Essays on firm efficiency with imperfectly competitive input markets: an empirical analysis

In the thesis I exploit an empirical analysis on firm'’s productivity. I relate the efficiency at plant level with the input market features and I suggest an estimation technique for production function that takes into account firm'’s liquidity constraints. The main results are three. When I consider services as inputs for manufacturing firm’'s production process, I find that more competition in service sector affects positively plant’s productivity and export decision. Secondly liquidity constraints are important for the calculation of firm'’s productivity because they are a second source of firm's heterogeneity. Third liquidity constraints are important for firm'’s internationalization

Mechanosensitivity in the myenteric plexus of the guinea pig ileum

The enteric nervous system regulates autonomously from the central nervous system all the reflex pathways that control blood flow, motility, water and electrolyte transport and acid secretion. The ability of the gut to function in isolation is one of the most intriguing phenomenons in neurogastroenterology. This requires coding of sensory stimuli by cells in the gut wall. Enteric neurons are prominent candidates to relay mechanosensitivity. Surprisingly, the identity of mechanosensitive neurons in the enteric nervous system as well as the appropriate stimulus modality is unknown despite the evidence that enteric neurons respond to sustained distension. Objectives: The aim of our study was to record from mechanosensitive neurons using physiological stimulus modalities. Identification of sensory neurons is of central importance to understand sensory transmission under normal conditions and in gut diseases associated with sensorimotor dysfunctions, such as Irritable Bowel Syndrome. Only then it will be possible to identify novel targets that help to normalise sensory functions. Methods: We used guinea-pig ileum myenteric plexus preparations and recorded responses of all neurons in a given ganglion with a fast neuroimaging technique based on voltage sensitive dyes. To evoke a mechanical response we used two different kinds of stimuli: firstly we applied a local mechanical distortion of the ganglion surface with von Frey hair. Secondarily we mimic the ganglia deformation during physiological movements of myenteric ganglia in a freely contracting ileal preparation. We were able to reliably and reproducibly mimic this distortion by intraganglionic injections of small volumes of oxygenated and buffered Krebs solution using stimulus parameters that correspond to single contractions. We also performed in every ganglion tested, electrical stimulations to evoke fast excitatory postsynaptic potentials. Immunohistochemistry reactions were done with antibodies against Calbindin and NeuN, considered markers for sensory neurons. Results: Recordings were performed in 46 ganglia from 31 guinea pigs. In every ganglion tested we found from 1 to 21 (from 3% to 62%) responding cells with a median value of 7 (24% of the total number of neurons). The response consisted of an almost instantaneous spike discharge that showed adaptation. The median value of the action potential frequency in the responding neurons was 2.0 Hz, with a recording time of 1255 ms. The spike discharge lasted for 302 ± 231 ms and occurred only during the initial deformation phase. During sustained deformation no spike discharge was observed. The response was reproducible and was a direct activation of the enteric neurons since it remained after synaptic blockade with hexamethonium or ω-conotoxin and after long time perfusion with capsaicin. Muscle tone appears not to be required for activation of mechanosensory neurons. Mechanosensory neurons showed a response to mechanical stimulation related to the stimulus strength. All mechanosensory neurons received fast synaptic inputs. There was no correlation between mechanosensitivity and Calbindin-IR and NeuN-IR (44% of mechanosensitive neurones Calb-IR-/NeuN-IR-). Conclusions: We identified mechanosensitive neurons in the myenteric plexus of the guinea pig ileum which responded to brief deformation. These cells appear to be rapidly accommodating neurons which respond to dynamic change. All mechanosensitive neurons received fast synaptic input suggesting that their activity can be highly modulated by other neurons and hence there is a low stimulus fidelity which allows adjusting the gain in a sensory network. Mechanosensitivity appears to be a common feature of many enteric neurons belonging to different functional classes. This supports the existence of multifunctional enteric neurons which may fulfil sensory, integrative and motor functions.

Microrganismi probiotici per le piante: una strategia di riduzione degli input nella coltura del pomodoro col metodo biologico

In the recent years, consumers became more aware and sensible in respect to environment and food safety matters. They are more and more interested in organic agriculture and markets and tend to prefer ‘organic’ products more than their traditional counterparts. To increase the quality and reduce the cost of production in organic and low-input agriculture, the 6FP-European “QLIF” project investigated the use of natural products such as bio-inoculants. They are mostly composed by arbuscular mycorrhizal fungi and other microorganisms, so-called “plant probiotic” microorganisms (PPM), because they help keeping an high yield, even under abiotic and biotic stressful conditions. Italian laws (DLgs 217, 2006) have recently included them as “special fertilizers”. This thesis focuses on the use of special fertilizers when growing tomatoes with organic methods in open field conditions, and the effects they induce on yield, quality and microbial rhizospheric communities. The primary objective was to achieve a better understanding of how plant-probiotic micro-flora management could buffer future reduction of external inputs, while keeping tomato fruit yield, quality and system sustainability. We studied microbial rhizospheric communities with statistical, molecular and histological methods. This work have demonstrated that long-lasting introduction of inoculum positively affected micorrhizal colonization and resistance against pathogens. Instead repeated introduction of compost negatively affected tomato quality, likely because it destabilized the ripening process, leading to over-ripening and increasing the amount of not-marketable product. Instead. After two years without any significant difference, the third year extreme combinations of inoculum and compost inputs (low inoculum with high amounts of compost, or vice versa) increased mycorrhizal colonization. As a result, in order to reduce production costs, we recommend using only inoculum rather than compost. Secondly, this thesis analyses how mycorrhizal colonization varies in respect to different tomato cultivars and experimental field locations. We found statistically significant differences between locations and between arbuscular colonization patterns per variety. To confirm these histological findings, we started a set of molecular experiments. The thesis discusses preliminary results and recommends their continuation and refinement to gather the complete results.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.

Wheat and low-input agriculture: agronomic, nutritional and nutraceutical implications

Recently, the increasing interest in organic food products and environmental friendly practices has emphasized the importance of selecting crop varieties suitable for the low-input systems. Additionally, in recent years the relationship between diet and human health has gained much attention among consumers, favoring the investigations on food nutraceutical properties. Among cereals, wheat plays an important role in human nutrition around the world and contributes to the daily intake of essential nutrients such as starch and protein. Moreover, whole grain contains several bioactive compounds that confer to wheat-derived products unique nutraceutical properties (dietary fibre, antioxidants). The present research provided interesting insights for the selection of wheat genotypes suitable for low-input systems and the development of specific breeding programs dedicated to organic farming. The investigation involved 5 old not dwarf genotypes (Andriolo, Frassineto, Gentil rosso, Inallettabile, Verna) and 1 modern dwarf variety (Palesio), grown under biodynamic management, over two consecutive growing seasons (2009/2010, 2010/2011). Results evidenced that under low-input farming some investigated old wheat genotypes (Frassineto, Inallettabile) were comparable to the modern cultivar in terms of whole agronomic performance. As regards the nutritional and nutraceutical properties, some old genotypes (Andriolo, Gentil rosso, Verna) emerged for their relevant content of several investigated phytochemicals (such as insoluble dietary fibre, polyphenols, flavonoids, in vitro antioxidant activity) and nutrients (protein, lipid, minerals). Despite of the low technological features, the six wheat varieties grown under low-input management may efficiently provide raw material for the preparation of traditionally processed bread with valuable sensory and nutritional properties. Results highlighted that old wheat varieties have peculiar phytochemical composition and may be a valuable source of nutraceutical compounds. Some of the genetic material involved in the present study may be used in breeding programs aimed at selecting varieties suitable for low-input farming and rich in health-promoting compounds.

An Input-Process-Output Approach to Interorganizational Teams: The Influence of Work Group Diversity, Trust and Shared Leadership on Communication Network and Team Outputs.

The market’s challenges bring firms to collaborate with other organizations in order to create Joint Ventures, Alliances and Consortia that are defined as “Interorganizational Networks” (IONs) (Provan, Fish and Sydow; 2007). Some of these IONs are managed through a shared partecipant governance (Provan and Kenis, 2008): a team composed by entrepreneurs and/or directors of each firm of an ION. The research is focused on these kind of management teams and it is based on an input-process-output model: some input variables (work group’s diversity, intra-team's friendship network density) have a direct influence on the process (team identification, shared leadership, interorganizational trust, team trust and intra-team's communication network density), which influence some team outputs, individual innovation behaviors and team effectiveness (team performance, work group satisfaction and ION affective commitment). Data was collected on a sample of 101 entrepreneurs grouped in 28 ION’s government teams and the research hypotheses are tested trough the path analysis and the multilevel models. As expected trust in team and shared leadership are positively and directly related to team effectiveness while team identification and interorganizational trust are indirectly related to the team outputs. The friendship network density among the team’s members has got positive effects on the trust in team and on the communication network density, and also, through the communication network density it improves the level of the teammates ION affective commitment. The shared leadership and its effects on the team effectiveness are fostered from higher level of team identification and weakened from higher level of work group diversity, specifically gender diversity. Finally, the communication network density and shared leadership at the individual level are related to the frequency of individual innovative behaviors. The dissertation’s results give a wider and more precise indication about the management of interfirm network through “shared” form of governance.

Integration of Multiple Simultaneous Stimuli within and between Somatosensory sub-Modalities

Psychological characterisation of the somatosensory system often focusses on minimal units of perception, such as detection, localisation, and magnitude estimation of single events. Research on how multiple simultaneous stimuli are aggregated to create integrated, synthetic experiences is rarer. This thesis aims to shed a light on the mechanisms underlying the integration of multiple simultaneous stimuli, within and between different sub-modalities of the somatosensory system. First, we investigated the ability of healthy individuals to perceive the total intensity of composite somatosensory patterns. We found that the overall intensity of tactile, cold, or warm patterns was systematically overestimated when the multiple simultaneous stimuli had different intensities. Perception of somatosensory totals was biased towards the most salient element in the pattern. Furthermore, we demonstrated that peak-biased aggregation is a genuine perceptual phenomenon which does not rely on the discrimination of the parts, but is rather based on the salience of each stimulus. Next, we studied a classical thermal illusion to assess participants’ ability to localise thermal stimuli delivered on the fingers either in isolation, or in uniform and non-uniform patterns. We found that despite a surprisingly high accuracy in reporting the location of a single stimulus, when participants were presented with non-uniform patterns, their ability to identify the thermal state of a specific finger was completely abolished. Lastly, we investigated the perceptual and neural correlates of thermo-nociceptive interaction during the presentation of multiple thermal stimuli. We found that inhibition of pain by warmth was independent from both the position and the number of thermal stimuli administered. Our results suggest that nonlinear integration of multiple stimuli, within and between somatosensory sub-modalities, may be an efficient way by which the somatosensory system synthesises the complexity of reality, providing an extended and coherent perception of the world, in spite of its deep bandwidth limitations.

Colocated multiple-input multiple-output radars for smart mobility

In recent years, radars have been used in many applications such as precision agriculture and advanced driver assistant systems. Optimal techniques for the estimation of the number of targets and of their coordinates require solving multidimensional optimization problems entailing huge computational efforts. This has motivated the development of sub-optimal estimation techniques able to achieve good accuracy at a manageable computational cost. Another technical issue in advanced driver assistant systems is the tracking of multiple targets. Even if various filtering techniques have been developed, new efficient and robust algorithms for target tracking can be devised exploiting a probabilistic approach, based on the use of the factor graph and the sum-product algorithm. The two contributions provided by this dissertation are the investigation of the filtering and smoothing problems from a factor graph perspective and the development of efficient algorithms for two and three-dimensional radar imaging. Concerning the first contribution, a new factor graph for filtering is derived and the sum-product rule is applied to this graphical model; this allows to interpret known algorithms and to develop new filtering techniques. Then, a general method, based on graphical modelling, is proposed to derive filtering algorithms that involve a network of interconnected Bayesian filters. Finally, the proposed graphical approach is exploited to devise a new smoothing algorithm. Numerical results for dynamic systems evidence that our algorithms can achieve a better complexity-accuracy tradeoff and tracking capability than other techniques in the literature. Regarding radar imaging, various algorithms are developed for frequency modulated continuous wave radars; these algorithms rely on novel and efficient methods for the detection and estimation of multiple superimposed tones in noise. The accuracy achieved in the presence of multiple closely spaced targets is assessed on the basis of both synthetically generated data and of the measurements acquired through two commercial multiple-input multiple-output radars.

New chemical modalities for leishmaniasis drug discovery

Leishmaniasis is one of the major parasitic diseases among neglected tropical diseases with a high rate of morbidity and mortality. Human migration and climate change have spread the disease from limited endemic areas all over the world, also reaching regions in Southern Europe, and causing significant health and economic burden. The currently available treatments are far from ideal due to host toxicity, elevated cost, and increasing rates of drug resistance. Safer and more effective drugs are thus urgently required. Nevertheless, the identification of new chemical entities for leishmaniasis has proven to be incredibly hard and exacerbated by the scarcity of well-validated targets. Trypanothione reductase (TR) represents one robustly validated target in Leishmania that fulfils most of the requirements for a good drug target. However, due to the large and featureless active site, TR is considered extremely challenging and almost undruggable by small molecules. This scenario advocates the development of new chemical entities by unlocking new modalities for leishmaniasis drug discovery. The classical toolbox for drug discovery has enormously expanded in the last decade, and medicinal chemists can now strategize across a variety of new chemical modalities and a vast chemical space, to efficiently modulate challenging targets and provide effective treatments. Beyond others, Targeted p Protein Degradation (TPD) is an emerging strategy that uses small molecules to hijack endogenous proteolysis systems to degrade disease-relevant proteins and thus reduce their abundance in the cell. Based on these considerations, this thesis aimed to develop new strategies for leishmaniasis drug discovery while embracing novel chemical modalities and navigating the chemical space by chasing unprecedented chemotypes. This has been achieved by four complementary projects. We believe that these next-generation chemical modalities for leishmaniasis will play an important role in what was previously thought to be a drug discovery landscape dominated by small molecules.

User scheduling for low earth orbit multi-user multiple-input-multiple-output non-terrestrial network systems

In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.