Networking: the "making of" social networks. A closer look at the process and antecedents of some resourcing-oriented behaviors in organizations.

Social networks are one of the “hot” themes in people’s life and contemporary social research. Considering our “embeddedness” in a thick web of social relations is a study perspective that could unveil a number of explanations of how people may manage their personal and social resources. Looking at people’s behaviors of building and managing their social networks, seems to be an effective way to find some possible rationalization about how to help people getting the best from their resources . The main aim of this dissertation is to give a closer look at the role of networking behaviors. Antecedents, motivations, different steps and measures about networking behaviors and outcomes are analyzed and discussed. Results seem to confirm, in a different setting and time perspective, that networking behaviors include different types and goals that change over time. Effects of networking behaviors seem to find empirical confirmation through social network analysis methods. Both personality and situational self-efficacy seem to predict networking behaviors. Different types of motivational drivers seem to be related to diverse networking behaviors.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

On the car sequencing problem: analysis and solution methods

This work deals with the car sequencing (CS) problem, a combinatorial optimization problem for sequencing mixed-model assembly lines. The aim is to find a production sequence for different variants of a common base product, such that work overload of the respective line operators is avoided or minimized. The variants are distinguished by certain options (e.g., sun roof yes/no) and, therefore, require different processing times at the stations of the line. CS introduces a so-called sequencing rule H:N for each option, which restricts the occurrence of this option to at most H in any N consecutive variants. It seeks for a sequence that leads to no or a minimum number of sequencing rule violations. In this work, CS’ suitability for workload-oriented sequencing is analyzed. Therefore, its solution quality is compared in experiments to the related mixed-model sequencing problem. A new sequencing rule generation approach as well as a new lower bound for the problem are presented. Different exact and heuristic solution methods for CS are developed and their efficiency is shown in experiments. Furthermore, CS is adjusted and applied to a resequencing problem with pull-off tables.

Design methods and geometric modelling of scaffolds for bone tissue engineering

Every year, thousand of surgical treatments are performed in order to fix up or completely substitute, where possible, organs or tissues affected by degenerative diseases. Patients with these kind of illnesses stay long times waiting for a donor that could replace, in a short time, the damaged organ or the tissue. The lack of biological alternates, related to conventional surgical treatments as autografts, allografts, e xenografts, led the researchers belonging to different areas to collaborate to find out innovative solutions. This research brought to a new discipline able to merge molecular biology, biomaterial, engineering, biomechanics and, recently, design and architecture knowledges. This discipline is named Tissue Engineering (TE) and it represents a step forward towards the substitutive or regenerative medicine. One of the major challenge of the TE is to design and develop, using a biomimetic approach, an artificial 3D anatomy scaffold, suitable for cells adhesion that are able to proliferate and differentiate themselves as consequence of the biological and biophysical stimulus offered by the specific tissue to be replaced. Nowadays, powerful instruments allow to perform analysis day by day more accurateand defined on patients that need more precise diagnosis and treatments.Starting from patient specific information provided by TC (Computed Tomography) microCT and MRI(Magnetic Resonance Imaging), an image-based approach can be performed in order to reconstruct the site to be replaced. With the aid of the recent Additive Manufacturing techniques that allow to print tridimensional objects with sub millimetric precision, it is now possible to practice an almost complete control of the parametrical characteristics of the scaffold: this is the way to achieve a correct cellular regeneration. In this work, we focalize the attention on a branch of TE known as Bone TE, whose the bone is main subject. Bone TE combines osteoconductive and morphological aspects of the scaffold, whose main properties are pore diameter, structure porosity and interconnectivity. The realization of the ideal values of these parameters represents the main goal of this work: here we'll a create simple and interactive biomimetic design process based on 3D CAD modeling and generative algorithmsthat provide a way to control the main properties and to create a structure morphologically similar to the cancellous bone. Two different typologies of scaffold will be compared: the first is based on Triply Periodic MinimalSurface (T.P.M.S.) whose basic crystalline geometries are nowadays used for Bone TE scaffolding; the second is based on using Voronoi's diagrams and they are more often used in the design of decorations and jewellery for their capacity to decompose and tasselate a volumetric space using an heterogeneous spatial distribution (often frequent in nature). In this work, we will show how to manipulate the main properties (pore diameter, structure porosity and interconnectivity) of the design TE oriented scaffolding using the implementation of generative algorithms: "bringing back the nature to the nature".

Regularization methods for the solution of a nonlinear least-squares problem in tomography

In this work we study a polyenergetic and multimaterial model for the breast image reconstruction in Digital Tomosynthesis, taking into consideration the variety of the materials forming the object and the polyenergetic nature of the X-rays beam. The modelling of the problem leads to the resolution of a high-dimensional nonlinear least-squares problem that, due to its nature of inverse ill-posed problem, needs some kind of regularization. We test two main classes of methods: the Levenberg-Marquardt method (together with the Conjugate Gradient method for the computation of the descent direction) and two limited-memory BFGS-like methods (L-BFGS). We perform some experiments for different values of the regularization parameter (constant or varying at each iteration), tolerances and stop conditions. Finally, we analyse the performance of the several methods comparing relative errors, iterations number, times and the qualities of the reconstructed images.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Image Analysis Methods for Sugar Beet Phenotyping

In un mondo che richiede sempre maggiormente un'automazione delle attività della catena produttiva industriale, la computer vision rappresenta uno strumento fondamentale perciò che viene già riconosciuta internazionalmente come la Quarta Rivoluzione Industriale o Industry 4.0. Avvalendomi di questo strumento ho intrapreso presso l'azienda Syngenta lo studio della problematica della conta automatica del numero di foglie di una pianta. Il problema è stato affrontato utilizzando due differenti approcci, ispirandosi alla letteratura. All'interno dell'elaborato è presente anche la descrizione progettuale di un ulteriore metodo, ad oggi non presente in letteratura. Le metodologie saranno spiegate in dettaglio ed i risultati ottenuti saranno confrontati utilizzando i primi due approcci. Nel capitolo finale si trarranno le conclusioni sulle basi dei risultati ottenuti e dall'analisi degli stessi.

Effectiveness of individual resource-oriented joint protection education in people with rheumatoid arthritis. A randomized controlled trial

the modern joint protection (JP) concept for people with rheumatoid arthritis (RA) is an active coping strategy to improve daily tasks and role performance by changing working methods and using assistive devices. Effective group JP education includes psycho-educational interventions. The Pictorial Representation of Illness and Self Measure (PRISM) is an interactive hands-on-tool, assessing (a) the individual's perceived burden of illness and (b) relevant individual resources. Both issues are important for intrinsic motivation to take action and change behaviour. This study compared individual conventional JP education (C-JP) with PRISM-based JP education (PRISM-JP).

The Use of Human and Conspecific Gestures By Capuchin Monkeys to Solve an Object-Choice Task

Most primates live in highly complex social systems, and therefore have evolved similarly complex methods of communicating with each other. One type of communication is the use of manual gestures, which are only found in primates. No substantial evidence exists indicating that monkeys use communicative gestures in the wild. However, monkeys may demonstrate the ability to learn and/or use gestures in certain experimental paradigms since they¿ve been shown to use other visual cues such as gaze. The purpose of this study was to investigate if ten brown capuchin monkeys (Cebus apella) were able to use gestural cues from monkeys and a pointing cue from a human to obtain a hidden reward. They were then tested to determine if they could transfer this skill from monkeys to humans and from humans to monkeys. One group of monkeys was trained and tested using a conspecific as the cue giver, and was then tested with a human cue-giver. The second group of monkeys began training and testing with a human cue giver, and was then tested with a monkey cue giver. I found that two monkeys were able to use gestural cues from conspecifics (e.g., reaching) to obtain a hidden reward and then transfer this ability to a pointing cue from a human. Four monkeys learned to use the human pointing cue first, and then transferred this ability to use the gestural cues from conspecifics to obtain a hidden reward. However, the number of trials it took for each monkey to transfer the ability varied considerably. Some subjects spontaneously transferred in the minimum number of trials needed to reach my criteria for successfully obtaining hidden rewards (N = 40 trials), while others needed a large number of trials to do so (e.g. N = 190 trials). Two subjects did not perform successfully in any of the conditions in which they were tested. One subject successfully used the human pointing cue and a human pointing plus vocalization cue, but did not learn the conspecific cue. One subject learned to use the conspecific cue but not the human pointing cue. This was the first study to test if brown capuchin monkeys could use gestural cues from conspecifics to solve an object choice task. The study was also the first to test if capuchins could transfer this skill from monkeys to humans and from humans to monkeys. Results showed that capuchin monkeys were able to flexibly use communicative gestures when they were both unintentionally given by a conspecific and intentionally given by a human to indicate a source of food.

[Methods for investigating Trichinella infections in domestic and wild animals]

Trichinellosis is an important parasitic zoonosis that is caused by the intracellular nematode Trichinella spp.. Infection of humans occurs through consumption of raw (or undercooked) meat containing infectious larvae. In Europe, meat from pork, horse, and wild boar have been identified as most important sources of Trichinella infections in humans. In Switzerland, both the domestic pig and wild boar population are considered free of Trichinella. Conversely, Swiss foxes, lynxs and recently a wolf were found to be infected, the species identified in these animals was always referred to as Trichinella britovi. Although this species rarely infects pork and, compared to Trichinella spiralis, only causes reduced pathogenic effects in humans, the basic presence of Trichinella in Switzerland cannot be neglegted. This fact has gained increasing importance since the responsible authorities in the European Union (EU) are preparing regulations for the official Trichinella-control in meat in order to improve food safety for consumers. These regulations will be implemented as a consequence of the recent association of east European countries with the EU. This new legislation particularly takes into account, that in the past by far most cases of human trichinellosis in the EU were due to consumption of imported east European meat.Within the framework of the bilateral agreements of Switzerland with the EU, the Swiss veterinary public health authorities will have to comply with the foreseen EU regulations. Although diagnostic methods for the direct demonstation of Trichinella in pork meat are already routine practice in several Swiss abattoirs, the implementation of a meat control program for Trichinella for the entire slaughter pig population of the country would lead to an enormous increase in costs for the administration and will require an increased infrastructure in veterinary services. In order to find a reduced testing format for monitoring Trichinella infections in Swiss pork, an infection risk-oriented survey strategy is currently evaluated. In the present article, this minimized survey strategy is discussed regarding its compatibility with the EU regulations laying down rules for the official control of meat for Trichinella.

Application of 3D documentation and geometric reconstruction methods in traffic accident analysis: with high resolution surface scanning, radiological MSCT/MRI scanning and real data based animation

The examination of traffic accidents is daily routine in forensic medicine. An important question in the analysis of the victims of traffic accidents, for example in collisions between motor vehicles and pedestrians or cyclists, is the situation of the impact. Apart from forensic medical examinations (external examination and autopsy), three-dimensional technologies and methods are gaining importance in forensic investigations. Besides the post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) for the documentation and analysis of internal findings, highly precise 3D surface scanning is employed for the documentation of the external body findings and of injury-inflicting instruments. The correlation of injuries of the body to the injury-inflicting object and the accident mechanism are of great importance. The applied methods include documentation of the external and internal body and the involved vehicles and inflicting tools as well as the analysis of the acquired data. The body surface and the accident vehicles with their damages were digitized by 3D surface scanning. For the internal findings of the body, post-mortem MSCT and MRI were used. The analysis included the processing of the obtained data to 3D models, determination of the driving direction of the vehicle, correlation of injuries to the vehicle damages, geometric determination of the impact situation and evaluation of further findings of the accident. In the following article, the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation, are shown on two examined cases.

Comparison of tendency-oriented perimetry and dynamic strategy in octopus perimetry as a screening tool in a clinical setting: a prospective study

OBJECTIVE: The aim of this study was to compare the results of tendency-oriented perimetry (TOP) and a dynamic strategy in octopus perimetry as screening methods in clinical practice. DESIGN: A prospective single centre observational case series was performed. PARTICIPANTS AND METHODS: In a newly opened general ophthalmologic practice 89 consecutive patients (171 eyes) with a clinical indication for octopus static perimetry testing (ocular hypertension or suspicious optic nerve cupping) were examined prospectively with TOP and a dynamic strategy. The visual fields were graded by 3 masked observers as normal, borderline or abnormal without any further clinical information. RESULTS: 83% eyes showed the same result for both strategies. In 14% there was a small difference (with one visual field being abnormal or normal, the other being borderline). In only 2.9% of the eyes (5 cases) was there a contradictory result. In 4 out of 5 cases the dynamic visual field was abnormal and TOP was normal. 4 of these cases came back for a second examination. In all 4 the follow-up examination showed a normal second dynamic visual field. CONCLUSIONS: Octopus static perimetry using a TOP strategy is a fast, patient-friendly and very reliable screening tool for the general ophthalmological practice. We found no false-negative results in our series.

Oil and Gas Production Methods in Montana

Montana's oil and gas industries aggregate a gross income of over 12,000,000 annually to the state. Oil and gas fields have been thoroughly discussed in liter­ature as to geology, location, production and future possibilities. The specific object of this report has been to compile a comprehensive study of the production methods as they occur.

Context-Oriented Programming

Context-dependent behavior is becoming increasingly important for a wide range of application domains, from pervasive computing to common business applications. Unfortunately, mainstream programming languages do not provide mechanisms that enable software entities to adapt their behavior dynamically to the current execution context. This leads developers to adopt convoluted designs to achieve the necessary runtime flexibility. We propose a new programming technique called Context-oriented Programming (COP) which addresses this problem. COP treats context explicitly, and provides mechanisms to dynamically adapt behavior in reaction to changes in context, even after system deployment at runtime. In this paper we lay the foundations of COP, show how dynamic layer activation enables multi-dimensional dispatch, illustrate the application of COP by examples in several language extensions, and demonstrate that COP is largely independent of other commitments to programming style.