Bilevel programming is widely used to model applications with two hierarchical decisions defining, respectively, an upper-level (leader) problem and a lower-level (follower) problem nested in the former. In this scena...
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Bilevel programming is widely used to model applications with two hierarchical decisions defining, respectively, an upper-level (leader) problem and a lower-level (follower) problem nested in the former. In this scenario, the stability of the solution is one of the main issues to address to have a well-posed optimization problem;indeed, the lower-level problem may admit more than one optimal solution generating uncertainty on what the real upper-level objective value will be (instability of the bilevel problem). Notwithstanding the importance of stability, the literature has concentrated the most on defining hypotheses and conditions warranting stability of bilevel problems rather than on algorithms able to find a stable solution to the latter. To give a contribution in this direction, in this paper, we define an algorithm capable of finding a stable solution in bilevel optimization problems. We restrict our analysis to the case in which both the leader and the follower problems are linear-continuous. The proposal starts with finding the optimistic solution of the single-level problem obtained by replacing the follower's problem with its Karush-Kuhn-Tucker conditions, and the corresponding pessimistic solution. In the presence of instability, the algorithm removes one of the follower constraints at a time producing additional constraints for the leader problem in the attempt to define a new stable bilevel problem. Experimental results show that the algorithm can produce stable bilevel solutions representing an effective trade-off between the optimistic and the pessimistic solution values. The proposed algorithm may represent an effective tool for decision-makers aiming at finding robust solutions to bilevel problems.
Chronic nodular prurigo (CNP) is a chronic dermatological disease characterized by the presence of chronic pruritus and pruritic nodular lesions. The aim of this study was to reach consensus among a group of experts b...
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Chronic nodular prurigo (CNP) is a chronic dermatological disease characterized by the presence of chronic pruritus and pruritic nodular lesions. The aim of this study was to reach consensus among a group of experts based on a non-systematic literature review and an algorithm for the clinical diagnosis of CNP. The resulting algorithm is structured in 3 blocks: 1) early identification of the patient with a possible diagnosis of CNP;2) diagnosis and assessment of CNP;and 3) categorization of CNP (identification of the underlying causes or associated comorbidities). We believe that this clinical algorithm can facilitate the correct diagnosis of patients with CNP. Additionally, it raises awareness on the need for a multidisciplinary approach and specific treatment of CNP, steps of paramount importance to make better therapeutic decisions. (c) 2024 AEDV. Published by Elsevier Espana, S.L.U. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
Integration of photovoltaic modules into greenhouse roofs is a novel and intriguing method. The cost of products grown in greenhouses is particularly high because of their high energy consumption for heating and cooli...
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Integration of photovoltaic modules into greenhouse roofs is a novel and intriguing method. The cost of products grown in greenhouses is particularly high because of their high energy consumption for heating and cooling, and at the same time the increase in demand for available land, increasing its cost and creating spatial issues, the integration of photovoltaics on the roof of greenhouses is a highly viable solution. Simultaneously, the use of solar radiation is critical to maintain optimal crop development, while also being a renewable energy source. However, photovoltaics reduce the incoming solar radiation in the greenhouse, due to their shade. Shading can be either beneficial for the crops or not, depending on the crop type, thus it is vital to find the shading caused by photovoltaics both temporally and spatially. In this study, a model calculating the shading in a greenhouse due to roof-integrated photovoltaics is developed, based on the Sun position, the geometry of both the greenhouse and of the roof-integrated photovoltaics and their position on the greenhouse roof. Calculating the coefficient of variation of radiation data, for the shaded and unshaded areas using the proposed algorithm, it was found the coefficient of variation for the shaded areas is lower than that for the unshaded areas for a least 76% of the time. Also, the radiation values under the shaded area are more uniform. The proposed model is a tool for PV designers, operators, and owners, in order to optimize the potential of their solar panel installations.
Background: Prediction algorithms may improve the ability of telehealth solutions to assess the risk of future exacerbations in patients with chronic obstructive pulmonary disease. Learning from patients' and clin...
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Background: Prediction algorithms may improve the ability of telehealth solutions to assess the risk of future exacerbations in patients with chronic obstructive pulmonary disease. Learning from patients' and clinicians' evaluations and experiences about the use of such algorithms is essential to evaluate its potential and examine factors that could potentially influence the implementation and sustained use. Objective: To investigate the patients' and clinicians' perceptions and satisfaction with an algorithm for predicting exacerbations in patients with chronic obstructive pulmonary disease. Design: Multimethod study. Setting: Three community nursing sites in Aalborg Municipality, Denmark. Participants: One hundred and eleven adults with chronic obstructive pulmonary disease and four clinicians (three nurses and one physiotherapist) specialized in telehealth monitoring of the disease. Methods: The study was performed from November 2021 to November 2022 alongside a clinical trial in which a prediction algorithm was integrated into an existing telehealth system. The patients' perspectives were investigated using a self-constructed questionnaire. The clinicians' perspective was explored using semistructured individual interviews. Results: Most patients (84.0 %-90.8 %) were satisfied with the algorithm and the additional measurements required by the algorithm. Approximately 71.7 %-75.9 % found that the algorithm could be a useful tool for disease assessment. Patients elaborated that they could see an exacerbation prevention potential in the algorithm. Patients trusted the algorithm and found an increased sense of security. The clinicians showed a positive response toward the algorithm and its user-friendliness. However, they were concerned that the additional measurements could be too demanding for some patients and questioned the accuracy of the measurements. Some felt that the algorithm could risk being time-consuming and harm the overall assessment of the individual
PurposeThe purpose of this study is to formulate an algorithm designed to discern the optimal routes for efficient municipal solid waste (MSW) ***/methodology/approachThe research method is simulation. The proposed al...
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PurposeThe purpose of this study is to formulate an algorithm designed to discern the optimal routes for efficient municipal solid waste (MSW) ***/methodology/approachThe research method is simulation. The proposed algorithm combines heuristics derived from the constructive genetic algorithm (CGA) and tabu search (TS). The algorithm is applied in a municipality located at Southern Brazil, with 40,000 inhabitants, *** implementation achieved a remarkable 25.44% reduction in daily mileage of the vehicles, resulting in savings of 150.80 km/month and 1,809.60 km/year. Additionally, it reduced greenhouse gas emissions (including fossil CO2, CH4, N2O, total CO2e and biogenic CO2) by an average of 26.15%. Moreover, it saved 39 min of daily working *** limitations/implicationsFurther research should thoroughly analyze the feasibility of decision-making regarding planning, scheduling and scaling municipal services using digital *** implicationsThe municipality now has a tool to improve public management, mainly related with municipal solid waste. The municipality reduced the cost of public management of municipal solid waste, redirecting funds to other priorities, such as public health and ***/valueThe study integrates MSW collection service with an online platform based on Google MapsTM. The advantages of employing geographical information systems are agility, low cost, adaptation to changes and accuracy.
The rise in AI-based assessments in hiring contexts has led to significant media speculation regarding their role in exacerbating or mitigating employment inequities. In this study, we examined 46,214 ratings from 494...
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The rise in AI-based assessments in hiring contexts has led to significant media speculation regarding their role in exacerbating or mitigating employment inequities. In this study, we examined 46,214 ratings from 4947 interviews to ascertain if gender differences in ratings were related to interactions among content (stereotype-relevant competencies), context (occupational gender composition), and rater type (human vs. algorithm). Contrary to the hypothesized effects of smaller gender differences in algorithmic scoring than with human raters, we found that both human and algorithmic ratings of men on agentic competencies were higher than those given to women. Also unexpected, the algorithmic scoring evidenced greater gender differences in communal ratings than humans (with women rated higher than men) and similar differences in non-stereotypic competency ratings that were in the opposite direction (humans rated men higher than women, while algorithms rated women higher than men). In more female-dominated occupations, humans tended to rate applicants as generally less competent overall relative to the algorithms, but algorithms rated men more highly in these occupations. Implications for auditing for group differences in selection contexts are discussed.
Background: The globally rising prevalence of obesity highlights the importance of implementing effective methods for prevention and treatment. In this context, personalized nutrition (PN) is being discussed as a prom...
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Background: The globally rising prevalence of obesity highlights the importance of implementing effective methods for prevention and treatment. In this context, personalized nutrition (PN) is being discussed as a promising approach. The Food4Me study, a clinical trial investigating the effectiveness of PN interventions, demonstrated that tailoring dietary advice to individual needs is more likely to initiate behavior changes than standard dietary guidelines. However, the accessibility of PN remains a challenge due to financial and structural barriers. ChatGPT, a freely available, natural language processing model published in 2022, might provide a solution to increase the availability of personalized nutrition to a broader population. Methods: To investigate ChatGPT's potential to provide accurate and reliable personalized dietary recommendations, we conducted a comparative analysis, comparing its recommendations with those of the Food4Me algorithm. We selected 20 obese subjects of the German Food4Me sub-cohort and entered their baseline data into ChatGPT (version 3.5). For each subject, a separate chat space was set up, maintaining consistent wording and prompt order throughout all chats to ensure comparability. The prompts were written from a first-person perspective, simulating an authentic scenario of average users asking for dietary recommendations. ChatGPT's responses were compared to the Food4Me feedback reports that had been provided to the selected subjects within the study. Results: ChatGPT may provide suitable personalized dietary advice and holds some noteworthy advantages over the Food4Me algorithm, but still tends to produce recommendations with inconsistent and unpredictable errors, for example, regarding intakes of macro- or micronutrients. Conclusion: Currently, it is not advisable for individuals without nutritional expertise to rely on ChatGPT for personalized dietary recommendations. Nevertheless, ChatGPT remains a promising approach and may deve
Afrocentric studies have questioned how content gets channelled, promoted, and programmed by the algorithms on Western-based social networking sites (SNSs) for and by African users. This article probes the uses of soc...
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Afrocentric studies have questioned how content gets channelled, promoted, and programmed by the algorithms on Western-based social networking sites (SNSs) for and by African users. This article probes the uses of social media through the algorithmic functions of Western-based technologies to analyse whether users understand the social media algorithm and how they circumvent or manipulate it to their own advantage. Based on focus group discussions, this article unpacks the level of algorithm literacy to explore the concept of decoloniality in terms of social media localisation. The study's findings reflect that whether literate or illiterate about the algorithm, users are active participants able to choose or search content that meets their needs. On the other hand, the study shows that literacy somehow enables users to manipulate the algorithmic functions for content consumption. Using the decolonial theory, the article argues that although Western owned, the algorithm can be localised to promote access and content consumption through a local social network.
In daily life, sensorimotor integration processes are fundamental for many cognitive operations. The pursuit-tracking paradigm is an ecological and valid paradigm to examine sensorimotor integration processes in a mor...
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In daily life, sensorimotor integration processes are fundamental for many cognitive operations. The pursuit-tracking paradigm is an ecological and valid paradigm to examine sensorimotor integration processes in a more complex environment than many established tasks that assess simple motor responses. However, the analysis of pursuit-tracking performance is complicated, and parameters quantified to examine performance are sometimes ambiguous regarding their interpretation. We introduce an open-source algorithm (TRACK) to calculate a new tracking error metric, the spatial error, based on the identification of the intended target position for the respective cursor position. The identification is based on assigning cursor and target direction changes to each other as key events, based on the assumptions of similarity and proximity. By applying our algorithm to pursuit-tracking data, beyond replication of known effects such as learning or practice effects, we show a higher precision of the spatial tracking error, i.e., it fits our behavioral data better than the temporal tracking error and thus provides new insights and parameters for the investigation of pursuit-tracking behavior. Our work provides an important step towards fully utilizing the potential of pursuit-tracking tasks for research on sensorimotor integration processes.
Aim: : The management of cardiorespiratory arrest in a diving bell presents multiple clinical, technical, and environmental considerations that standard resuscitation algorithms do not address, and no situation-specif...
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Aim: : The management of cardiorespiratory arrest in a diving bell presents multiple clinical, technical, and environmental considerations that standard resuscitation algorithms do not address, and no situation-specific algorithm exists. The development and testing of an algorithm to guide the management of cardiorespiratory arrest in a bell is described. Methods: : An iterative approach to algorithm development was used. Phase 1 involved a small multidisciplinary group and took place in a simulation centre and a decommissioned diving bell. The algorithm was then refined in a purpose-build simulation complex with repeated simulation by a group of divers, and with input from industry experts. ALS principles were followed unless contextual or technical factors necessitated deviation. Results: : Clinical and technical aspects of the resuscitation are addressed. Key priorities that conflict with standard ALS principles are: prioritisation of rescue breaths;use of mechanical CPR when available;and the provision of CPR with the casualty in a seated position where necessary. Conclusion: : This is the first algorithm to guide the delivery of resuscitation in a diving bell. It incorporates adapted ALS principles and available data concerning compression technique effectiveness, and was informed by industry and clinical expertise. It provides guiding principles that can be adapted to setting-specific needs, and we would encourage its industry-wide international adoption.
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