Dalla città alla casa, dalla casa alla città: la mutevole ricerca di un Piano per il ben-essere urbano

La ricerca si propone di definire le linee guida per la stesura di un Piano che si occupi di qualità della vita e di benessere. Il richiamo alla qualità e al benessere è positivamente innovativo, in quanto impone agli organi decisionali di sintonizzarsi con la soggettività attiva dei cittadini e, contemporaneamente, rende evidente la necessità di un approccio più ampio e trasversale al tema della città e di una più stretta relazione dei tecnici/esperti con i responsabili degli organismi politicoamministrativi. La ricerca vuole indagare i limiti dell’urbanistica moderna di fronte alla complessità di bisogni e di nuove necessità espresse dalle popolazioni urbane contemporanee. La domanda dei servizi è notevolmente cambiata rispetto a quella degli anni Sessanta, oltre che sul piano quantitativo anche e soprattutto sul piano qualitativo, a causa degli intervenuti cambiamenti sociali che hanno trasformato la città moderna non solo dal punto di vista strutturale ma anche dal punto di vista culturale: l’intermittenza della cittadinanza, per cui le città sono sempre più vissute e godute da cittadini del mondo (turisti e/o visitatori, temporaneamente presenti) e da cittadini diffusi (suburbani, provinciali, metropolitani); la radicale trasformazione della struttura familiare, per cui la famiglia-tipo costituita da una coppia con figli, solido riferimento per l’economia e la politica, è oggi minoritaria; l’irregolarità e flessibilità dei calendari, delle agende e dei ritmi di vita della popolazione attiva; la mobilità sociale, per cui gli individui hanno traiettorie di vita e pratiche quotidiane meno determinate dalle loro origini sociali di quanto avveniva nel passato; l’elevazione del livello di istruzione e quindi l’incremento della domanda di cultura; la crescita della popolazione anziana e la forte individualizzazione sociale hanno generato una domanda di città espressa dalla gente estremamente variegata ed eterogenea, frammentata e volatile, e per alcuni aspetti assolutamente nuova. Accanto a vecchie e consolidate richieste – la città efficiente, funzionale, produttiva, accessibile a tutti – sorgono nuove domande, ideali e bisogni che hanno come oggetto la bellezza, la varietà, la fruibilità, la sicurezza, la capacità di stupire e divertire, la sostenibilità, la ricerca di nuove identità, domande che esprimono il desiderio di vivere e di godere la città, di stare bene in città, domande che non possono essere più soddisfatte attraverso un’idea di welfare semplicemente basata sull’istruzione, la sanità, il sistema pensionistico e l’assistenza sociale. La città moderna ovvero l’idea moderna della città, organizzata solo sui concetti di ordine, regolarità, pulizia, uguaglianza e buon governo, è stata consegnata alla storia passata trasformandosi ora in qualcosa di assai diverso che facciamo fatica a rappresentare, a descrivere, a raccontare. La città contemporanea può essere rappresentata in molteplici modi, sia dal punto di vista urbanistico che dal punto di vista sociale: nella letteratura recente è evidente la difficoltà di definire e di racchiudere entro limiti certi l’oggetto “città” e la mancanza di un convincimento forte nell’interpretazione delle trasformazioni politiche, economiche e sociali che hanno investito la società e il mondo nel secolo scorso. La città contemporanea, al di là degli ambiti amministrativi, delle espansioni territoriali e degli assetti urbanistici, delle infrastrutture, della tecnologia, del funzionalismo e dei mercati globali, è anche luogo delle relazioni umane, rappresentazione dei rapporti tra gli individui e dello spazio urbano in cui queste relazioni si muovono. La città è sia concentrazione fisica di persone e di edifici, ma anche varietà di usi e di gruppi, densità di rapporti sociali; è il luogo in cui avvengono i processi di coesione o di esclusione sociale, luogo delle norme culturali che regolano i comportamenti, dell’identità che si esprime materialmente e simbolicamente nello spazio pubblico della vita cittadina. Per studiare la città contemporanea è necessario utilizzare un approccio nuovo, fatto di contaminazioni e saperi trasversali forniti da altre discipline, come la sociologia e le scienze umane, che pure contribuiscono a costruire l’immagine comunemente percepita della città e del territorio, del paesaggio e dell’ambiente. La rappresentazione del sociale urbano varia in base all’idea di cosa è, in un dato momento storico e in un dato contesto, una situazione di benessere delle persone. L’urbanistica moderna mirava al massimo benessere del singolo e della collettività e a modellarsi sulle “effettive necessità delle persone”: nei vecchi manuali di urbanistica compare come appendice al piano regolatore il “Piano dei servizi”, che comprende i servizi distribuiti sul territorio circostante, una sorta di “piano regolatore sociale”, per evitare quartieri separati per fasce di popolazione o per classi. Nella città contemporanea la globalizzazione, le nuove forme di marginalizzazione e di esclusione, l’avvento della cosiddetta “new economy”, la ridefinizione della base produttiva e del mercato del lavoro urbani sono espressione di una complessità sociale che può essere definita sulla base delle transazioni e gli scambi simbolici piuttosto che sui processi di industrializzazione e di modernizzazione verso cui era orientata la città storica, definita moderna. Tutto ciò costituisce quel complesso di questioni che attualmente viene definito “nuovo welfare”, in contrapposizione a quello essenzialmente basato sull’istruzione, sulla sanità, sul sistema pensionistico e sull’assistenza sociale. La ricerca ha quindi analizzato gli strumenti tradizionali della pianificazione e programmazione territoriale, nella loro dimensione operativa e istituzionale: la destinazione principale di tali strumenti consiste nella classificazione e nella sistemazione dei servizi e dei contenitori urbanistici. E’ chiaro, tuttavia, che per poter rispondere alla molteplice complessità di domande, bisogni e desideri espressi dalla società contemporanea le dotazioni effettive per “fare città” devono necessariamente superare i concetti di “standard” e di “zonizzazione”, che risultano essere troppo rigidi e quindi incapaci di adattarsi all’evoluzione di una domanda crescente di qualità e di servizi e allo stesso tempo inadeguati nella gestione del rapporto tra lo spazio domestico e lo spazio collettivo. In questo senso è rilevante il rapporto tra le tipologie abitative e la morfologia urbana e quindi anche l’ambiente intorno alla casa, che stabilisce il rapporto “dalla casa alla città”, perché è in questa dualità che si definisce il rapporto tra spazi privati e spazi pubblici e si contestualizzano i temi della strada, dei negozi, dei luoghi di incontro, degli accessi. Dopo la convergenza dalla scala urbana alla scala edilizia si passa quindi dalla scala edilizia a quella urbana, dal momento che il criterio del benessere attraversa le diverse scale dello spazio abitabile. Non solo, nei sistemi territoriali in cui si è raggiunto un benessere diffuso ed un alto livello di sviluppo economico è emersa la consapevolezza che il concetto stesso di benessere sia non più legato esclusivamente alla capacità di reddito collettiva e/o individuale: oggi la qualità della vita si misura in termini di qualità ambientale e sociale. Ecco dunque la necessità di uno strumento di conoscenza della città contemporanea, da allegare al Piano, in cui vengano definiti i criteri da osservare nella progettazione dello spazio urbano al fine di determinare la qualità e il benessere dell’ambiente costruito, inteso come benessere generalizzato, nel suo significato di “qualità dello star bene”. E’ evidente che per raggiungere tale livello di qualità e benessere è necessario provvedere al soddisfacimento da una parte degli aspetti macroscopici del funzionamento sociale e del tenore di vita attraverso gli indicatori di reddito, occupazione, povertà, criminalità, abitazione, istruzione, etc.; dall’altra dei bisogni primari, elementari e di base, e di quelli secondari, culturali e quindi mutevoli, trapassando dal welfare state allo star bene o well being personale, alla wellness in senso olistico, tutte espressioni di un desiderio di bellezza mentale e fisica e di un nuovo rapporto del corpo con l’ambiente, quindi manifestazione concreta di un’esigenza di ben-essere individuale e collettivo. Ed è questa esigenza, nuova e difficile, che crea la diffusa sensazione dell’inizio di una nuova stagione urbana, molto più di quanto facciano pensare le stesse modifiche fisiche della città.

Costrutti ed Applicazioni di Programmazione Generica in Linguaggi Object-Oriented

Generic programming is likely to become a new challenge for a critical mass of developers. Therefore, it is crucial to refine the support for generic programming in mainstream Object-Oriented languages — both at the design and at the implementation level — as well as to suggest novel ways to exploit the additional degree of expressiveness made available by genericity. This study is meant to provide a contribution towards bringing Java genericity to a more mature stage with respect to mainstream programming practice, by increasing the effectiveness of its implementation, and by revealing its full expressive power in real world scenario. With respect to the current research setting, the main contribution of the thesis is twofold. First, we propose a revised implementation for Java generics that greatly increases the expressiveness of the Java platform by adding reification support for generic types. Secondly, we show how Java genericity can be leveraged in a real world case-study in the context of the multi-paradigm language integration. Several approaches have been proposed in order to overcome the lack of reification of generic types in the Java programming language. Existing approaches tackle the problem of reification of generic types by defining new translation techniques which would allow for a runtime representation of generics and wildcards. Unfortunately most approaches suffer from several problems: heterogeneous translations are known to be problematic when considering reification of generic methods and wildcards. On the other hand, more sophisticated techniques requiring changes in the Java runtime, supports reified generics through a true language extension (where clauses) so that backward compatibility is compromised. In this thesis we develop a sophisticated type-passing technique for addressing the problem of reification of generic types in the Java programming language; this approach — first pioneered by the so called EGO translator — is here turned into a full-blown solution which reifies generic types inside the Java Virtual Machine (JVM) itself, thus overcoming both performance penalties and compatibility issues of the original EGO translator. Java-Prolog integration Integrating Object-Oriented and declarative programming has been the subject of several researches and corresponding technologies. Such proposals come in two flavours, either attempting at joining the two paradigms, or simply providing an interface library for accessing Prolog declarative features from a mainstream Object-Oriented languages such as Java. Both solutions have however drawbacks: in the case of hybrid languages featuring both Object-Oriented and logic traits, such resulting language is typically too complex, thus making mainstream application development an harder task; in the case of library-based integration approaches there is no true language integration, and some “boilerplate code” has to be implemented to fix the paradigm mismatch. In this thesis we develop a framework called PatJ which promotes seamless exploitation of Prolog programming in Java. A sophisticated usage of generics/wildcards allows to define a precise mapping between Object-Oriented and declarative features. PatJ defines a hierarchy of classes where the bidirectional semantics of Prolog terms is modelled directly at the level of the Java generic type-system.

Exact Algorithms for Different Classes of Vehicle Routing Problems

We deal with five problems arising in the field of logistics: the Asymmetric TSP (ATSP), the TSP with Time Windows (TSPTW), the VRP with Time Windows (VRPTW), the Multi-Trip VRP (MTVRP), and the Two-Echelon Capacitated VRP (2E-CVRP). The ATSP requires finding a lest-cost Hamiltonian tour in a digraph. We survey models and classical relaxations, and describe the most effective exact algorithms from the literature. A survey and analysis of the polynomial formulations is provided. The considered algorithms and formulations are experimentally compared on benchmark instances. The TSPTW requires finding, in a weighted digraph, a least-cost Hamiltonian tour visiting each vertex within a given time window. We propose a new exact method, based on new tour relaxations and dynamic programming. Computational results on benchmark instances show that the proposed algorithm outperforms the state-of-the-art exact methods. In the VRPTW, a fleet of identical capacitated vehicles located at a depot must be optimally routed to supply customers with known demands and time window constraints. Different column generation bounding procedures and an exact algorithm are developed. The new exact method closed four of the five open Solomon instances. The MTVRP is the problem of optimally routing capacitated vehicles located at a depot to supply customers without exceeding maximum driving time constraints. Two set-partitioning-like formulations of the problem are introduced. Lower bounds are derived and embedded into an exact solution method, that can solve benchmark instances with up to 120 customers. The 2E-CVRP requires designing the optimal routing plan to deliver goods from a depot to customers by using intermediate depots. The objective is to minimize the sum of routing and handling costs. A new mathematical formulation is introduced. Valid lower bounds and an exact method are derived. Computational results on benchmark instances show that the new exact algorithm outperforms the state-of-the-art exact methods.

Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.

Enhanced Mixed Integer Programming Techniques and Routing Problems

Mixed integer programming is up today one of the most widely used techniques for dealing with hard optimization problems. On the one side, many practical optimization problems arising from real-world applications (such as, e.g., scheduling, project planning, transportation, telecommunications, economics and finance, timetabling, etc) can be easily and effectively formulated as Mixed Integer linear Programs (MIPs). On the other hand, 50 and more years of intensive research has dramatically improved on the capability of the current generation of MIP solvers to tackle hard problems in practice. However, many questions are still open and not fully understood, and the mixed integer programming community is still more than active in trying to answer some of these questions. As a consequence, a huge number of papers are continuously developed and new intriguing questions arise every year. When dealing with MIPs, we have to distinguish between two different scenarios. The first one happens when we are asked to handle a general MIP and we cannot assume any special structure for the given problem. In this case, a Linear Programming (LP) relaxation and some integrality requirements are all we have for tackling the problem, and we are ``forced" to use some general purpose techniques. The second one happens when mixed integer programming is used to address a somehow structured problem. In this context, polyhedral analysis and other theoretical and practical considerations are typically exploited to devise some special purpose techniques. This thesis tries to give some insights in both the above mentioned situations. The first part of the work is focused on general purpose cutting planes, which are probably the key ingredient behind the success of the current generation of MIP solvers. Chapter 1 presents a quick overview of the main ingredients of a branch-and-cut algorithm, while Chapter 2 recalls some results from the literature in the context of disjunctive cuts and their connections with Gomory mixed integer cuts. Chapter 3 presents a theoretical and computational investigation of disjunctive cuts. In particular, we analyze the connections between different normalization conditions (i.e., conditions to truncate the cone associated with disjunctive cutting planes) and other crucial aspects as cut rank, cut density and cut strength. We give a theoretical characterization of weak rays of the disjunctive cone that lead to dominated cuts, and propose a practical method to possibly strengthen those cuts arising from such weak extremal solution. Further, we point out how redundant constraints can affect the quality of the generated disjunctive cuts, and discuss possible ways to cope with them. Finally, Chapter 4 presents some preliminary ideas in the context of multiple-row cuts. Very recently, a series of papers have brought the attention to the possibility of generating cuts using more than one row of the simplex tableau at a time. Several interesting theoretical results have been presented in this direction, often revisiting and recalling other important results discovered more than 40 years ago. However, is not clear at all how these results can be exploited in practice. As stated, the chapter is a still work-in-progress and simply presents a possible way for generating two-row cuts from the simplex tableau arising from lattice-free triangles and some preliminary computational results. The second part of the thesis is instead focused on the heuristic and exact exploitation of integer programming techniques for hard combinatorial optimization problems in the context of routing applications. Chapters 5 and 6 present an integer linear programming local search algorithm for Vehicle Routing Problems (VRPs). The overall procedure follows a general destroy-and-repair paradigm (i.e., the current solution is first randomly destroyed and then repaired in the attempt of finding a new improved solution) where a class of exponential neighborhoods are iteratively explored by heuristically solving an integer programming formulation through a general purpose MIP solver. Chapters 7 and 8 deal with exact branch-and-cut methods. Chapter 7 presents an extended formulation for the Traveling Salesman Problem with Time Windows (TSPTW), a generalization of the well known TSP where each node must be visited within a given time window. The polyhedral approaches proposed for this problem in the literature typically follow the one which has been proven to be extremely effective in the classical TSP context. Here we present an overall (quite) general idea which is based on a relaxed discretization of time windows. Such an idea leads to a stronger formulation and to stronger valid inequalities which are then separated within the classical branch-and-cut framework. Finally, Chapter 8 addresses the branch-and-cut in the context of Generalized Minimum Spanning Tree Problems (GMSTPs) (i.e., a class of NP-hard generalizations of the classical minimum spanning tree problem). In this chapter, we show how some basic ideas (and, in particular, the usage of general purpose cutting planes) can be useful to improve on branch-and-cut methods proposed in the literature.

Designing and Programming Organizational Infrastructures for Agents situated in Artifact-based Environments

Actual trends in software development are pushing the need to face a multiplicity of diverse activities and interaction styles characterizing complex and distributed application domains, in such a way that the resulting dynamics exhibits some grade of order, i.e. in terms of evolution of the system and desired equilibrium. Autonomous agents and Multiagent Systems are argued in literature as one of the most immediate approaches for describing such a kind of challenges. Actually, agent research seems to converge towards the definition of renewed abstraction tools aimed at better capturing the new demands of open systems. Besides agents, which are assumed as autonomous entities purposing a series of design objectives, Multiagent Systems account new notions as first-class entities, aimed, above all, at modeling institutional/organizational entities, placed for normative regulation, interaction and teamwork management, as well as environmental entities, placed as resources to further support and regulate agent work. The starting point of this thesis is recognizing that both organizations and environments can be rooted in a unifying perspective. Whereas recent research in agent systems seems to account a set of diverse approaches to specifically face with at least one aspect within the above mentioned, this work aims at proposing a unifying approach where both agents and their organizations can be straightforwardly situated in properly designed working environments. In this line, this work pursues reconciliation of environments with sociality, social interaction with environment based interaction, environmental resources with organizational functionalities with the aim to smoothly integrate the various aspects of complex and situated organizations in a coherent programming approach. Rooted in Agents and Artifacts (A&A) meta-model, which has been recently introduced both in the context of agent oriented software engineering and programming, the thesis promotes the notion of Embodied Organizations, characterized by computational infrastructures attaining a seamless integration between agents, organizations and environmental entities.

Decomposition and reformulation of integer linear programming problems

This thesis deals with an investigation of Decomposition and Reformulation to solve Integer Linear Programming Problems. This method is often a very successful approach computationally, producing high-quality solutions for well-structured combinatorial optimization problems like vehicle routing, cutting stock, p-median and generalized assignment . However, until now the method has always been tailored to the specific problem under investigation. The principal innovation of this thesis is to develop a new framework able to apply this concept to a generic MIP problem. The new approach is thus capable of auto-decomposition and autoreformulation of the input problem applicable as a resolving black box algorithm and works as a complement and alternative to the normal resolving techniques. The idea of Decomposing and Reformulating (usually called in literature Dantzig and Wolfe Decomposition DWD) is, given a MIP, to convexify one (or more) subset(s) of constraints (slaves) and working on the partially convexified polyhedron(s) obtained. For a given MIP several decompositions can be defined depending from what sets of constraints we want to convexify. In this thesis we mainly reformulate MIPs using two sets of variables: the original variables and the extended variables (representing the exponential extreme points). The master constraints consist of the original constraints not included in any slaves plus the convexity constraint(s) and the linking constraints(ensuring that each original variable can be viewed as linear combination of extreme points of the slaves). The solution procedure consists of iteratively solving the reformulated MIP (master) and checking (pricing) if a variable of reduced costs exists, and in which case adding it to the master and solving it again (columns generation), or otherwise stopping the procedure. The advantage of using DWD is that the reformulated relaxation gives bounds stronger than the original LP relaxation, in addition it can be incorporated in a Branch and bound scheme (Branch and Price) in order to solve the problem to optimality. If the computational time for the pricing problem is reasonable this leads in practice to a stronger speed up in the solution time, specially when the convex hull of the slaves is easy to compute, usually because of its special structure.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

Theoretical and implementation aspects in the mechanization of the metatheory of programming languages

Interactive theorem provers are tools designed for the certification of formal proofs developed by means of man-machine collaboration. Formal proofs obtained in this way cover a large variety of logical theories, ranging from the branches of mainstream mathematics, to the field of software verification. The border between these two worlds is marked by results in theoretical computer science and proofs related to the metatheory of programming languages. This last field, which is an obvious application of interactive theorem proving, poses nonetheless a serious challenge to the users of such tools, due both to the particularly structured way in which these proofs are constructed, and to difficulties related to the management of notions typical of programming languages like variable binding. This thesis is composed of two parts, discussing our experience in the development of the Matita interactive theorem prover and its use in the mechanization of the metatheory of programming languages. More specifically, part I covers: - the results of our effort in providing a better framework for the development of tactics for Matita, in order to make their implementation and debugging easier, also resulting in a much clearer code; - a discussion of the implementation of two tactics, providing infrastructure for the unification of constructor forms and the inversion of inductive predicates; we point out interactions between induction and inversion and provide an advancement over the state of the art. In the second part of the thesis, we focus on aspects related to the formalization of programming languages. We describe two works of ours: - a discussion of basic issues we encountered in our formalizations of part 1A of the Poplmark challenge, where we apply the extended inversion principles we implemented for Matita; - a formalization of an algebraic logical framework, posing more complex challenges, including multiple binding and a form of hereditary substitution; this work adopts, for the encoding of binding, an extension of Masahiko Sato's canonical locally named representation we designed during our visit to the Laboratory for Foundations of Computer Science at the University of Edinburgh, under the supervision of Randy Pollack.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

A farm-level programming model to compare the atmospheric impact of conventional and organic farming

A model is developed to represent the activity of a farm using the method of linear programming. Two are the main components of the model, the balance of soil fertility and the livestock nutrition. According to the first, the farm is supposed to have a total requirement of nitrogen, which is to be accomplished either through internal sources (manure) or through external sources (fertilisers). The second component describes the animal husbandry as having a nutritional requirement which must be satisfied through the internal production of arable crops or the acquisition of feed from the market. The farmer is supposed to maximise total net income from the agricultural and the zoo-technical activities by choosing one rotation among those available for climate and acclivity. The perspective of the analysis is one of a short period: the structure of the farm is supposed to be fixed without possibility to change the allocation of permanent crops and the amount of animal husbandry. The model is integrated with an environmental module that describes the role of the farm within the carbon-nitrogen cycle. On the one hand the farm allows storing carbon through the photosynthesis of the plants and the accumulation of carbon in the soil; on the other some activities of the farm emit greenhouse gases into the atmosphere. The model is tested for some representative farms of the Emilia-Romagna region, showing to be capable to give different results for conventional and organic farming and providing first results concerning the different atmospheric impact. Relevant data about the representative farms and the feasible rotations are extracted from the FADN database, with an integration of the coefficients from the literature.

The impact of phosphoinositide metabolic enzymes in glioblastoma: a tale of phosphoinositide-specific phospholipase C PLCβ1 and 5-phosphatase SKIP

Background: Glioblastoma multiforme (GBM) is one of the deadliest and most aggressive form of primary brain tumor. Unfortunately, current GBM treatment therapies are not effective in treating GBM patients. They usually experience very poor prognosis with a median survival of approximately 12 months. Only 3-5% survive up to 3 years or more. A large-scale gene profile study revealed that several genes involved in essential cellular processes are altered in GBM, thus, explaining why existing therapies are not effective. The survival of GBM patients depends on understanding the molecular and key signaling events associated with these altered physiological processes in GBM. Phosphoinositides (PI) form just a tiny fraction of the total lipid content in humans, however they are implicated in almost all essential biological processes, such as acting as second messengers in spatio-temporal regulation of cell signaling, cytoskeletal reorganization, cell adhesion, migration, apoptosis, vesicular trafficking, differentiation, cell cycle and post-translational modifications. Interestingly, these essential processes are altered in GBM. More importantly, incoming reports have associated PI metabolism, which is mediated by several PI phosphatases such as SKIP, lipases such as PLCβ1, and other kinases, to regulate GBM associated cellular processes. Even as PLCβ1 and SKIP are involved in regulating aberrant cellular processes in several other cancers, very few studies, of which majority are in-silico-based, have focused on the impact of PLCβ1 and SKIP in GBM. Hence, it is important to employ clinical, in vitro, and in vivo GBM models to define the actual impact of PLCβ1 and SKIP in GBM. AIM: Since studies of PLCβ1 and SKIP in GBM are limited, this study aimed at determining the pathological impact of PI metabolic enzymes, PLCB1 and SKIP, in GBM patient samples, GBM cell line models, and xenograft models for SKIP. Results: For the first time, this study confirmed through qPCR that PLCβ1 gene expression is lower in human GBM patient samples. Moreover, PLCβ1 gene expression inversely correlates with pathological grades of glioma; it decreases as glioma grades increases or worsens. Silencing PLCβ1 in U87MG GBM cells produces a dual impact in GBM by participating in both pro-tumoral and anti-tumoral roles. PLCβ1 knockdown cells were observed to have more migratory abilities, increased cell to extracellular matrix (ECM) adhesion, transition from epithelial phenotype to mesenchymal phenotype through the upregulation of EMT transcription factors Twist1 and Slug, and mesenchymal marker, vimentin. On the other hand, p-Akt and p-mTOR protein expression were downregulated in PLCβ1 knockdown cells. Thus, the oncogenic pathway PI3K/Akt/mTOR pathway is inhibited during PLCβ1 knockdown. Consistently, cell viability in PLCβ1 knockdown cells were significantly decreased compared to controls. As for SKIP, this study demonstrated that about 48% of SKIP colocalizes with nuclear PtdIns(4,5)P2 to nuclear speckles and that SKIP knockdown alters nuclear PtdIns(4,5)P2 in a cell-type dependent manner. In addition, SKIP silencing increased tumor volume and weight in xenografts than controls by reducing apoptosis and increasing viability. All in all, these data confirm that PLCβ1 and SKIP are involved in GBM pathology and a complete understanding of their roles in GBM may be beneficial.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.