TOV sampling value is proposed, which is used to accelerate DC current recovery and suppress the TOV of the sending‐end system. Finally, the effectiveness of the designed control method has been confirmed through electromagnetic transient simulations using the CIGRE HVDC benchmark model and a ±800 kV HVDC transmission system model situated in Northwest China.