Optimization with constraint learning

Mathematical optimization is a powerful decision-making tool used across diverse fields, with mixed-integer optimization (MIO) playing a key role in solving large-scale problems. However, optimization models often face challenges when constraints or objective functions are not explicit and difficult to design. This thesis introduces an Optimization with Constraint Learning (OCL) framework, integrating Machine Learning (ML) to infer and embed unknown constraints and objectives into MIO models.This thesis applies OCL to supply chain optimization for humanitarian aid, demonstrating how learned food palatability constraints can be integrated to ensure that recipients enjoy the food and know how to prepare it. The thesis further demonstrates OCL’s versatility through two distinct applications: radiotherapy optimization and explainable artificial intelligence (XAI). In radiotherapy, OCL personalizes cancer treatment planning by integrating a predictive model for radiation-induced toxicity, optimizing treatment while minimizing patient risk. In XAI, given a fitted ML model, the OCL framework can be used to generate actionable counterfactual explanations that meet established quality criteria such as closeness, diversity, and robustness against environmental uncertainties.The proposed OCL framework ensures computational efficiency and global optimality, facilitating its adoption by practitioners and researchers. By bridging optimization and ML, this work advances decision-making methodologies and lays the foundation for future research in data-driven optimization

Optimization with constraint learning

Mathematical optimization is a powerful decision-making tool used across diverse fields, with mixed-integer optimization (MIO) playing a key role in solving large-scale problems. However, optimization models often face challenges when constraints or objective functions are not explicit and difficult to design. This thesis introduces an Optimization with Constraint Learning (OCL) framework, integrating Machine Learning (ML) to infer and embed unknown constraints and objectives into MIO models.This thesis applies OCL to supply chain optimization for humanitarian aid, demonstrating how learned food palatability constraints can be integrated to ensure that recipients enjoy the food and know how to prepare it. The thesis further demonstrates OCL’s versatility through two distinct applications: radiotherapy optimization and explainable artificial intelligence (XAI). In radiotherapy, OCL personalizes cancer treatment planning by integrating a predictive model for radiation-induced toxicity, optimizing treatment while minimizing patient risk. In XAI, given a fitted ML model, the OCL framework can be used to generate actionable counterfactual explanations that meet established quality criteria such as closeness, diversity, and robustness against environmental uncertainties.The proposed OCL framework ensures computational efficiency and global optimality, facilitating its adoption by practitioners and researchers. By bridging optimization and ML, this work advances decision-making methodologies and lays the foundation for future research in data-driven optimization

Testosterone represses ubiquitin ligases atrogin-1 and Murf-1 expression in an androgen-sensitive rat skeletal muscle in vivo

Pires-Oliveira M, Maragno AL, Parreiras-E-Silva LT, Chiavegatti T, Gomes MD, Godinho RO. Testosterone represses ubiquitin ligases atrogin-1 and Murf-1 expression in an androgen-sensitive rat skeletal muscle in vivo. J Appl Physiol 108: 266-273, 2010. First published November 19, 2009; doi:10.1152/japplphysiol.00490.2009.-Skeletal muscle atrophy induced by denervation and metabolic diseases has been associated with increased ubiquitin ligase expression. in the present study, we evaluate the influence of androgens on muscle ubiquitin ligases atrogin-1/MAFbx/FBXO32 and Murf-1/Trim63 expression and its correlation with maintenance of muscle mass by using the testosterone-dependent fast-twitch levator ani muscle (LA) from normal or castrated adult male Wistar rats. Gene expression was determined by qRT-PCR and/or immunoblotting. Castration induced progressive loss of LA mass (30% of control, 90 days) and an exponential decrease of LA cytoplasm-to-nucleus ratio (nuclear domain; 22% of control after 60 days). Testosterone deprivation induced a 31-fold increase in LA atrogin-1 mRNA and an 18-fold increase in Murf-1 mRNA detected after 2 and 7 days of castration, respectively. Acute (24 h) testosterone administration fully repressed atrogin-1 and Murf-1 mRNA expression to control levels. Atrogin-1 protein was also increased by castration up to 170% after 30 days. Testosterone administration for 7 days restored atrogin-1 protein to control levels. in addition to the well known stimulus of protein synthesis, our results show that testosterone maintains muscle mass by repressing ubiquitin ligases, indicating that inhibition of ubiquitin-proteasome catabolic system is critical for trophic action of androgens in skeletal muscle. Besides, since neither castration nor androgen treatment had any effect on weight or ubiquitin ligases mRNA levels of extensor digitorum longus muscle, a fast-twitch muscle with low androgen sensitivity, our study shows that perineal muscle LA is a suitable in vivo model to evaluate regulation of muscle proteolysis, closely resembling human muscle responsiveness to androgens.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo, Dept Pharmacol, BR-04044020 São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Dept Biochem & Immunol, Ribeirao Preto, BrazilUniversidade Federal de São Paulo, Dept Pharmacol, BR-04044020 São Paulo, BrazilFAPESP: 05/59006-1FAPESP: 2006/58629-8Web of Scienc

Climate change adaptation mainstreaming through strategic environmental assessments. An in-depth analysis of environmental indicators from spatial plans in Friuli Venezia Giulia Region (Italy)

Climate change adaptation, CCA henceforth, is nowadays a shared concern, deeply investigated and advocated by international research and political organisations. However, both CCA implementation and its monitoring and evaluation (M&E) are challenges yet to be properly addressed. From a spatial planning perspective, local plans are the land-use-oriented tools with the highest potential to enhance CCA operativity. Strategic Environmental Assessment (SEA) is also acknowledged to be a key instrument to integrate climate change concerns and hence, to monitor and evaluate climate change (CC) risks and CCA efforts. This study addresses two hypotheses, i.e., i) indicators included in SEAs' spatial plans may be used at the service of CCA M&E, ii) the full extent of indicators can be captured by multi-level planning analyses. To this aim, this study provides an in-depth analysis, through a multi-step systematic categorization, of the indicators used within the SEA of regional and municipal plans in the Friuli Venezia Giulia Region (Italy). This study brings novelty in the SEA research field by bridging the climate risk theoretical principles to the methodological approach for analysing SEAs' indicators, which are classified within the risk function frame. Key insights come from the metrics, the indicators' explicitness for CCA, and the indicators' extent into the climate risk function. Finally, the paper paves the way for further research of CC- and CCA-related indicators in both spatial planning and other public sectors to support CCA mainstreaming through SEAs

Learn global and optimize local:A data-driven methodology for last-mile routing

In last-mile routing, the task of finding a route is often framed as a Traveling Salesman Problem to minimize travel time and associated cost. However, solutions stemming from this approach do not match the realized paths as drivers deviate due to navigational considerations and preferences. To prescribe routes that incorporate this tacit knowledge, a data-driven model is proposed that aligns well with the hierarchical structure of delivery data wherein each stop belongs to a zone — a geographical area. First, on the global level, a zone sequence is established as a result of a minimization over a cost matrix which is a weighted combination of historical information and distances (travel times) between zones. Subsequently, within zones, sequences of stops are determined, such that, integrated with the predetermined zone sequence, a full solution is obtained. The methodology is particularly promising as it propels itself within the top-tier of submissions to the Last-Mile Routing Research Challenge while maintaining an elegant decomposition that ensures a feasible implementation into practice. The concurrence between prescribed and realized routes underpins the adequateness of a hierarchical breakdown of the problem, and the fact that drivers make a series of locally optimal decisions when navigating. Furthermore, experimenting with the balance between historical information and distance exposes that historic information is pivotal in deciding a starting zone of a route. The experiments also reveal that at the end of a route, historical information can best be discarded, making the time it takes to return to the station the primary concern.</p

Recent structural evolution of forni glacier tongue (Ortles-Cevedale Group, Central Italian Alps)

Structural glaciology yields important details about the evolution of glacier dynamics in response to climate change. The maps provided here document the occurrence and evolution of brittle and ductile structures on the tongue of Forni Glacier, Ortles-Cevedale Group, Central Italian Alps, between 2003 and 2014. Through the remote sensing-based analysis of structures, we found evidence of brittle fractures such as crevasses, faults and ring faults, and ductile structures such as ogives at the base of the icefall in the eastern glacier tongue. Although each of the three glacier tongues have evolved differently, a reduction in flow-related dynamics and an increase in the number of collapse structures occurred over the study period. Analysis of the glacier structural evolution based on the numbers and the locations of different structures, suggest a slowdown of glacier flow on the eastern tongue. The recent evolution of the glacier also suggests that the occurrence of a disintegration scenario is likely to worsen over the next decades

Climate change effects on landscape and environment in glacierized Alpine areas: retreating glaciers and enlarging forelands in the Bernina group (Italy) in the period 1954&#8211;2007

We analysed the recent involution of glaciers in the Bernina group (Italy), which are shrinking thus permitting a rapid enlargement of the forelands. We delimited glacier outlines upon aerial photographs (1954 and 1981 stereo pairs analysed through an optical system) and orthophotos (2003 and 2007 digital imagines directly managed via GIS software). All the obtained data were overlapped and compared. The estimated glacier area change during 1954\u20132007 was 1236.5 \ub1 2.4% ( 1216.2 \ub1 0.4 km2). The changes sped up more recently; in fact, during 1981\u20131954 (27 years) the variation was 120.206 km2/y, against 120.387 km2/y during 1981\u20132003 (22 years), and 120.535 km2/y during 2007\u20132003 (4 years). In the 1954\u20132007 period, the forelands experienced a continuous increase (+14.7 km2). Moreover, the analysis of the colour orthophotos allowed observations of: (i) changes a\ufb00ecting shape and geometry of glaciers (growing rock outcrops, tongue separations, increasing supraglacial debris and collapse structures) and (ii) main features of glacier forelands (bare rock exposures, debris and sediments and, in the latter case, occurrence of vegetation colonizing such pristine areas). Glacier forelands resulted also subjected to the action of melting water, debris transport, and periglacial processes, with consequences on landscape and geoheritage

Supporting Stakeholder Relationship Management via Disclosure on Resource Origins: Evidence from the World\u27s Top NGOs

Issues surrounding accountability form a central part of the ongoing discussion regarding the role, place, and value of civil society organizations. Decision-makers must be aware of this challenge, seeking out proactive and innovative ways to meet the calls for legitimacy, lest increasing competition for finite resources overcome them. The disclosure of financial information using the internet demonstrates a commitment to transparency and provides an opportunity for users to make better decisions, fitting into theories on relationship marketing. This study serves the dual purpose of joining theoretical bases concerning accountability, legitimacy and marketing in the NGO realm and the execution of survey research on the online financial disclosure of the organizations listed in The Global Journal\u27s “100 Top NGOs 2013” Ranking, with particular attention to the origins of their resources. Content analysis was applied to categorize the line items contained in the NGOs´ Income Statement (or equivalent) reports, and quantitative techniques were employed to generate conclusions regarding the income mix, the share of the resource total represented by each category, and each NGO´s degree of dependence on each. The results indicate that donations are the most prevalent category among the sample (41.25%), followed by revenues (24.10%) and grants (17.93%). Donations were also shown to represent, on average, approximately 39% of the income mix of the NGOs in question. Finally, the vast majority of the sample (62 of the 69 reports-providing NGOs) was found to be dependent on one category alone, more than half of which received 80% or more of their resources from a single category in the year in question. These results contribute to developing research in the field of NGO web-based accountability as well as highlighting the need for a greater integration of transparency into stakeholder management practices