Self-Organizing Mechanisms for Task Allocation in a Knowledge-Based Economy

A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of “Knowledge-based economy” indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (people’s skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a “supervisory problem” (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because ‘the nominal supervisors will not know the best way of doing the job – or even the precise purpose of the specialist job itself – and the worker will know better’ (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that’ why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Carbon fluxes and allocation pattern in an apple orchard

Carbon fluxes and allocation pattern, and their relationship with the main environmental and physiological parameters, were studied in an apple orchard for one year (2010). I combined three widely used methods: eddy covariance, soil respiration and biometric measurements, and I applied a measurement protocol allowing a cross-check between C fluxes estimated using different methods. I attributed NPP components to standing biomass increment, detritus cycle and lateral export. The influence of environmental and physiological parameters on NEE, GPP and Reco was analyzed with a multiple regression model approach. I found that both NEP and GPP of the apple orchard were of similar magnitude to those of forests growing in similar climate conditions, while large differences occurred in the allocation pattern and in the fate of produced biomass. Apple production accounted for 49% of annual NPP, organic material (leaves, fine root litter, pruned wood and early fruit drop) contributing to detritus cycle was 46%, and only 5% went to standing biomass increment. The carbon use efficiency (CUE), with an annual average of 0.68 ± 0.10, was higher than the previously suggested constant values of 0.47-0.50. Light and leaf area index had the strongest influence on both NEE and GPP. On a diurnal basis, NEE and GPP reached their peak approximately at noon, while they appeared to be limited by high values of VPD and air temperature in the afternoon. The proposed models can be used to explain and simulate current relations between carbon fluxes and environmental parameters at daily and yearly time scale. On average, the annual NEP balanced the carbon annually exported with the harvested apples. These data support the hypothesis of a minimal or null impact of the apple orchard ecosystem on net C emission to the atmosphere.

Scenari finanziari e portafogli ottimi: modelli di previsione e strategie per l'asset allocation tattica

Le scelte di asset allocation costituiscono un problema ricorrente per ogni investitore. Quest’ultimo è continuamente impegnato a combinare diverse asset class per giungere ad un investimento coerente con le proprie preferenze. L’esigenza di supportare gli asset manager nello svolgimento delle proprie mansioni ha alimentato nel tempo una vasta letteratura che ha proposto numerose strategie e modelli di portfolio construction. Questa tesi tenta di fornire una rassegna di alcuni modelli innovativi di previsione e di alcune strategie nell’ambito dell’asset allocation tattica, per poi valutarne i risvolti pratici. In primis verificheremo la sussistenza di eventuali relazioni tra la dinamica di alcune variabili macroeconomiche ed i mercati finanziari. Lo scopo è quello di individuare un modello econometrico capace di orientare le strategie dei gestori nella costruzione dei propri portafogli di investimento. L’analisi prende in considerazione il mercato americano, durante un periodo caratterizzato da rapide trasformazioni economiche e da un’elevata volatilità dei prezzi azionari. In secondo luogo verrà esaminata la validità delle strategie di trading momentum e contrarian nei mercati futures, in particolare quelli dell’Eurozona, che ben si prestano all’implementazione delle stesse, grazie all’assenza di vincoli sulle operazioni di shorting ed ai ridotti costi di transazione. Dall’indagine emerge che entrambe le anomalie si presentano con carattere di stabilità. I rendimenti anomali permangono anche qualora vengano utilizzati i tradizionali modelli di asset pricing, quali il CAPM, il modello di Fama e French e quello di Carhart. Infine, utilizzando l’approccio EGARCH-M, verranno formulate previsioni sulla volatilità dei rendimenti dei titoli appartenenti al Dow Jones. Quest’ultime saranno poi utilizzate come input per determinare le views da inserire nel modello di Black e Litterman. I risultati ottenuti, evidenziano, per diversi valori dello scalare tau, extra rendimenti medi del new combined vector superiori al vettore degli extra rendimenti di equilibrio di mercato, seppur con livelli più elevati di rischio.

Constraint based methods for allocation and scheduling of periodic applications

This work presents exact algorithms for the Resource Allocation and Cyclic Scheduling Problems (RA&CSPs). Cyclic Scheduling Problems arise in a number of application areas, such as in hoist scheduling, mass production, compiler design (implementing scheduling loops on parallel architectures), software pipelining, and in embedded system design. The RA&CS problem concerns time and resource assignment to a set of activities, to be indefinitely repeated, subject to precedence and resource capacity constraints. In this work we present two constraint programming frameworks facing two different types of cyclic problems. In first instance, we consider the disjunctive RA&CSP, where the allocation problem considers unary resources. Instances are described through the Synchronous Data-flow (SDF) Model of Computation. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms. We propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. Results show that the approach can handle realistic instances in terms of size and complexity. Next, we tackle the Cyclic Resource-Constrained Scheduling Problem (i.e. CRCSP). We propose a Constraint Programming approach based on modular arithmetic: in particular, we introduce a modular precedence constraint and a global cumulative constraint along with their filtering algorithms. Many traditional approaches to cyclic scheduling operate by fixing the period value and then solving a linear problem in a generate-and-test fashion. Conversely, our technique is based on a non-linear model and tackles the problem as a whole: the period value is inferred from the scheduling decisions. The proposed approaches have been tested on a number of non-trivial synthetic instances and on a set of realistic industrial instances achieving good results on practical size problem.

Effects of pesticides on honey bees (Apis mellifera L.): study of a specific route of exposure and evaluation of biochemical-physiological changes in the assessment of the pesticides toxicity

In this study, some important aspects of the relationship between honey bees (Apis mellifera L.) and pesticides have been investigated. In the first part of the research, the effects of the exposure of honey bees to neonicotinoids and fipronil contaminated dusts were analyzed. In fact, considerable amounts of these pesticides, employed for maize seed dressing treatments, may be dispersed during the sowing operations, thus representing a way of intoxication for honey bees. In particular, a specific way of exposure to this pesticides formulation, the indirect contact, was taken into account. To this aim, we conducted different experimentations, in laboratory, in semi-field and in open field conditions in order to assess the effects on mortality, foraging behaviour, colony development and capacity of orientation. The real dispersal of contaminated dusts was previously assessed in specific filed trials. In the second part, the impact of various pesticides (chemical and biological) on honey bee biochemical-physiological changes, was evaluated. Different ways and durations of exposure to the tested products were also employed. Three experimentations were performed, combining Bt spores and deltamethrin, Bt spores and fipronil, difenoconazole and deltamethrin. Several important enzymes (GST, ALP, SOD, CAT, G6PDH, GAPDH) were selected in order to test the pesticides induced variations in their activity. In particular, these enzymes are involved in different pathways of detoxification, oxidative stress defence and energetic metabolism. The results showed a significant effect on mortality of neonicotinoids and fipronil contaminated dusts, both in laboratory and in semi-field trials. However, no effects were evidenced in honey bees orientation capacity. The analysis of different biochemical indicators highlighted some interesting physiological variations that can be linked to the pesticide exposure. We therefore stress the attention on the possibility of using such a methodology as a novel toxicity endpoint in environmental risk assessment.

Au(I) Catalyzed Manipulation of Propargylic Alcohols: A New Route Towards the Synthesis of Indole Alkaloids

In this work we presented several aspects regarding the possibility to use readily available propargylic alcohols as acyclic precursors to develop new stereoselective [Au(I)]-catalyzed cascade reactions for the synthesis of highly complex indole architectures. The use of indole-based propargylic alcohols of type 1 in a stereoselective [Au(I)]-catalyzed hydroindolynation/immiun trapping reactive sequence opened access to a new class of tetracyclic indolines, dihydropyranylindolines A and furoindolines B. An enantioselective protocol was futher explored in order to synthesize this molecules with high yields and ee. The suitability of propargylic alcohols in [Au(I)]-catalyzed cascade reactions was deeply investigated by developing cascade reactions in which was possible not only to synthesize the indole core but also to achieve a second functionalization. Aniline based propargylic alcohols 2 were found to be modular acyclic precursors for the synthesis of [1,2-a] azepinoindoles C. In describing this reactivity we additionally reported experimental evidences for an unprecedented NHCAu(I)-vinyl specie which in a chemoselective fashion, led to the annulation step, synthesizing the N1-C2-connected seven membered ring. The chemical flexibility of propargylic alcohols was further explored by changing the nature of the chemical surrounding with different preinstalled N-alkyl moiety in propargylic alcohols of type 3. Particularly, in the case of a primary alcohol, [Au(I)] catalysis was found to be prominent in the synthesis of a new class of [4,3-a]-oxazinoindoles D while the use of an allylic alcohol led to the first example of [Au(I)] catalyzed synthesis and enantioselective functionalization of this class of molecules (D*). With this work we established propargylic alcohols as excellent acyclic precursor to developed new [Au(I)]-catalyzed cascade reaction and providing new catalytic synthetic tools for the stereoselective synthesis of complex indole/indoline architectures.

Innovative asymmetric organocatalytic processess: en route to the synthesis of biologically relevant compounds

This doctoral thesis deals with the development of novel organocatalytic strategies for asymmetric transformation. The intrinsic versatility of organocatalysis and the use of different activation modes have been exploited to achieve new catalytic enantioselective processes, towards the synthesis of biologically relevant scaffolds. The most investigated organocatalytic system have been those based on H-bond interaction (such as chiral thioureas or phosphoric acids) as well as the ones based on aminocatalysis. Despite conceptually distinct, the transformations detailed in this Thesis are linked together by simple and recurring modes of activation, induction and reactivity, promoted by the catalysts employed. The chemical diversity of the challenges encountered allows to get a precious overall view on organocatalysis, highlighting that enormous chemical diversity can be created by judicious choice of select catalyst.